📉Graphical Representation: Insight (Just the Quotes)

"The truth is that one display is better than another if it leads to more understanding. Often a simpler display, one that tries to accomplish less at one time, succeeds in conveying more insight. In order to understand complicated or subtle structure in the data we should be prepared to look at complicated displays when necessary, but to see any particular type of structure we should use the simplest display that shows it." (John M Chambers et al, "Graphical Methods for Data Analysis", 1983)

"Understandability implies that the graph will mean something to the audience. If the presentation has little meaning to the audience, it has little value. Understandability is the difference between data and information. Data are facts. Information is facts that mean something and make a difference to whoever receives them. Graphic presentation enhances understanding in a number of ways. Many people find that the visual comparison and contrast of information permit relationships to be grasped more easily. Relationships that had been obscure become clear and provide new insights." (Anker V Andersen, "Graphing Financial Information: How accountants can use graphs to communicate", 1983)

"Why does representing information in terms of natural frequencies rather than probabilities or percentages foster insight? For two reasons. First, computational simplicity: The representation does part of the computation. And second, evolutionary and developmental primacy: Our minds are adapted to natural frequencies." (Gerd Gigerenzer, "Calculated Risks: How to know when numbers deceive you", 2002)

"Dashboards aren't all that different from some of the other means of presenting information, but when properly designed the single-screen display of integrated and finely tuned data can deliver insight in an especially powerful way." (Richard Brath & Michael Peters, "Dashboard Design: Why Design is Important," DM Direct, 2004)

"Graphical displays are often constructed to place principal focus on the individual observations in a dataset, and this is particularly helpful in identifying both the typical positions of datapoints and unusual or influential cases. However, in many investigations, principal interest lies in identifying the nature of underlying trends and relationships between variables, and so it is often helpful to enhance graphical displays in ways which give deeper insight into these features. This can be very beneficial both for small datasets, where variation can obscure underlying patterns, and large datasets, where the volume of data is so large that effective representation inevitably involves suitable summaries." (Adrian W Bowman, "Smoothing Techniques for Visualisation" [in "Handbook of Data Visualization"], 2008)

"The main goal of data visualization is its ability to visualize data, communicating information clearly and effectively. It doesn’t mean that data visualization needs to look boring to be functional or extremely sophisticated to look beautiful. To convey ideas effectively, both aesthetic form and functionality need to go hand in hand, providing insights into a rather sparse and complex dataset by communicating its key aspects in a more intuitive way. Yet designers often tend to discard the balance between design and function, creating gorgeous data visualizations which fail to serve its main purpose - communicate information." (Vitaly Friedman, "Data Visualization and Infographics", Smashing Magazine, 2008)

"For a visual to qualify as beautiful, it must be aesthetically pleasing, yes, but it must also be novel, informative, and efficient. [...] For a visual to truly be beautiful, it must go beyond merely being a conduit for information and offer some novelty: a fresh look at the data or a format that gives readers a spark of excitement and results in a new level of understanding. Well-understood formats (e.g., scatterplots) may be accessible and effective, but for the most part they no longer have the ability to surprise or delight us. Most often, designs that delight us do so not because they were designed to be novel, but because they were designed to be effective; their novelty is a byproduct of effectively revealing some new insight about the world." (Noah Iliinsky, "On Beauty", [in "Beautiful Visualization"] 2010)

"Done well, annotation can help explain and facilitate the viewing and interpretive experience. It is the challenge of creating a layer of user assistance and user insight: how can you maximize the clarity and value of engaging with this visualization design?" (Andy Kirk, "Data Visualization: A successful design process", 2012)

"A common mistake is that all visualization must be simple, but this skips a step. You should actually design graphics that lend clarity, and that clarity can make a chart 'simple' to read. However, sometimes a dataset is complex, so the visualization must be complex. The visualization might still work if it provides useful insights that you wouldn’t get from a spreadsheet. […] Sometimes a table is better. Sometimes it’s better to show numbers instead of abstract them with shapes. Sometimes you have a lot of data, and it makes more sense to visualize a simple aggregate than it does to show every data point." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"For every rule in data visualization, there is a scenario where that rule should be broken. This means that choosing the best chart or the best design is always a trade-off between several conflicting goals. Our imperfect perception means that data visualization has a larger subjective dimension than a data table. Sometimes we only need this subjective, impressionist dimension and other times we need to translate it into hard figures. Striving for accuracy is important, but it’s more important to provide those insights that only a visual display can reveal." (Jorge Camões, "Data at Work: Best practices for creating effective charts and information graphics in Microsoft Excel", 2016)

"Are your insights based on data that is accurate and reliable? Trustworthy data is correct or valid, free from significant defects and gaps. The trustworthiness of your data begins with the proper collection, processing, and maintenance of the data at its source. However, the reliability of your numbers can also be influenced by how they are handled during the analysis process. Clean data can inadvertently lose its integrity and true meaning depending on how it is analyzed and interpreted." (Brent Dykes, "Effective Data Storytelling: How to Drive Change with Data, Narrative and Visuals", 2019)

"Before you can even consider creating a data story, you must have a meaningful insight to share. One of the essential attributes of a data story is a central or main insight. Without a main point, your data story will lack purpose, direction, and cohesion. A central insight is the unifying theme (telos appeal) that ties your various findings together and guides your audience to a focal point or climax for your data story. However, when you have an increasing amount of data at your disposal, insights can be elusive. The noise from irrelevant and peripheral data can interfere with your ability to pinpoint the important signals hidden within its core." (Brent Dykes, "Effective Data Storytelling: How to Drive Change with Data, Narrative and Visuals", 2019)

"When narrative is coupled with data, it helps to explain to your audience what’s happening in the data and why a particular insight is important. Ample context and commentary are often needed to fully appreciate an analysis finding. The narrative element adds structure to the data and helps to guide the audience through the meaning of what’s being shared." (Brent Dykes, "Effective Data Storytelling: How to Drive Change with Data, Narrative and Visuals", 2019)

📉Graphical Representation: Communication (Just the Quotes)

"Good design looks right. It is simple (clear and uncomplicated). Good design is also elegant, and does not look contrived. A map should be aesthetically pleasing, thought provoking, and communicative." (Arthur H Robinson, "Elements of Cartography", 1953)

"A drawing can show a true picture of both the situation as a whole and its separate components at a glance, and do the job better than could figures or the spoken word. In its essence, a chart is a medium of communication conveying a thought, an idea, a situation from one mind to another and not a work of art or a statistical table. The simpler, the more direct it is, the better it will perform that service which is its sole function." (Anna C Rogers, "Graphic Charts Handbook", 1961)

"To see is to reason. Thus, the use of visual forms of communication has great potential for influencing what a person thinks. Graphic presentation is always much more than a way to present just facts or information. Rather, it is a way to influence thought, and, as such, graphics can be a powerful mode of persuasion." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"Graphical excellence is the well-designed presentation of interesting data - a matter of substance, of statistics, and of design. Graphical excellence consists of complex ideas communicated with clarity, precision, and efficiency. Graphical excellence is that which gives to the viewer the greatest number of ideas in the shortest time with the least ink in the smallest space. Graphical excellence is nearly always multivariate. And graphical excellence requires telling the truth about the data." (Edward R Tufte, "The Visual Display of Quantitative Information", 1983)

"The effective communication of information in visual form, whether it be text, tables, graphs, charts or diagrams, requires an understanding of those factors which determine the 'legibility', 'readability' and 'comprehensibility', of the information being presented. By legibility we mean: can the data be clearly seen and easily read? By readability we mean: is the information set out in a logical way so that its structure is clear and it can be easily scanned? By comprehensibility we mean: does the data make sense to the audience for whom it is intended? Is the presentation appropriate for their previous knowledge, their present information needs and their information processing capacities?" (Linda Reynolds & Doig Simmonds, "Presentation of Data in Science" 4th Ed, 1984)

"Despite the prevailing use of graphs as metaphors for communicating and reasoning about dependencies, the task of capturing informational dependencies by graphs is not at all trivial." (Judea Pearl, "Probabilistic Reasoning in Intelligent Systems: Network of Plausible Inference", 1988)

"We envision information in order to reason about, communicate, document, and preserve that knowledge - activities nearly always carried out on two-dimensional paper and computer screen. Escaping this flatland and enriching the density of data displays are the essential tasks of information design." (Edward R Tufte, "Envisioning Information", 1990)

"A good chart delineates and organizes information. It communicates complex ideas, procedures, and lists of facts by simplifying, grouping, and setting and marking priorities. By spatial organization, it should lead the eye through information smoothly and efficiently." (Mary H Briscoe, "Preparing Scientific Illustrations: A guide to better posters, presentations, and publications" 2nd ed., 1995)

"Graphical design notations have been with us for a while [...] their primary value is in communication and understanding. A good diagram can often help communicate ideas about a design, particularly when you want to avoid a lot of details. Diagrams can also help you understand either a software system or a business process. As part of a team trying to figure out something, diagrams both help understanding and communicate that understanding throughout a team. Although they aren't, at least yet, a replacement for textual programming languages, they are a helpful assistant." (Martin Fowler, "UML Distilled: A Brief Guide to the Standard Object Modeling", 2004)

"One graph is more effective than another if its quantitative information can be decoded more quickly or more easily by most observers. […] This definition of effectiveness assumes that the reason we draw graphs is to communicate information - but there are actually many other reasons to draw graphs." (Naomi B Robbins, "Creating More effective Graphs", 2005)

"An effective dashboard is the product not of cute gauges, meters, and traffic lights, but rather of informed design: more science than art, more simplicity than dazzle. It is, above all else, about communication." (Stephen Few, "Information Dashboard Design", 2006)

"Most dashboards fail to communicate efficiently and effectively, not because of inadequate technology (at least not primarily), but because of poorly designed implementations. No matter how great the technology, a dashboard's success as a medium of communication is a product of design, a result of a display that speaks clearly and immediately. Dashboards can tap into the tremendous power of visual perception to communicate, but only if those who implement them understand visual perception and apply that understanding through design principles and practices that are aligned with the way people see and think." (Stephen Few, "Information Dashboard Design", 2006)

"Communication is the primary goal of data visualization. Any element that hinders - rather than helps - the reader, then, needs to be changed or removed: labels and tags that are in the way, colors that confuse or simply add no value, uncomfortable scales or angles. Each element needs to serve a particular purpose toward the goal of communicating and explaining information. Efficiency matters, because if you’re wasting a viewer’s time or energy, they’re going to move on without receiving your message." (Noah Iliinsky & Julie Steel, "Designing Data Visualizations", 2011)

"The art side of the field [data visualization] refers to the scope for unleashing design flair and encouraging innovation, where you strive to design communications that appeal on an aesthetic level and then survive in the mind on an emotional one." (Andy Kirk, "Data Visualization: A successful design process", 2012)

"[...] communicating with data is less often about telling a specific story and more like starting a guided conversation. It is a dialogue with the audience rather than a monologue. While some data presentations may share the linear approach of a traditional story, other data products (analytical tools, in particular) give audiences the flexibility for exploration. In our experience, the best data products combine a little of both: a clear sense of direction defined by the author with the ability for audiences to focus on the information that is most relevant to them. The attributes of the traditional story approach combined with the self-exploration approach leads to the guided safari analogy." (Zach Gemignani et al, "Data Fluency", 2014)

"Commonly, data do not make a clear and unambiguous statement about our world, often requiring tools and methods to provide such clarity. These methods, called statistical data analysis, involve collecting, manipulating, analyzing, interpreting, and presenting data in a form that can be used, understood, and communicated to others." (Forrest W Young et al, "Visual Statistics: Seeing data with dynamic interactive graphics", 2016)

"The first rule of communication is to shut up and listen, so that you can get to know about the audience for your communication, whether it might be politicians, professionals or the general public. We have to understand their inevitable limitations and any misunderstandings, and fight the temptation to be too sophisticated and clever, or put in too much detail." (David Spiegelhalter, "The Art of Statistics: Learning from Data", 2019)

"The second rule of communication is to know what you want to achieve. Hopefully the aim is to encourage open debate, and informed decision-making. But there seems no harm in repeating yet again that numbers do not speak for themselves; the context, language and graphic design all contribute to the way the communication is received. We have to acknowledge we are telling a story, and it is inevitable that people will make comparisons and judgements, no matter how much we only want to inform and not persuade. All we can do is try to pre-empt inappropriate gut reactions by design or warning." (David Spiegelhalter, "The Art of Statistics: Learning from Data", 2019)

"While visuals are an essential part of data storytelling, data visualizations can serve a variety of purposes from analysis to communication to even art. Most data charts are designed to disseminate information in a visual manner. Only a subset of data compositions is focused on presenting specific insights as opposed to just general information. When most data compositions combine both visualizations and text, it can be difficult to discern whether a particular scenario falls into the realm of data storytelling or not." (Brent Dykes, "Effective Data Storytelling: How to Drive Change with Data, Narrative and Visuals", 2019)

"Communicating data through functionally aesthetic charts is not only about perception and precision but also understanding." (Vidya Setlur & Bridget Cogley, "Functional Aesthetics for data visualization", 2022)

"Communication requires the ability to expand or contract a message based on norms within a given culture or language. Expansion provides more detail, sometimes adding in information that is culturally relevant or needed for the person to understand. Contraction preserves the same intent but discards information that isn't needed by that person. Some concepts in certain situations require greater detail than others." (Vidya Setlur & Bridget Cogley, "Functional Aesthetics for data visualization", 2022)

"Conversational repair is the process people use to detect and resolve problems in communicating, receiving, and understanding. Through repair, participants in social interaction display how they establish and maintain communication and mutual understanding. Language interpretation formalizes multiple levels of repair, from monitoring and evaluating various benchmarks of accuracy to proper ways to intervene and seek clarification." (Vidya Setlur & Bridget Cogley, "Functional Aesthetics for data visualization", 2022)

📉Graphical Representation: Attention (Just the Quotes)

"The visible figures by which principles are illustrated should, so far as possible, have no accessories. They should be magnitudes pure and simple, so that the thought of the pupil may not be distracted, and that he may know what features of the thing represented he is to pay attention to." (National Education Association, 1894)

"Though variety in method of charting is sometimes desirable in large reports where numerous illustrations must follow each other closely, or in wall exhibits where there must be a great number of charts in rapid sequence, it is better in general to use a variety of effects simply to attract attention, and to present the data themselves according to standard well-known methods." (Willard C Brinton, "Graphic Methods for Presenting Facts", 1919)

"Graphic charts have often been thought to be tools of those alone who are highly skilled in mathematics, but one needs to have a knowledge of only eighth-grade arithmetic to use intelligently even the logarithmic or ratio chart, which is considered so difficult by those unfamiliar with it. […] If graphic methods are to be most effective, those who are unfamiliar with charts must give some attention to their fundamental structure. Even simple charts may be misinterpreted unless they are thoroughly understood. For instance, one is not likely to read an arithmetic chart correctly unless he also appreciates the significance of a logarithmic chart." (John R Riggleman & Ira N Frisbee, "Business Statistics", 1938)

"In making up the charts, keep them simple. One idea to a page and not too much detail is a good rule. Try to get variety in the subject matter - now a chart, next a diagram, then a tabulation. Such variety helps hold audience attention." (Edward J Hegarty, "How to Use a Set of Display Charts", The American Statistician Vol. 2 (5), 1948)

"Charts and graphs are a method of organizing information for a unique purpose. The purpose may be to inform, to persuade, to obtain a clear understanding of certain facts, or to focus information and attention on a particular problem. The information contained in charts and graphs must, obviously, be relevant to the purpose. For decision-making purposes. information must be focused clearly on the issue or issues requiring attention. The need is not simply for 'information', but for structured information, clearly presented and narrowed to fit a distinctive decision-making context. An advantage of having a 'formula' or 'model' appropriate to a given situation is that the formula indicates what kind of information is needed to obtain a solution or answer to a specific problem." (Cecil H Meyers, "Handbook of Basic Graphs: A modern approach", 1970)

"Graphic misrepresentation is a frequent misuse in presentations to the nonprofessional. The granddaddy of all graphical offenses is to omit the zero on the vertical axis. As a consequence, the chart is often interpreted as if its bottom axis were zero, even though it may be far removed. This can lead to attention-getting headlines about 'a soar' or 'a dramatic rise (or fall)'. A modest, and possibly insignificant, change is amplified into a disastrous or inspirational trend." (Herbert F Spirer et al, "Misused Statistics" 2nd Ed, 1998)

"Color can tell us where to look, what to compare and contrast, and it can give us a visual scale of measure. Because color can be so effective, it is often used for multiple purposes in the same graphic - which can create graphics that are dazzling but difficult to interpret. Separating the roles that color can play makes it easier to apply color specifically for encouraging different kinds of visual thinking. [...] Choose colors to draw attention, to label, to show relationships (compare and contrast), or to indicate a visual scale of measure." (Felice C Frankel & Angela H DePace, "Visual Strategies", 2012)

"Competition for your audiences attention is fierce. The fact that infographics are unique allows organizations an opportunity to make the content they are publishing stand out and get noticed." (Mark Smiciklas, "The Power of Inforgraphics", 2012)

"Upon discovering a visual image, the brain analyzes it in terms of primitive shapes and colors. Next, unity contours and connections are formed. As well, distinct variations are segmented. Finally, the mind attracts active attention to the significant things it found. That process is permanently running to react to similarities and dissimilarities in shapes, positions, rhythms, colors, and behavior. It can reveal patterns and pattern-violations among the hundreds of data values. That natural ability is the most important thing used in diagramming." (Vasily Pantyukhin, "Principles of Design Diagramming", 2015)

"Using a table in a live presentation is rarely a good idea. As your audience reads it, you lose their ears and attention to make your point verbally." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"Usually, diagrams contain some noise - information unrelated to the diagram’s primary goal. Noise is decorations, redundant, and irrelevant data, unnecessarily emphasized and ambiguous icons, symbols, lines, grids, or labels. Every unnecessary element draws attention away from the central idea that the designer is trying to share. Noise reduces clarity by hiding useful information in a fog of useless data. You may quickly identify noise elements if you can remove them from the diagram or make them less intense and attractive without compromising the function." (Vasily Pantyukhin, "Principles of Design Diagramming", 2015)

"Data storytelling gives your insight the best opportunity to capture attention, be understood, be remembered, and be acted on. An effective data story helps your insight reach its full potential: inspiring others to act and drive change." (Brent Dykes, "Effective Data Storytelling: How to Drive Change with Data, Narrative and Visuals", 2019)

"People see bar charts and line charts and pie charts all the time, and those charts are often boring. Boring graphs are forgettable. Different shapes and uncommon forms that move beyond the borders of our typical data visualization experience can draw readers in." (Jonathan Schwabish, "Better Data Visualizations: A guide for scholars, researchers, and wonks", 2021)

"Data generation is part of knowledge production. It is the generation of material that can help frame a debate or dispel a myth. As designers of visualizations, we choose what data and which stories are amplified through our work. As critical visualization designers, we assume a responsibility for producing those stories and for the ways they were produced." (Peter A Hall & Patricio Dávila, "Critical Visualization: Rethinking the Representation of Data", 2022)

📉Graphical Representation: Simplicity (Just the Quotes)

"Graphic charts have often been thought to be tools of those alone who are highly skilled in mathematics, but one needs to have a knowledge of only eighth-grade arithmetic to use intelligently even the logarithmic or ratio chart, which is considered so difficult by those unfamiliar with it. […] If graphic methods are to be most effective, those who are unfamiliar with charts must give some attention to their fundamental structure. Even simple charts may be misinterpreted unless they are thoroughly understood. For instance, one is not likely to read an arithmetic chart correctly unless he also appreciates the significance of a logarithmic chart." (John R Riggleman & Ira N Frisbee, "Business Statistics", 1938)

"In many instances, a picture is indeed worth a thousand words. To make this true in more diverse circumstances, much more creative effort is needed to pictorialize the output from data analysis. Naive pictures are often extremely helpful, but more sophisticated pictures can be both simple and even more informative." (John W Tukey & Martin B Wilk, "Data Analysis and Statistics: An Expository Overview", 1966)

"Pencil and paper for construction of distributions, scatter diagrams, and run-charts to compare small groups and to detect trends are more efficient methods of estimation than statistical inference that depends on variances and standard errors, as the simple techniques preserve the information in the original data." (W Edwards Deming, "On Probability as Basis for Action", American Statistician Vol. 29 (4), 1975)

"The more complex the shape of any object. the more difficult it is to perceive it. The nature of thought based on the visual apprehension of objective forms suggests, therefore, the necessity to keep all graphics as simple as possible. Otherwise, their meaning will be lost or ambiguous, and the ability to convey the intended information and to persuade will be inhibited." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"Understanding is accomplished through: (a) the use of relative size of the shapes used in the graphic; (b) the positioning of the graphic-line forms; (c) shading; (d) the use of scales of measurement; and (e) the use of words to label the forms in the graphic. In addition. in order for a person to attach meaning to a graphic it must also be simple, clear, and appropriate." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"The truth is that one display is better than another if it leads to more understanding. Often a simpler display, one that tries to accomplish less at one time, succeeds in conveying more insight. In order to understand complicated or subtle structure in the data we should be prepared to look at complicated displays when necessary, but to see any particular type of structure we should use the simplest display that shows it." (John M Chambers et al, "Graphical Methods for Data Analysis", 1983)

"What about confusing clutter? Information overload? Doesn't data have to be ‘boiled down’ and  ‘simplified’? These common questions miss the point, for the quantity of detail is an issue completely separate from the difficulty of reading. Clutter and confusion are failures of design, not attributes of information." (Edward R Tufte, "Envisioning Information", 1990)

"Graphical illustrations should be simple and pleasing to the eye, but the presentation must remain scientific. In other words, we want to avoid those graphical features that are purely decorative while keeping a critical eye open for opportunities to enhance the scientific inference we expect from the reader. A good graphical design should maximize the proportion of the ink used for communicating scientific information in the overall display." (Phillip I Good & James W Hardin, "Common Errors in Statistics (and How to Avoid Them)", 2003)

"An effective dashboard is the product not of cute gauges, meters, and traffic lights, but rather of informed design: more science than art, more simplicity than dazzle. It is, above all else, about communication." (Stephen Few, "Information Dashboard Design", 2006)

"A common mistake is that all visualization must be simple, but this skips a step. You should actually design graphics that lend clarity, and that clarity can make a chart 'simple' to read. However, sometimes a dataset is complex, so the visualization must be complex. The visualization might still work if it provides useful insights that you wouldn’t get from a spreadsheet. […] Sometimes a table is better. Sometimes it’s better to show numbers instead of abstract them with shapes. Sometimes you have a lot of data, and it makes more sense to visualize a simple aggregate than it does to show every data point." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"The biggest thing to know is that data visualization is hard. Really difficult to pull off well. It requires harmonization of several skills sets and ways of thinking: conceptual, analytic, statistical, graphic design, programmatic, interface-design, story-telling, journalism - plus a bit of ‘gut feel.’ The end result is often simple and beautiful, but the process itself is usually challenging and messy." (David McCandless, 2013)

"What is good visualization? It is a representation of data that helps you see what you otherwise would have been blind to if you looked only at the naked source. It enables you to see trends, patterns, and outliers that tell you about yourself and what surrounds you. The best visualization evokes that moment of bliss when seeing something for the first time, knowing that what you see has been right in front of you, just slightly hidden. Sometimes it is a simple bar graph, and other times the visualization is complex because the data requires it." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"It’s important to note that parsimony and simplicity are not absolute principles. We should not take them to the extreme and risk losing useful elements for understanding." (Jorge Camões, "Data at Work: Best practices for creating effective charts and information graphics in Microsoft Excel", 2016)

"Dashboards are collections of several linked visualizations all in one place. The idea is very popular as part of business intelligence: having current data on activity summarized and presented all in one place. One danger of cramming a lot of disparate information into one place is that you will quickly hit information overload. Interactivity and small multiples are definitely worth considering as ways of simplifying the information a reader has to digest in a dashboard. As with so many other visualizations, layering the detail for different readers is valuable." (Robert Grant, "Data Visualization: Charts, Maps and Interactive Graphics", 2019)

"Visualisation is any technique for creating images, diagrams or animations to communicate a message; techniques used to communicate data or information by encoding it as visual objects, e.g., points, lines or bars contained in graphics. One of the most important benefits of visualisation is that it allows us visual access to huge amounts of data in easily digestible visuals. Well designed data graphics are usually the simplest, and at the same time, the most powerful." (C S V Murthy, "Data and Businesss Analytics", 2020) 

"Cartographers employed a minimalist visual language and the simplicity of lines and geometry to lend an air of objectivity, universality and clarity. The sparse treatment of visuals suggests a more direct correspondence between the data and the representation, and less human involvement. It communicates that the image has been reduced to its bare minimum. It has been polished through successive passes to remove the unnecessary and the contingent. And in doing so, it indicates something essential and closer to a transcendent type, or perhaps an ideal." (Peter A Hall & Patricio Dávila, "Critical Visualization: Rethinking the Representation of Data", 2022)

📈Graphical Representation: Tree (Definitions)

"A complex data structure built from nodes, each of which points to two or more other nodes." (Jesse Liberty, "Sams Teach Yourself C++ in 24 Hours" 3rd Ed., 2001)

"In the hierarchical data mode, a single entity hierarchy." (Jan L Harrington, "Relational Database Design and Implementation" 3rd Ed., 2009)

"A structure for data relationships where all relationships are one-to-many and no child entity may have more than one parent entity." (Jan L Harrington, "SQL Clearly Explained" 3rd Ed., 2010)

"A graph in which child nodes do not have more than one parent. SEE ALSO chart; graph; structure, tree." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A hierarchy of things from the same population. The things could be a) instances from a population represented by a single type icon representing the population of instances, and a reflexive relationship on that type, or b) types from the set of types defined in a database represented by a tree structure where each node of the tree is a population of instances of the same type. In the first case, it is the instances that form a tree structure, and in the second, it is the types that form a tree structure. The latter is called a hierarchical data structure." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A linked data structure that forms a hierarchy where nodes at higher levels know about a subset of the nodes in the level below them. Each node in a tree can only be reached from a single node in the level above it." (Mark C Lewis, "Introduction to the Art of Programming Using Scala", 2012)

"A structure with a unique starting node (the root), in which each node is capable of having multiple child nodes, and in which a unique path exists from the root to every other node" (Nell Dale et al, "Object-Oriented Data Structures Using Java" 4th Ed., 2016)

"A tree is a constrained graph. Trees are directed graphs because the 'parent of' relationship between nodes is asymmetric: the edges are arrows that point in a certain direction. Trees are acyclic graphs, because if you follow the directed edges from one node to another, you can never encounter the same node twice. Finally, trees have the constraint that every node (except the root) must have exactly one parent." (Robert J Glushko, "The Discipline of Organizing: Professional Edition, 4th Ed", 2016)

"Trees consist of nodes joined by edges, recursively nested. When a single, root dictionary is connected to child nodes that are themselves dictionaries, we say that the dictionaries are nested into a kind of tree structure." (Robert J Glushko, "The Discipline of Organizing: Professional Edition" 4th Ed., 2016)

"Hierarchical data structure where each node may have any number of child nodes, but only one parent node (with the exception of the root node, which has no parent)." (Karl Beecher, "Computational Thinking - A beginner's guide to problem-solving and programming", 2017)

📈Graphical Representation: PERT Chart (Definitions)

"A type of network planning chart." (Michael S Dobson, "The Juggler's Guide to Managing Multiple Projects", 2003)

"Diagram that displays the dependency relationships between tasks." (Clyde M Creveling, "Six Sigma for Technical Processes", 2006)

"Diagram that displays the dependency relationships that exist between tasks and helps to discern the variation in expected task time." (Lynne Hambleton, "Treasure Chest of Six Sigma Growth Methods, Tools, and Best Practices", 2007)

"Project Evaluation and Review Technique; a graphical representation of work tasks and their predecessor and successor relations." (Bruce P Douglass, "Real-Time Agility", 2009)

"a type of chart used in project management, where tasks are represented as circles, and arrows between tasks are used to show the sequence and task dependencies." (Bill Holtsnider & Brian D Jaffe, "IT Manager's Handbook" 3rd Ed., 2012)

"A graph that uses nodes (circles or boxes) and links (arrows) to show the precedence relationships among the tasks in a project." (Rod Stephens, "Beginning Software Engineering", 2015)

🚧Project Management: Program (Definitions)

"(1) A project. (2) A collection of related projects and the infrastructure that supports them, including objectives, methods, activities, plans, and success measures." (Sandy Shrum et al, "CMMI®: Guidelines for Process Integration and Product Improvement", 2003)

"A set of projects pointed toward the same objective." (Steve Williams & Nancy Williams, "The Profit Impact of Business Intelligence", 2007)

"A group of related projects managed in a coordinated way to obtain benefits and control not available from managing them individually. Programs may include elements of related work outside of the scope of the discrete projects in the program." (Cynthia Stackpole, "PMP® Certification All-in-One For Dummies®", 2011)

"A collection of projects with a common success criteria under integrated management. These projects consist of people, technology, and processes aimed at implementing significant business and technology change. A program is a major enterprise initiative, an element in the overall business strategy and direction." (Paul C Dinsmore et al, "Enterprise Project Governance", 2012)

"A portfolio of projects and initiatives managed together - sharing something critical like joint objectives or a common resource pool." (Mike Clayton, "Brilliant Project Leader", 2012)

"A group of related projects, subprograms, and program activities that are managed in a coordinated way to obtain benefits not available from managing them individually." (PMI, "Implementing Organizational Project Management: A Practice Guide", 2014)

"An endeavor that seeks to deliver benefits via activities that by their nature have uncertain outcomes. The uncertainty associated with programs dictates that they need to be managed adaptively, so that their strategies and plans can be modified in response to emergent outcomes. As a result, programs may be highly complex. The outcomes required by programs are pursued via projects, subprograms, and other program-related activities." (Richard J Heaslip, "Managing Complex Projects and Programs", 2014)

"Coordinated set of change projects that provide business benefits to the organization." (Gilbert Raymond & Philippe Desfray, "Modeling Enterprise Architecture with TOGAF", 2014)

"Related projects, subsidiary programs, and program activities that are managed in a coordinated manner to obtain benefits not available from managing them individually." (Project Management Institute, "A Guide to the Project Management Body of Knowledge (PMBOK® Guide)" 6th Ed., 2017)

"A group of related projects, subsidiary programs, and program activities managed in a coordinated way to obtain benefits not available from managing them individually. May include work outside the scope of projects but will always have two or more projects within its scope." (H James Harrington & William S Ruggles, "Project Management for Performance Improvement Teams", 2018)

"Projects/activities planned and managed together to achieve an overall set of related objectives and outcomes" (ITIL)

📈Graphical Representation: Flow Chart (Definitions)

"A flow chart is a graphic method to show pictorially how a series of activities, procedures. operations. events. ideas, or other factors are related to each other. It shows the sequence, cycle. or flow of these factors and how they are connected in a series of steps from beginning to end." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"A flow chart is a diagram that visually displays interrelated information such as events, steps in a process, functions, etc., in an organized fashion, such as sequentially or chronologically. The things being represented can be tangible or intangible." (Robert L Harris, "Information Graphics: A Comprehensive Illustrated Reference", 1996)

"A pictorial representation of the flow of logic." (Greg Perry, "Sams Teach Yourself Beginning Programming in 24 Hours" 2nd Ed., 2001)

"An activity that defines the flow chart modeling style. Child activities can be added to this activity, and direct connections can be defined between the activities to control the flow of execution." (Bruce Bukovics, "Pro WF: Windows Workflow in .NET 4", 2010)

[flowcharting:] "The depiction in a diagram format of the inputs, process actions, and outputs of one or more processes within a system." (Cynthia Stackpole, "PMP® Certification All-in-One For Dummies®", 2011)

"A means of depicting a process from beginning to end, using flowcharting symbols to indicate the type of tasks in the process." (Charles Cooper & Ann Rockley, "Managing Enterprise Content: A Unified Content Strategy" 2nd Ed., 2012)

[flowcharting:] "A graphical method for depicting the movement of items, customers, or information though a system. Although many of the symbols were originally developed with information processing in mind, they have been adapted in various forms to map other process flows." (Kenneth A Shaw, "Integrated Management of Processes and Information", 2013)

"The depiction in a diagram format of the inputs, process actions, and outputs of one or more processes within a system." (For Dummies, "PMP Certification All-in-One For Dummies" 2nd Ed., 2013)

"A diagram that represents an algorithm or process. Some organizations use flow charts in troubleshooting guides to help technicians diagnose problems. They are also useful when developing expert systems." (Darril Gibson, "Effective Help Desk Specialist Skills", 2014)

📈Graphical Representation: Heatmaps (Definitions)

"A chart where one set of values is represented by areas of rectangles, and other sets of values are represented by colors. [...] the size of a rectangle reflects its importance, and color conveys the speed of change." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A type of map presentation where the intensity of color for each polygon corresponds to the related analytical data. For example, low values in a range appear as blue (cold) and high values as red (hot)." (Microsoft, "SQL Server 2012 Glossary", 2012)

"A heat map is a graphical representation where the data values are mapped to color intensities. The name heat map refers to the popular color-encoding where high values are encoded to hotter colors such as reds and yellows and smaller values are encoded to greens and blues. However, a heat map can have any color encoding that is convenient." (Ira Greenberg et al, "Processing: Creative Coding and Generative Art in Processing 2", 2013)

"A color-coded matrix generated by stakeholders voting on risk level by color (e.g., red being highest)." (Robert F Smallwood, "Information Governance: Concepts, Strategies, and Best Practices", 2014)

"Heatmap is a visualization that displays the expression values of the features (genes, exons, etc.) using a color scale. Features are typically arranged in columns (samples) and rows (features) as in the original data matrix. Each feature-sample pair is represented with a small rectangle that is colored according to its expression. Often both samples and features are hierarchically clustered before constructing the heatmap, and clustering is represented with a tree on the left and top from the colored data matrix." (Eija Korpelainen et al, "RNA-seq Data Analysis: A Practical Approach", 2014)

"[Heatmap is] a special kind of tile map, which is a two-dimensional graphical representation of data having values displayed using colors instead of numbers, text, or markers (data  points). It provides an easy way to understand and analyze complex/huge data sets. It applies blurring of markers and shading (dark or light) on the basis of the total amount of overlap."  (Yuvraj Gupta, "Kibana Essentials", 2015)

"Heatmaps are two-dimensional graphical representations of data where the values of a variable are shown as colors." (Agnieszka Bojkon, "Informative or Misleading? Heatmaps Deconstructed", [in "Human-Computer Interaction: New Trends, 13th International Conference"] 2009) 

"A heat map is a graphical representation of a table of data. The individual values are arranged in a table/matrix and represented by colors. Use grayscale or gradient for coloring. Sorting of the variables changes the color pattern." (Kristen Sosulski, "Data Visualization Made Simple: Insights into Becoming Visual", 2019)

"A heat map is a thematic map in which areas are shaded or patterned in proportion to the measurement of the statistical variable being displayed on the map, such as population density or per capita income. Heat maps provide an easy way to visualize how a measurement varies across a geographic area or show the level of variability within a region." (Sankar N. Nair & E S Gopi,  "Deep Learning Techniques for Crime Hotspot Detection", 2020)

"A heatmap is a visualization where values contained in a matrix are represented as colors or color saturation. Heatmaps are great for visualizing multivariate data (data in which analysis is based on more than two variables per observation), where categorical variables are placed in the rows and columns and a numerical or categorical variable is represented as colors or color saturation." (Mario Döbler & Tim Großmann, "The Data Visualization Workshop", 2nd Ed., 2020)

"Heatmap is another representational way in which the frequencies of the various parameters of the data set is represented in different colors, much like an image captured by a thermal imaging camera in which the graph consists of varying temperatures and the temperatures are differentiated according to the colors." (Shreyans Pathak & Shashwat Pathak, "Data Visualization Techniques, Model and Taxonomy", 2020)

"A heatmap is a plot that shows the magnitude of a phenomenon as color in two dimensions. The color variation may be by hue or intensity." (Swapnil Saurav, "Python Apps on Visual Studio Code", 2024)

📈Graphical Representation: Bar Chart (Definitions)

"A graphic that uses rectangular bars in varying lengths to represent comparisons of amounts." (Jennifer George-Palilonis, "A Practical Guide to Graphics Reporting", 2006)

"A chart that shows bars to illustrate frequencies or values for individual categories." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A horizontal bar chart used in project management; a graphical illustration of a schedule that helps to plan, coordinate, and track specific tasks in a project." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A graphic display of schedule-related information. In the typical bar chart, schedule activities or work breakdown structure components are listed down the left side of the chart, dates are shown across the top, and activity durations are shown as date-placed horizontal bars." (For Dummies, "PMP Certification All-in-One For Dummies" 2nd Ed., 2013)

"A graphical representation of project activities shown in a time-scaled bar line with no links shown between activities." (Peter Oakander et al, "CPM Scheduling for Construction: Best Practices and Guidelines", 2014)

"A chart that uses horizontal bars to represent values." (Faithe Wempen, "Computing Fundamentals: Introduction to Computers", 2015)

"It is a statistical presentation technique that represents frequency data as horizontal or vertical bars. Bar charts are used to represent time series and quantitative data." (K  N Krishnaswamy et al, "Management Research Methodology: Integration of Principles, Methods and Techniques", 2016)

📈Graphical Representation: Gantt Chart (Definitions)

"A chart that represents project activities as horizontal lines whose length shows the time span of each activity. The ends of each line correspond to the start and finish milestones, indicated by triangles. Progress is indicated by filling in the triangles when milestones are completed. Gantt charts are useful for simple schedules, but do not show task dependencies. Resource loaded networks (RLNs) should be used for projects with many interdependent tasks." (Richard D Stutzke, "Estimating Software-Intensive Systems: Projects, Products, and Processes", 2005)

"A bar chart (named after Henry Gantt) that shows when tasks start and finish as well as the relationships between tasks." (Bonnie Biafore, "Successful Project Management: Applying Best Practices and Real-World Techniques with Microsoft Project", 2011)

"A horizontal bar chart used in project management; a graphical illustration of a schedule that helps to plan, coordinate, and track specific tasks in a project. Named for Henry Gantt." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A tool developed by Henry Gantt that helps a project manager to plan, communicate and manage a project. Shows project activities as horizontal bars, with a length that represents the duration of the task, and places them against a fixed timeline." (Mike Clayton, "Brilliant Project Leader", 2012)

📈Graphical Representation: Infographic (Definitions)

"an infographic is defined as a visualization of data or ideas that tries to convey complex information to an audience in a manner that can be quickly consumed and easily understood." (Mark Smiciklas, "The Power of Infographics: Using Pictures to Communicate and Connect with Your Audiences", 2012)

"Tools and techniques involved in graphical representation of data, mostly in journalism, art, and storytelling." (Anna Ursyn, "Visualization as Communication with Graphic Representation", 2015)

"Use of visual images such as charts, graphic organizers, diagrams, photos, etc. in teaching and learning." (Esther Ntuli, "Active Learning Strategies in Technology Integrated K-12 Classrooms", 2015)

"Information graphics that are visual representations of data or information." (Julie A Delello & Rochell R McWhorter, "New Visual Literacies and Competencies for Education and the Workplace", 2016)

 "Information or data represented as a visual image in a chart or diagram. An infographic can be an excellent way to conceptualize dense text or numbers in ways that appeal to the eye and engage the reader." (Kindra Cotton et al, "Leveraging New Media as Social Capital for Diversity Officers", 2016)

"A short-form, visual representation of information, data, or knowledge presented through simple images that highlight patterns, trends, or insights. Simplified from the term information graphic." (Jonathan Ferrar et al, "The Power of People: Learn How Successful Organizations Use Workforce Analytics To Improve Business Performance", 2017)

[Infographic Map:] "Diagrammatic 'visualizations' of the space of knowledge and its associative logics that allows to use its own 'form' as a tool to 'act' on complex systems of knowledge." (Alessandra Cirafici & Alessandra Avella, "A Virtual Museum of Pompeii 'ex Votos': Design Strategies", 2020)

"Graphic visual representations of information, data or knowledge intended to present complex information quickly and clearly." (Jing Zhou, "Connecting Art, Culture, Science, and Technology", 2021)

"a form of communication that uses visual language and text. Both languages are complementary, part of a whole, and therefore can’t be understood when separate" (Jaime Serra)

"An infographic is a visual form of content used as a medium to represent and share information, knowledge, and data." (Infographic World)

"An infographic is an edited, summarized presentation of data selected by a designer to tell a story. A visualization is a display designed to explore data so every reader will be able to extract his or her own stories" (Alberto Cairo)

🔹SQL Server: Model Database (Definitions)

"A template for new user databases. The installation process creates model when SQL Server is installed. Each time the create database command is issued, SQL Server makes a copy of model and extends it to the size requested, if necessary." (Karen Paulsell et al, "Sybase SQL Server: Performance and Tuning Guide", 1996)

"An SQL Server–supplied database that provides a template for new user databases. Each time a database is created, SQL Server makes a copy of the model database, sizes it to the requested size, and files the user database with the system tables and objects currently defined in the model database." (Patrick Dalton, "Microsoft SQL Server Black Book", 1997)

"A database installed with SQL Server that provides the template for new user databases. Each time a database is created, SQL Server makes a copy of the model and then extends it to the size requested. A new database cannot be smaller than the model. The model database contains the system tables required for each user database. You can modify the model to add objects that you want in all newly created databases." (Microsoft Corporation, "SQL Server 7.0 System Administration Training Kit", 1999)

"A database installed with SQL Server that provides the template for new user databases. SQL Server 2000 creates a new database by copying in the contents of the model database and then expanding it to the size requested." (Anthony Sequeira & Brian Alderman, "The SQL Server 2000 Book", 2003)

"The template used when creating new databases. Any new database is created from a copy of the Model database and then modified from there." (Darril Gibson, "MCITP SQL Server 2005 Database Developer All-in-One Exam Guide", 2008)

"A database that is installed with Microsoft SQL Server and that provides the template for new user databases. SQL Server creates a database by copying in the contents of the model database and then expanding the new database to the size requested." (Microsoft, SQL Server 2012 Glossary", 2012)

📈Graphical Representation: Causal Loop Diagrams (Definition)

"One of the tools of systems thinking. Causal loop diagrams capture how variables in a system are interrelated. A CLD takes the form of a closed loop that depicts cause-and-effect linkages." (Virginia Anderson & Lauren Johnson, "Systems Thinking Basics: From Concepts to Casual Loops", 1997)

"A CLD is a graphic model of some of the key system variables connected by arrows that denote the causal influences among the variables. Each arrowhead is identified as either positive (+) or negative (-) to indicate how the dependent variable changes when the independent variable changes." (Daniel D Burke, System Dynamics-based Computer Simulations and Evaluation, 2006)

"A CLD is diagrammatic tool used to describe the causal relationship between key quantities and to identify feedback mechanisms." (Dina Neiger & Leonid Churilov, "Integration of Diagrammatic Business Modeling Tools", 2008)

"A network of actuators connected together is called a causal loop diagram. A causal loop diagram shows how potential business actions lead to complex dynamic effects." (David M Bridgeland & Ron Zahavi, "Business Modeling: A Practical Guide to Realizing Business Value", 2009)

"A tool that captures the causal interrelationships amongst a set of variables. CLDs reveal systemic patterns underlying complex relationships and highlight hidden causes and unintended consequences." (Kambiz E Maani, "Systems Thinking and the Internet from Independence to Interdependence", 2009)

"Causal loop diagramming is a form of cause-and-effect modeling. The diagrams represent systems and their behaviors as a collection of nodes and links. Nodes represent the things in a system, and links illustrate interactions and influences." (Olivia Parr Rudd, "Business Intelligence Success Factors: Tools for Aligning Your Business in the Global Economy", 2009)

"Causal loop diagrams (CLDs) are a kind of systems thinking tool. These diagrams consist of arrows connecting variables (things that change over time) in a way that shows how one variable affects another." (Raed M Al-Qirem & Saad G Yaseen, "Modelling a Small Firm in Jordan Using System Dynamics", 2010)

"A visual representation of a system's feedback loops, where positive loops cycle clockwise, and negative loops cycle counter-clockwise." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"In systems thinking terms, causal loop diagrams are simplified ways to describe essential elements and relationships in a system. These diagrams include curved causal-link arrows (depicting influence from cause to effect) and the polarity of that linkage. An 's' indicates that cause and effect move in the same direction and an  'o' shows that they move in opposite directions (e.g., when cause increases, effect decreases below what it would have been). Causal-link arrows combine into balancing (B) and reinforcing (R) feedback loops. Significant lags between an action and the effects of that action appear as 'delay' on the causal-link arrows." (Karen L Higgins, "Economic Growth and Sustainability: Systems Thinking for a Complex World", 2015)

"A causal loop diagram (CLD) is a causal diagram that aids in visualizing how a number of variables in a system are interrelated and drive cause-and-effect processes. The diagram consists of a set of nodes and edges. Nodes represent the variables, and edges are the links that represent a connection or a relation between the two variables." (Andreas F Vermeulen, "Practical Data Science: A Guide to Building the Technology Stack for Turning Data Lakes into Business Assets", 2018)

"Methodology to build conceptual or simulation models depicting the causal structure of a complex system." (Francesca Costanza & Pietro Fontana, "Distributing Mutual Advantages in Italian Cooperatives: An Analysis of Patronage Refunds", 2019)

"In system dynamics modelling, they are closed causal chains involving relevant variables, whose interactions are responsible for the patterns of behavior taking place within a certain system." (Francesca Costanza, "Managing Patients' Organizations to Improve Healthcare: Emerging Research and Opportunities", 2020)

📈Graphical Representation: Pareto Chart/Diagram (Definitions)

"Fundamental tool for determining which characteristic is causing problems in a given process. Constructed by categorizing data, ranking, and plotting frequency of occurrence in bar-chart form in descending order along the x axis. Sometimes dollars are plotted on the y axis to emphasize the cost factor." (Alan Wa Steiss, "Strategic Management for Public and Nonprofit Organizations", 2003)

"A graphical tool for ranking causes from most significant to least significant." (Sohail Anwar, "Quality Management and Control", 2009)

"A chart showing both bars and a line, where the line shows the cumulative total of the individual bars going left to right." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A histogram, ordered by frequency of occurrence, that shows how many results were generated by each identified cause." (Cynthia Stackpole, "PMP® Certification All-in-One For Dummies", 2011)

"A method of displaying data values over time and classification" (Daniel Linstedt & W H Inmon, "Data Architecture: A Primer for the Data Scientist", 2014)

"A basic Pareto chart analyzes the unique values of a process variable, which are referred to as Pareto categories or levels. These values typically represent problems encountered during some phase of a manufacturing or service activity." (SAS)

"A Pareto chart is a bar graph. The lengths of the bars represent frequency or cost (time or money), and are arranged with longest bars on the left and the shortest to the right. In this way the chart visually depicts which situations are more significant." (ASQ) [source]

[Pareto analysis] "A statistical technique in decision making that is used for selection of a limited number of factors that produce significant overall effect. In terms of quality improvement, a large majority of problems (80%) are produced by a few key causes (20%)." (IQBBA)

📈Graphical Representation: Data Flow Diagram (Definitions)

"A diagram that shows the data flows in an organization, including sources of data, where data are stored, and processes that transform data." (Jan L Harrington, "Relational Database Dessign: Clearly Explained" 2nd Ed., 2002)

"A diagram of the data flow from sources through processes and files to users. A source or user is represented by a square; a data file is represented by rectangles with missing righthand edges; a process is represented by a circle or rounded rectangle; and a data flow is represented by an arrow." (Jens Mende, "Data Flow Diagram Use to Plan Empirical Research Projects", 2009)

"A diagram used in functional analysis which specifies the functions of the system, the inputs/outputs from/to external (user) entities, and the data being retrieved from or updating data stores. There are well-defined rules for specifying correct DFDs, as well as for creating hierarchies of interrelated DFDs." (Peretz Shoval & Judith Kabeli, "Functional and Object-Oriented Methodology for Analysis and Design", 2009)

[Control Data Flow Graph (CDFG):] " Represents the control flow and the data dependencies in a program." (Alexander Dreweke et al, "Text Mining in Program Code", 2009)

"A graphic method for documenting the flow of data within an organization." (Jan L Harrington, "Relational Database Design and Implementation: Clearly explained" 3rd Ed., 2009)

"A graphic representation of the interactions between different processes in an organization in terms of data flow communications among them. This may be a physical data flow diagram that describes processes and flows in terms of the mechanisms involved, a logical data flow diagram that is without any representation of the mechansm, or an essential data flow diagram that is a logical data flow diagram organized in terms of the processes that respond to each external event." (David C Hay, "Data Model Patterns: A Metadata Map", 2010)

"Data-flow diagrams (DFDs) are system models that show a functional perspective where each transformation represents a single function or process. DFDs are used to show how data flows through a sequence of processing steps." (Ian Sommerville, "Software Engineering" 9th Ed., 2011)

"A model of the system that shows the system’s processes, the data that flow between them (hence the name), and the data stores used by the processes. The data flow diagram shows the system as a network of processes, and is thought to be the most easily recognized of all the analysis models." (James Robertson et al, "Complete Systems Analysis: The Workbook, the Textbook, the Answers", 2013)

"A picture of the movement of data between external entities and the processes and data stores within a system." (Jeffrey A Hoffer et al, "Modern Systems Analysis and Design" 7th Ed., 2014)

"A schematic indicating the direction of the movement of data" (Daniel Linstedt & W H Inmon, "Data Architecture: A Primer for the Data Scientist", 2014)

"A Data Flow Diagram (DFD) is a graphical representation of the 'flow' of data through an information system, modeling its process aspects. Often it is a preliminary step used to create an overview of the system that can later be elaborated." (Henrikvon Scheel et al, "Process Concept Evolution", 2015)

"Data flow maps are tools that graphically represent the results of a comprehensive data assessment to illustrate what information comes into an organization, for what purposes that information is used, and who has access to that information." (James R Kalyvas & Michael R Overly, "Big Data: A Business and Legal Guide", 2015)

"A graphical representation of the logical or conceptual movement of data within an existing or planned system." (George Tillmann, "Usage-Driven Database Design: From Logical Data Modeling through Physical Schmea Definition", 2017)

"a visual depiction using standard symbols and conventions of the sources of, movement of, operations on, and storage of data." (Meredith Zozus, "The Data Book: Collection and Management of Research Data", 2017)

"A data-flow diagram is a way of representing a flow of data through a process or a system (usually an information system). The DFD also provides information about the outputs and inputs of each entity and the process itself." (Wikipedia) [source]

"A graphical representation of the sequence and possible changes of the state of data objects, where the state of an object is any of: creation, usage, or destruction." (IQBBA)

📈Graphical Representation: Cause-Effect Diagram (Definitions)

"A chart that can be used to systematically gather the problem causes of quality defects. Sometimes referred to as the 5M- or 6M-chart because most causes can be related to man (e.g., human factors), machine, method, material, milieu (i.e., the work environment), or the medium (the IT-platform)." (Martin J Eppler, "Managing Information Quality" 2nd Ed., 2006)

"A root cause approach to identifying, exploring, and graphically displaying all possible causes of an issue using a standard quality technique." (Danette McGilvray, "Executing Data Quality Projects", 2008)

"A chart that links an outcome to chains of possible contributing factors as tree structure working backwards from an event to determine possible root causes, drawn sideways so that it resembles the skeleton of a fish. Because the chart resembles the skeleton of a fish, it is often called a fishbone diagram." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A chart associated with a technique for identifying factors linked to potential problems, risks, or effects. Factors can include time, machinery, methods, material, energy, measurements, personnel, and environment. Also known as the Ishikawa diagram or fishbone diagram." (Bonnie Biafore & Teresa Stover, "Your Project Management Coach: Best Practices for Managing Projects in the Real World", 2012)

"A decomposition technique that helps trace an undesirable effect back to its root cause." (For Dummies, "PMP Certification All-in-One For Dummies" 2nd Ed., 2013)

"A model used for identifying cause and effect. Also known as a fishbone diagram and named after its creator, Kaoru Ishikawa." (Sally-Anne Pitt, "Internal Audit Quality", 2014)

"Named after Kaoru Ishikawa, a diagram that shows possible causes of effects that you want to study such as excessive bugs, delays, and other failures in the development process." (Rod Stephens, "Beginning Software Engineering", 2015)

"A diagramming technique, also called the Ishikawa diagramming, which teams can use to identify root causes to a problem, the effects of an action, or the action items they could take to meet a goal." (David K Pham, "From Business Strategy to Information Technology Roadmap", 2016)

"A decomposition technique that helps trace an undesirable effect back to its root cause." (Project Management Institute, "The Standard for Organizational Project Management (OPM)", 2018)

📈Graphical Representation: Sparklines (Definitions)

"A sparkline is a small, intense, simple, word-sized graphic with typographic resolution." (Edward R Tufte, "Beautiful Evidence", 2006)

"A sparkline is a mini-image (thumbnail) of graphical data that enables you to put numbers in a temporal context without the need to display full charts." (Brian Clifton, "Advanced Web Metrics with Google Analytics", 2010)

"A sparkline is a very small chart, typically a line chart, that is drawn without labels on either axis. Its purpose is to show the variation in data, typically over time." (Bruce Johnson, "Professional Visual Studio", 2012)

"Sparklines are condensed graphs or charts that can be used in-line with text or grouped to show trends across several different measures." (Ryan Sleeper, "Practical Tableau: 100 Tips, Tutorials, and Strategies from a Tableau Zen Master", 2018)

"A sparkline is a small line chart with the purpose of showing a general trend, without the full details. A sparkline is very efficient in the amount of screen space it uses." (Andrew Berridge &, Michael Phillips, "TIBCO Spotfire: A Comprehensive Primer", 2019)

"A Sparkline is a tiny chart that appears in a cell and does not include any text data. So, a Sparkline is a great way to give a quick glance of a trend." (Eric Butow, "MCA Microsoft Office Specialist: Office 365 and Office 2019", 2021)

"A sparkline chart is a small, simple, and condensed data visualization tool that presents trends and variations in data over a concise space, typically in the form of a tiny line chart." (Phocas)

"A sparkline is a line chart that displays the variation in a null value, unique value, or non-unique value across the latest five consecutive profile runs." (Informatica)

"A sparkline is a tiny chart in a worksheet cell that provides a visual representation of data. Use sparklines to show trends in a series of values, such as seasonal increases or decreases, economic cycles, or to highlight maximum and minimum values. Position a sparkline near its data for greatest impact." (Microsoft)

"A sparkline is a very small line chart, typically drawn without axes or coordinates. It presents the general shape of a variation (typically over time) in some measurement, such as temperature or stock market price, in a simple and highly condensed way." (Wikipedia)

"Sparklines are small, simple line graphs traditionally used for displaying trends or variations of some variable" (TIBCO)

📈Graphical Representation: Mind Map (Definitions)

"A visual note-taking process that pares thoughts to key words and pictures illustrating the relationships among concepts." (Ruth C Clark & Chopeta Lyons, "Graphics for Learning", 2004)

"A mind map consists of a central concept which acts as a headline for the map and the branches that represent the aspects of the main concept. A mind map allows summarizing and decomposition of the key aspects of a complex problem or issue." (Hannu Kivijärvi et al, "A Support System for the Strategic Scenario Process", 2008) 

"A mind map is a diagram uses intuition to depict words, ideas or other items in branches around a central key word or idea." (Wan Ng & Ria Hanewald, "Concept Maps as a Tool for Promoting Online Collaborative Learning in Virtual Teams with Pre-Service Teachers", 2010)

[mind mapping:] "A process that brainstorms ideas, words, tasks or other elements and arranges them in groups around a central notion."  (Wan Ng & Ria Hanewald, "Concept Maps as a Tool for Promoting Online Collaborative Learning in Virtual Teams with Pre-Service Teachers", 2010)

[mind-mapping:] "A technique that uses multiple levels of detail for a texture. This technique selects from among the different sizes of an image available, or possibly combines the two nearest sized matches to produce the final fragments used for texturing." (Graham Sellers et al, "OpenGL SuperBible: Comprehensive Tutorial and Reference" 5th Ed., 2010)

"Refers to a technique for the graphical representation of information items, enabling visualization. A mindmap has a radial structure: it is constructed by starting from a central information item, around which other information items are organized like rays from a star, except that each ray can in turn be subdivided in a plurality of finer rays, and so on. The 'rays' are linear, going from an upstream point to downstream, more secondary points, and so on." (Humbert Lesca & Nicolas Lesca, "Weak Signals for Strategic Intelligence: Anticipation Tool for Managers", 2011)

"Powerful techniques you can utilize to increase your comprehension of written materials." (Jeffrey Magee, "The Managerial Leadership Bible", 2015)

[mind-mapping:] "A technique used to consolidate ideas created through individual brainstorming sessions into a single map to reflect commonality and differences in understanding and to generate new ideas." (Project Management Institute, "A Guide to the Project Management Body of Knowledge (PMBOK Guide)", 2017)

[mind mapping:] "A method to brainstorm thoughts while showing relationships of the parts to the whole." (Errick D Farmer et al, "Digital Course Redesign to Increase Student Engagement and Success", 2019)

"A diagram used to represent words, ideas, tasks, or other items linked to and arranged around a central keyword or idea. Mind maps are  used to generate, visualize, structure, and classify ideas, and as an aid in study, organization, problem solving, decision making, and writing." (Software Quality Assurance)

🔏MS Office: Access vs. LightSwitch - About Starts and Ends of Software Products

Introduction

When an important software product or technology is released on the market, it brings with it dooming prophecies about the end/death of a competing or related product or technology. Even if maybe it catches the attention, the approach became a stereotype leading to other futile fights between adepts, some food for thought and a pile of words for search engines. As LightSwitch was released recently, people started already sketching dooming plans for competing tools like MS Access, Silverlight, WebMatrix, Visual Studio, etc. It’s actually interesting to study and understand how the entry on the software market impacts the overall landscape, the publishing of more or less pertinent thoughts on the future of a product are more than welcome, though from this to forecasting the end of a software product or technology, at least not without well-grounded reasons, it’s a long way.

In many cases it’s not even needed to go too deep into the features of the compared software products in order to dismiss such statements, this because there are a few common sense reasons for which the respective products will coexist, at least for the near future. Here are a few of them grouped into technology, products, people, partners and processes. Please note that by the terms old and new (software) products I’m referring here to a product existing on the market for a longer time, respectively a newly entered product.

Technology

In theory  a new software product attempts to take advantage of the latest technological advances in the field, following the trends. Also an old product can take advantage of the latest technological developments, though a certain backward compatibility needs to be maintained, fact that could come with advantages and disadvantages altogether. Considering that nowadays such a product doesn’t exist “per se” but in a complex infrastructure with multiple layers of interconnectivity, a new product has to fit also in the overall picture.
 

A product in particular and a technology in general is doomed to extinction when it’s not more able to cope with the trends, when its characteristics don’t satisfy anymore users’ demands or the overhead of using it is greater than its benefits. As long two competing software products are trying to keep up with the trends and consolidate their market, the chances that they will parish are quite small. On the other side, each technology has sooner or later its own end.

Products

Software products having a few years on the market have reached in theory a certain maturity and stability. New software products typically go through an adoption phase that may last from months to years, and it will take time until they reach a certain maturity and stability, until their market develops, until vendors include them in their portfolio, until other products will develop interfaces to them, etc. First of all it will take some time until the two will come to have the same market share, and secondly it will take even more time until the market share of one of the products will deprecate. In addition, markets embrace diversity and the demands are so various that each product arrives to find his place.

When the products are coming from the same vendor and they are a part of greater packages and strategies, it’s hard to believe that a vendor would want to blow in the air his own business. Usually the two solutions target different markets, even if their markets intersect. Sure, there are also cases when a vendor might want to strengthen the position of a product in the detriment of another, especially when the benefits are higher.

People

 Often different products demand different skill sets or an upgrade of skill set. For sure not all developers will move from one platform to the other, some will be reticent, while others are declared fans so there is no way to move to something new. Sure, in IT there are frequent the cases when developers have knowledge about 2-3 competing products, though this aspect doesn’t necessarily have a huge impact on the short term. Considering that software products are becoming more and more complex, it’s sometimes even needed a specialization covering only a part of a product.

Partners

Vendors and Customers, especially existing partners, will most probably approach and evaluate the new product, find a place in their portfolio/solution, conduct some pilot projects and eventually consider the product for further use. We can talk here about an adoption period, corroborated with the appearance of training material, best practices, books or any other material that facilitate the use of such a product. All this time requires time and effort, successful and unsuccessful projects, some years of experience.

Processes

Organizations have already in place solutions based on a product and integrated with other products. Some of them could be personal solutions, and maybe quite easy to replace, though the replacement of business/enterprise solutions come maybe with important expenses, changes in the infrastructure, and maybe the most important, process changes. And why change something that’s working just for the sake of change?! Sure, if there is the need for a second or third product, this doesn’t (always) mean that all the previous similar products will be replaced. For sure the two or more products can coexist, even if provide similar functionality, and the can maybe complete each other.

Conclusion

If one product or another will come to its end, for sure only time will tell. Usually when this happens, there are multiple factors that influenced the decay, factors that could be used maybe to foresee such an event. Though, without a detailed analysis or at least some well-supported ideas, dooming declarations about the rise or fall of software products are kind of futile, even if intended to catch readers’ attention. Enthusiastic or contradictory feelings about old or new products are natural, expressing opinions is free and welcomed when there is something to say, though are such declarations really necessary?!

📈Graphical Representation: Histogram (Definitions)

"A graph showing a variable's discrete values or ranges of values on the x-axis and counts or percentages on the y-axis. The number of observations for each value or range is presented as a vertical rectangle whose length is proportionate to the number of observations." (Glenn J Myatt, "Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining", 2006)

"A graphical display of the frequency distribution of a set of data. Histograms display the shape, dispersion, and central tendency of the distribution of a data set." (Clyde M Creveling, "Six Sigma for Technical Processes: An Overview for R Executives, Technical Leaders, and Engineering Managers", 2006)

"A chart that shows quantities of data points that occur within various numeric ranges." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A special form of bar chart used to describe the central tendency, dispersion, and shape of a statistical distribution." (For Dummies, "PMP Certification All-in-One For Dummies, 2nd Ed.", 2013)

[height-balanced histogram:] "A histogram in which column values are divided into buckets so that each bucket contains approximately the same number of rows." (Oracle, "Database SQL Tuning Guide Glossary", 2013)

[top frequency histogram:] "A variation of a frequency histogram that ignores nonpopular values that are statistically insignificant, thus producing a better histogram for highly popular values." (Oracle, "Database SQL Tuning Guide Glossary", 2013)

[hybrid histogram:] "An enhanced height-based histogram that stores the exact frequency of each endpoint in the sample, and ensures that a value is never stored in multiple buckets." (Oracle, "Database SQL Tuning Guide Glossary", 2013)

[frequency histogram:] "A type of histogram in which each distinct column value corresponds to a single bucket. An analogy is sorting coins: all pennies go in bucket 1, all nickels go in bucket 2, and so on." (Oracle, "Database SQL Tuning Guide Glossary", 2013)

"A chart that shows a frequency distribution." (E C Nelson & Stephen L Nelson, "Excel Data Analysis For Dummies ", 2015)

"A bar chart that shows the graphical representation of numerical data." (Project Management Institute, "A Guide to the Project Management Body of Knowledge (PMBOK Guide )", 2017)

💠🛠️SQL Server: Administration [Could not load file or assembly Microsoft.MSXML]

I’m not programming anymore as I used to do, though from time to time I still fancy some .Net programming. It’s not much, small applications or CLR-based libraries for SQL Server. Quite often, when I return to programming after a long pause it happens that I run into problems, finding that something that was working previously stopped working. During my last attempt I couldn’t load anymore one of the projects I worked on, receiving the following error:

“Could not load file or assembly ‘Microsoft.MSXML, Version=8.0.0.0, Culture=neutral, PublicKeyToken=b03f5f7f11d50a3a’ or one of its dependencies. The system cannot find the file specified.”

Same happened when I tried to load other projects. I looked then into GAC in “C:\Windows\assembly” folder and saw no reference to Microsoft.MSXML dll. So I tried to install the msxml6.dll assembly in GAC however, never doing that, I run into another problem. In the meantime I tried to install the Visual Studio 2010 SP1, the MSXML 6.0 and even the Windows .Net SDK. All this without success. After several good hours, I returned to one of the forum posts (here) I run into in a first place. Thomas Sun was pointing that it might be a problem with the Microsoft Document Explorer 20xx. The solution was to reinstall it from  “C:\Program Files\Common Files\microsoft shared\Help 9\Microsoft Document Explorer 2008”. Once I did that everything was back to normal. At least until I’ll run into another issue.

After all this there is still one positive point: I managed to install SP1 and all the goodies it comes with, and I’m thinking here at the support for HMTL5. The downside – several good hours of lost time! I don’t want to think how much time I lost until now trying to solve things that were supposed to work in a first place – probably weeks, months…  That’s part of programmers’ life.

Disclaimer:
As Microsoft changed the whole structure of their support websites, most of the resources become unavailable. Therefore I had to remove the links pointing to the various sources.

💎SQL Reloaded: Pulling the Strings of SQL Server X (Dynamic Queries)

A dynamic query is a query constructed at runtime, techniques often indispensable in many situations that require a certain flexibility in query’s creation. The creation of a dynamic query is nothing but a set of operations with strings, many of the techniques mentioned before becoming handy. SQL Server provides two functions for the execution of dynamic queries, namely EXECUTE statements (or its shortened form EXEC) and sp_executesql stored procedure. Even if the later it’s more flexible allowing passing parameters from and to the caller and allows reusing executions plans (see Using sp_esecutesql), for the following examples will be used only EXEC. But before let’s look how a static could become dynamic. For this let’s consider the following query based on AdventureWorks database:
 

-- example 1 - simple query   
SELECT *  
FROM Person.Address  
WHERE AddressID = 1 

-- example 2 - query encapsulated in a string: 
EXEC ('SELECT * FROM Person.Address WHERE AddressID = 1') 

-- example 3 - query stored into a string variable      
EXEC ('SELECT * FROM Person.Address WHERE AddressID = 1') 

Supposing that the AddressID is considered as parameter we can write:

-- example 4 - static query     
DECLARE @AddressID int 
SET @AddressID = 1 
SELECT *  
FROM Person.Address  
WHERE AddressID = @AddressID  

-- example 5 - dynamic query  
DECLARE @sql varchar(100) 
DECLARE @AddressID int 
SET @AddressID = 1 
SET @sql = 'SELECT * FROM Person.Address WHERE AddressID = ' + CAST(@AddressID as varchar (10)) 
EXEC (@sql) 

Until here there is no important conceptual difference. What if is needed to pass multiple AddressIDs? We can create a parameter for which expected values, though that’s not a reasonable solution as the number of values can vary. A more elegant solution would be to create a list of values and provided as a string parameter and then concatenate the original query and the string parameter like below. We just need to accommodate the length of the string variable to the expected size of the list of value.
 

-- example 6 (dynamic query) 
DECLARE @sql varchar(100) 
DECLARE @AddressIDs varchar(50) -- supposed parameter 
SET @AddressIDs = '1, 2, 4, 5, 6, 10'  
SET @sql = 'SELECT * FROM Person.Address WHERE AddressID IN (' + @AddressIDs + ')' 
EXEC (@sql) 

There is actually a third solution. As in the previous post on list of values has been introduced the dbo.StringToTable function, the function can be used thus to transform the list in a table:
 

-- example 7 (list of values) 
DECLARE @AddressIDs varchar(50) -- supposed parameter 
SET @AddressIDs = '1,2,4,5,6,10'  
SELECT *  
FROM Person.Address  
WHERE AddressID IN ( 
      SELECT value  
      FROM dbo.StringToTable(@AddressIDs, ',')) 

In the same post was constructed the DoubleList list of values which can be used in a dynamic query in bulk inserts or table-value constructors. The list needs to be slightly modified by replacing the single quote with two single quotes in order to accommodate value’s storage in a string. Considering that there are no integrity constraints on the targeted table, he query for bulk insert can be written as follows:
 

-- example 8 (list of values & bulk insert) 
DECLARE @sql varchar(200) 
DECLARE @AddressTypes varchar(150)  
SET @AddressTypes = '(6,''Archive''), (1,''Billing''), (2,''Home''), (3,''Main Office''), (4,''Primary''), (5,''Shipping'')' 
SET @sql = 'INSERT Person.AddressType (AddressTypeID, Name) VALUES ' + @AddressTypes  
EXEC (@sql) 

  The same technique can be used with a table-value constructor:
 

-- example 9 (list of values & table-value constructor) 
DECLARE @sql varchar(400) 
DECLARE @AddressTypes varchar(150)  
SET @AddressTypes = '(6,''Archive''), (1,''Billing''), (2,''Home''), (3,''Main Office''), (4,''Primary''), (5,''Shipping'')' 
SET @sql = 'SELECT VA.AddressID, VA.AddressTypeID, AT.NAME FROM Purchasing.VendorAddress VA JOIN ( VALUES ' + @AddressTypes + ') AS AT(AddressTypeID, Name) ON VA.AddressTypeID = AT.AddressTypeID' 
EXEC (@sql) 

The above examples are basic, in daily problems such queries can involve multiple parameters and operations. In addition, in the last examples the concatenation step was left out.

 

Happy coding!