🪙Business Intelligence: Data Visualization (Definitions)

"Technique for presentation and analysis of data through visual objects, such as graphs, charts, images, and specialized tabular formats." (Paulraj Ponniah, "Data Warehousing Fundamentals", 2001)

"Technique for presentation and analysis of data through visual objects, such as graphs, charts, images, and specialized tabular formats." (Paulraj Ponniah, "Data Warehousing Fundamentals for IT Professionals", 2010) 

"Visual representation of data, aiming to convey as much information as possible through visual processes." (Alfredo Vellido & Iván Olie, "Clustering and Visualization of Multivariate Time Series", 2010)

"Techniques for graphical representation of trends, patterns and other information." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"Information abstracted in a schematic form to provide visual insights into sets of data. Data visualization enables us to go from the abstract numbers in a computer program (ones and zeros) to visual interpretation of data. Text visualization means converting textual information into graphic representation, so we can see information without having to read the data, as tables, histograms, pie or bar charts, or Cartesian coordinates." (Anna Ursyn, "Visualization as Communication with Graphic Representation", 2015)

"[...] data visualization [is] a tool that, by applying perceptual mechanisms to the visual representation of abstract quantitative data, facilitates the search for relevant shapes, order, or exceptions." (Jorge Camões, "Data at Work: Best practices for creating effective charts and information graphics in Microsoft Excel", 2016)

"Presenting data and summary information using graphics, animation, and three-dimensional displays. Tools for visually displaying information and relationships often using dynamic and interactive graphics." (Daniel J Power & Ciara Heavin, "Decision Support, Analytics, and Business Intelligence" 3rd Ed., 2017)

"Data Visualization is a way of representing the data collected in the form of figures and diagrams like tables, charts, graphs in order to make the data for common man more easily understandable." (Kirti R Bhatele, "Data Analysis on Global Stratification", 2020)

"Techniques for turning data into information by using the high capacity of the human brain to visually recognize patterns and trends. There are many specialized techniques designed to make particular kinds of visualization easy." (Information Management)

"The art of communicating meaningful data visually. This can involve infographics, traditional plots, or even full data dashboards." (KDnuggets)

"The practice of structuring and arranging data within a visual context to help users understand it. Patterns and trends that might be unrecognizable to the layman in text-based data can be easily viewed and digested by end users with the help of data visualization software." (Insight Software)

"Data visualization enables people to easily uncover actionable insights by presenting information and data in graphical, and often interactive graphs, charts, and maps." (Qlik) [source]

"Data visualization is the graphical representation of data to help people understand context and significance. Interactive data visualization enables companies to drill down to explore details, identify patterns and outliers, and change which data is processed and/or excluded." (Tibco) [source]

"Data visualization is the practice of translating information into a visual context, such as a map or graph, to make data easier for the human brain to understand and pull insights from." (Techtarget) [source]

"Data visualization is the process of graphically illustrating data sets to discover hidden patterns, trends, and relationships in order to develop key insights. Data visualization uses data points as a basis for the creation of graphs, charts, plots, and other images." (Talend) [source]

"Data visualization is the use of graphics to represent data. The purpose of these graphics is to quickly and concisely communicate the most important insights produced by data analytics." (Xplenty) [source]

📊Business Intelligence: Report Model (Definitions)

"A semantic description of business entities and their relationships in a SQL Server Reporting Services solution. Used to create ad hoc reports through the Report Builder application." (Marilyn Miller-White et al, "MCITP Administrator: Microsoft® SQL Server™ 2005 Optimization and Maintenance 70-444", 2007)

"A 'blueprint' of a report. A report model includes the data source (such as a SQL Server database) and a data view (the tables and/or views that can be used in the report). Users can then use the report model to create their own reports, picking and choosing what data they want to include from the data view." (Robert D. Schneider and Darril Gibson, "Microsoft SQL Server 2008 All-In-One Desk Reference For Dummies", 2008)

"Report models are templates used to create reports with Report Builder. They include the data source definitions (such as which server and which database to connect to for the model) and data source VIEW definitions (such as which tables or VIEWs to include in the model). Reports can't be viewed from a report model. Instead, the report model must be used to create a report using Report Builder." (Darril Gibson, "MCITP SQL Server 2005 Database Developer All-in-One Exam Guide", 2008)

"A metadata description of business data used for creating ad hoc reports in Report Builder." (Jim Joseph, "Microsoft SQL Server 2008 Reporting Services Unleashed", 2009)

"A metadata description of business data used for creating ad hoc reports." (Microsoft, "SQL Server 2012 Glossary", 2012)

 "A metadata description of business data used for creating ad hoc reports in Report Builder." (Microsoft Technet)

📊Business Intelligence: Dashboards (Definitions)

"A dashboard is a visual display of the most important information needed to achieve one or more objectives; consolidated and arranged on a single screen so the information can be monitored at a glance." (Stephen Few, "Dashboard Confusion", Intelligent Enterprise, 2004)

Dashboard reports: "Highly summarized, often graphical, representations of the state of the business that are often used by executives and strategic decision makers." (Reed Jacobsen & Stacia Misner, "Microsoft SQL Server 2005 Analysis Services Step by Step", 2006)

Dashboard: "A means of providing information in a straightforward way. Like the part in a car it is named after, a business dashboard allows executives to see key metrics about anything from monthly sales to manufacturing downtime." (Tony Fisher, "The Data Asset", 2009)

Dashboard (also called performance dashboard): "The presentation of key business measurements on a single interface designed for quick interpretation, often using graphics. The most effective dashboards are supported by a full data mart that enables drilling down into more detailed data to better understand the indicators." (Laura Reeves, "A Manager's Guide to Data Warehousing", 2009)

Dashboard: "A visual display mechanism to enable business users at every level to receive the information they need to make better decisions that improve business performance." (Paulraj Ponniah, "Data Warehousing Fundamentals for IT Professionals", 2010)

Dashboard: "A BI tool that provides a comprehensive, at-a-glance view of corporate performance with graphical presentations, resembling a dashboard of a car. These graphical presentations show performance measures, trends, and exceptions, and integrate information from multiple business areas." (Linda Volonino & Efraim Turban, "Information Technology for Management" 8th Ed., 2011)

Dashboard: "A technique to represent vast amounts of decision-support information at an amalgamated level using tabular and graphic representation, such as graphs and traffic lights." (Paul C Dinsmore et al, "Enterprise Project Governance", 2012)

Dashboards: "Business intelligence tools that display performance indicators, present data and information at both summary and detailed levels, and assist decision-makers employing them to act on the information they present." (Joan C Dessinger, "Fundamentals of Performance Improvement" 3rd Ed., 2012)

Dashboard: "A view that displays ranges of data in a graphical format. Key performance indicators (KPIs) or any element can be displayed in a dashboard. Each element is represented by a gauge that displays the data ranges that are defined. Links to comments, trend data, and element properties can also be provided." (Jim Davis & Aiman Zeid, "Business Transformation", 2014)

"[...] dashboards indicate the status of a performance metric at a given point in time. [...] dashboards are used to represent actual granular data, they contain data that is more recent than that of scorecards." (Saumya Chaki, "Enterprise Information Management in Practice", 2015)

Data dashboard: "A management-level online report capturing data conditions and trends."(Gregory Lampshire, "The Data and Analytics Playbook", 2016)

"A dashboard is a visual display of data used to monitor conditions and/or facilitate understanding."

(Steve Wexler et al, "The Big Book of Dashboards: Visualizing Your Data Using Real-World Business Scenarios", 2017)

"A dashboard is a reporting tool that consolidates, aggregates and arranges measurements, metrics (measurements compared to a goal) and sometimes scorecards on a single screen so information can be monitored at a glance. Dashboards differ from scorecards in being tailored to monitor a specific role or generate metrics reflecting a particular point of view; typically they do not conform to a specific management methodology." (Information Management) [also (Intrafocus)] 

"Dashboards are a reporting mechanism that aggregate and display metrics and key performance indicators (KPIs), enabling them to be examined at a glance by all manner of users before further exploration via additional business analytics (BA) tools." (Gartner)

See also the quotes on" dasboards". 

📊Business Intelligence: Trend Analysis (Definitions)

"The process of looking at homogeneous data over a duration of time to find recurring and predictable behavior." (Sharon Allen & Evan Terry, "Beginning Relational Data Modeling" 2nd Ed., 2005)

"the process of looking at homogeneous data over a spectrum of time." (William H Inmon, "Building the Data Warehouse", 2005)

"An analytical technique that uses mathematical models to forecast future outcomes based on historical results. It is a method of determining the variance from a baseline of a budget, cost, schedule, or scope parameter by using prior progress reporting periods' data and projecting how much that parameter's variance from baseline might be at some future point in the project if no changes are made in executing the project." (Cynthia Stackpole, "PMP® Certification All-in-One For Dummies®", 2011)

[trending] "A process by which underlying trends are identified within time-related data. These trends may be manually, algorithmically, or statistically identified and may be extrapolated into the future to aid planning." (Evan Stubbs, "Delivering Business Analytics: Practical Guidelines for Best Practice", 2013)

"A form of statistical analysis used to analyze activities over a period of time." (Sally-Anne Pitt, "Internal Audit Quality", 2014)

"Using tools and statistics to identify consistent movement in one direction or another. The analysis might show a consistent upward trend or a consistent downward trend, but either way it indicates a change worth investigating." (Darril Gibson, "Effective Help Desk Specialist Skills", 2014)

"A data analysis technique that examines project performance over time to determine if performance is improving or deteriorating." (Cate McCoy & James L Haner, "CAPM Certified Associate in Project Management Practice Exams", 2018)

"An analytical technique that uses mathematical models to forecast future outcomes based on historical results." (Project Management Institute, "The Standard for Organizational Project Management (OPM)", 2018)

 "analysis of data to identify time-related patters" (ITIL)

📊Business Intelligence: Indicator (Definitions)

"An indicator is an objective feature or attribute supporting the implementation of a process. Indicators are used for the rating of process attributes. The indicators of the process dimension are base practices and work products; the indicators of the capability dimension are generic practices and generic resources." (Lars Dittmann et al, "Automotive SPICE in Practice", 2008)

"1.An attribute type that is considered to be binary: On or Off, True or False, Yes or No." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A metric that you can use to predict the project’s future. For example, if the metric 'comments per KLOC' is 3, that may be an indicator that the project will be hard to maintain." (Rod Stephens, "Beginning Software Engineering", 2015)

"A measure that can be used to estimate or predict another measure." (ISO 14598)

📊Business Intelligence: Descriptive Analytics (Definitions)

"The practice of reporting what has happened, analyzing contributing data to determine why it happened, and monitoring new data to determine what is happening now. Also known as reporting and business intelligence." (Brenda L Dietrich et al, "Analytics Across the Enterprise", 2014)

"If you are using charts and graphs or time series plots to study the demand or the sales patterns, or the trend for the stock market you are using descriptive analytics. Also, calculating statistics from the data such as, the mean, variance, median, or percentiles are all examples of descriptive analytics." (Amar Sahay, "Business Analytics" Vol. I, 2018)

"The simplest form of data analytics, in which historical data is collated and summarized in a user-friendly format, providing an understanding of what has previously happened." (Board International)

"Descriptive analytics is a form of data analytics that looks at data statistically to tell you what happened in the past. It helps a business understand how it is performing by providing context that will aid stakeholders in interpreting information." (Logi Analytics) [source]

"Descriptive analytics is a preliminary stage of data processing that creates a summary of historical data to yield useful information and possibly prepare the data for further analysis." (Techtarget) [source]

📊Business Intelligence: Delta Lake (Definitions)

"Delta Lake, an open source ACID table storage layer over cloud object stores initially developed at Databricks." (Michael Armbrust et al, "Delta Lake: High-Performance ACID Table Storage over Cloud Object Stores", Proceedings of the VLDB Endowment 13(12), 2020) [link]

"Delta Lake is a transactional storage software layer that runs on top of an existing data lake and adds RDW-like features that improve the lake’s reliability, security, and performance. Delta Lake itself is not storage." (James Serra, "Deciphering Data Architectures", 2024)

"A Delta Lake is an open-source storage layer designed to run on top of an existing data lake and improve its reliability, security, and performance." (Hewlett Packard Enterprise) [source]

"Delta Lake is an open source storage framework that enables building a Lakehouse architecture with various compute engines." (Apache Druid) [source] 

"Delta Lake is an open-source storage framework designed to improve performance and provide transactional guarantees to data lake tables." (lakeFS) [source] 

"Delta Lake is an open-source storage framework that enables building a format agnostic Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, Hive, Snowflake, Google BigQuery, Athena, Redshift, Databricks, Azure Fabric and APIs for Scala, Java, Rust, and Python." (Delta) [source]

"Delta Lake is an open-source storage layer that uses the ACID compliance of transactional databases to bring reliability, performance, and flexibility to data lakes. It is ideal for scenarios where you need transactional capabilities and schema enforcement within your data lake." (Qlik) [source] 

"Delta Lake is an open-source storage layer for big data workloads. It provides ACID transactions for batch/streaming data pipelines reading and writing data concurrently."  (Database of Databases) [source] 

"Delta Lake is the optimized storage layer that provides the foundation for tables in a lakehouse on Databricks. Delta Lake is open source software that extends Parquet data files with a file-based transaction log for ACID transactions and scalable metadata handling." (Databricks) [source]

"Delta Lake is the optimized storage layer that provides the foundation for tables in a lakehouse on Databricks. Delta Lake is open source software that extends Parquet data files with a file-based transaction log for ACID transactions and scalable metadata handling. Delta Lake is fully compatible with Apache Spark APIs, and was developed for tight integration with Structured Streaming, allowing you to easily use a single copy of data for both batch and streaming operations and providing incremental processing at scale." (Microsoft) [source]