Showing posts with label DSS. Show all posts
Showing posts with label DSS. Show all posts

02 January 2015

📊Business Intelligence: Decision Support System [DSS] (Definitions)

"Interactive computer-based systems intended to help decision makers utilize data and models to identify and solve problems and make decisions." (D J Power, "Decision Support Systems Hyperbook", 2000)

"The original name for data warehousing." (Ralph Kimball & Margy Ross, "The Data Warehouse Toolkit" 2nd Ed., 2002)

"The presentation of data to support management in making decisions." (William A Giovinazzo, "Internet-Enabled Business Intelligence", 2002)

"The automated process to provide facts and information to facilitate decision-making activities. Usually DSS involves the analysis of many units of data in a heuristic fashion." (Margaret Y Chu, "Blissful Data ", 2004)

"A system used to support managerial decisions. Usually DSS involves the analysis of many units of data in a heuristic fashion. As a rule, DSS processing does not involve the update of data." (William H Inmon, "Building the Data Warehouse", 2005)

"Commonly known as DSS databases, these support decisions, generally more management-level and even executive-level decision-type of objectives." (Gavin Powell, "Beginning Database Design", 2006)

"A system used to support managerial decisions. Usually DSS involves the analysis of many units of data in a heuristic fashion. As a rule, DSS processing does not involve the update of data." (William H Inmon & Anthony Nesavich, "Tapping into Unstructured Data", 2007)

"A branch of the broadly defined management information system (MIS). It is an information system that provides answers to problems and that integrates the decision maker into the system as a component. The system utilizes such quantitative techniques as regression and financial planning modeling. DSS software furnishes support to the accountant in the decision - making process." (Jae K Shim & Joel G Siegel, "Budgeting Basics and Beyond", 2008)

"An application that uses data to support managerial decisions through ad hoc query, summarization, drill-down analysis, trend analysis, exception identification and 'what if' scenario modeling." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"An arrangement of computerized tools used to assist managerial decision making within a business." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management" 9th Ed., 2011)

"Computer-based information system that combines models and data to solve semistructured and some unstructured problems with intensive user involvement." (Linda Volonino & Efraim Turban, "Information Technology for Management" 8th Ed., 2011)

"Information processing application used by managers and business professionals to analyze situations, monitor and compare performance data, highlight changes that require their attention, and to identify the more promising solutions. DSSs are one component of the overall MIS content for a business" (Kenneth A Shaw, "Integrated Management of Processes and Information", 2013)

"A DSS is an interactive computer-based system or subsystem intended to help decision makers use communications technologies, data, documents, knowledge, or models to identify and solve problems, complete decision process tasks, and make decisions." (Ciara Heavin & Daniel J Power, "Decision Support, Analytics, and Business Intelligence" 3rd Ed., 2017)

"A computer-based information ­system that supports individual or team decision making. Five primary types: communications-driven, data-driven, document-driven, knowledge­driven, and data-driven DSS." (Daniel J Power & Ciara Heavin, "Data-Based Decision Making and Digital Transformation", 2018)

"A coordinated assemblage of people, devices or other resources that analyzes, typically, business data and presents it so that users can make business decisions more easily." (GEMET - Environmental thesaurus)

"A computer system that provides managers with the tools they need to analyze information they deem relevant for a particular decision or class of decisions. Pearson, "Digital Planet: Tomorrow's Technology and You" 10th Ed.)

"A computer-based system that supports organizational decision making activities. Oftentimes, this type of system is used when data is changing rapidly or is not easy to extrapolate." (Solutions Review)

"A decision support system includes the technologies used for management, operations, and planning in an organization to help users make better decisions by providing data and analytics capabilities." (Qlik) [source]

"A decision support system (DSS) is a computer program application that analyzes business data and presents it so that users can make business decisions more easily. It is an 'informational application' (to distinguish it from an 'operational application' that collects the data in the course of normal business operation)." (Techtarget) [source]

"A decision support system or tool is one specifically designed to allow business end users to perform computer generated analyses of data on their own. This system supports exception reporting, stop light reporting, standard repository, data analysis and rule-based analysis." (Information Management)

"An application primarily used to consolidate, summarize, or transform transaction data to support analytical reporting and trend analysis." (IDW BI)

"Business intelligence, sometimes abbreviated BI, is a broad term that describes the set of processes that business use to analyze the data that they generate through operations and turn it into actionable insights that can drive effective business decision-making." (Sumo Logic) [source]

"Software tools that help with decision support." (Oracle) 

📊Business Intelligence: Business Intelligence [BI] (Definitions)

"Throughout Holland, Flanders, France, and Germany, he maintained a complete and perfect train of business intelligence. The news of the many battles fought was thus received first by him, and the fall of Namur added to his profits, owing to his early receipt of the news." (Richard M Devens, "Cyclopaedia of Commercial and Business Anecdotes", 1865) [first usage of the term] 

"An automatic system is being developed to disseminate information to the various sections of any industrial, scientific or government organization. This intelligence system will utilize data-processing machines for auto-abstracting and auto-encoding of documents and for creating interest profiles for each of the ‘action points’ in an organization. Both incoming and internally generated documents are automatically abstracted, characterized by a word pattern, and sent automatically to appropriate action points. […] All of these techniques are based on statistical procedures which can be performed on present-day data processing machines. Together with proper communication facilities and input-output equipment a comprehensive system may be assembled to accommodate all information problems of an organization. We call this a Business Intelligence System." (Hans P Luhn, "A Business Intelligence System", IBM Journal, 1958)  [first usage of the term in modern context] 

"The communication facility serving the conduct of a business (in the broad sense) may be referred to as an intelligence system. The notion of intelligence is also defined here, in a more general sense, as ‘the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal’." (Hans P Luhn,"A Business Intelligence System", IBM Journal, 1958)

"The process of accessing and analyzing data and using it to make better business decisions. Business intelligence distinguishes the use of data, which may or may not be valuable, with the use of information, which is always of value in business decisions." (Microsoft Corporation, "Microsoft SQL Server 7.0 Data Warehouse Training Kit", 2000)

"A generic term to describe leveraging the organization’s internal and external information assets for making better business decisions." (Ralph Kimball & Margy Ross, "The Data Warehouse Toolkit" 2nd Ed., 2002)

"The processes, technologies, and tools needed to turn data into information, information into knowledge, and knowledge into plans that drive profitable business action. Business intelligence encompasses data warehousing, business analytic tools, and content/knowledge management." (Data Warehousing Institute, 2002)

"Thinking abstractly about an organization, reasoning about the business, organizing large quantities of information about the business in order to define and execute a strategy." (William A Giovinazzo, "Internet-Enabled Business Intelligence", 2002)

"Business intelligence is the set of processes and data structures used to analyze data and information used in strategic decision support. The components of Business Intelligence are the data warehouse, data marts, the DSS interface and the processes to 'get data in' to the data warehouse and to 'get information out'." (Claudia Imhoff et al, "Mastering Data Warehouse Design", 2003)

"The set of products or services used to access and analyze data to turn them into information or knowledge enhancement. It includes decision support and data warehousing." (Margaret Y Chu, "Blissful Data", 2004)

"A category of applications and technologies to guide the analysis and use of detailed business data for improved business decision making. The term is sometimes used synonymously with decision support, though business intelligence is technically much broader." (Jill Dyché & Evan Levy, "Customer Data Integration", 2006)

"An approach to management that allows an organization to define what information is useful and relevant to its corporate decision making. Business intelligence helps decision makers make better decisions faster by converting data into information." (Reed Jacobsen & Stacia Misner, "Microsoft SQL Server 2005 Analysis Services Step by Step", 2006)

"Business Intelligence is defined as getting the right information to the right people at the right time. The term encompasses all the capabilities required to turn data into intelligence that everyone in your organization can trust and use for more effective decision making."(Stefanie V Gerlach et al, "Business Intelligence Competency Centers", 2006)

"The part of information technology that focuses on reporting and analysis currently goes by the name business intelligence (BI)." (Stephen Few, "Information Dashboard Design", 2006)

"Business information and business analyses within the context of key business processes that lead to decisions and actions and which result in improved business performance." (Steve Williams & Nancy Williams, "The Profit Impact of Business Intelligence", 2007)

"The activity of converting data into information." (William H Inmon & Anthony Nesavich, "Tapping into Unstructured Data", 2007)

"Business Intelligence is a method of storing and presenting key enterprise data so that anyone in your company can quickly and easily ask questions of accurate and timely data. Effective BI allows end users to use data to understand why your business got the particular results that it did, to decide on courses of action based on past data, and to accurately forecast future results." (Lynn Langit, "Foundations of SQL Server 2005 Business Intelligence", 2007)

"A generic term to describe leveraging the organization’s internal and external information assets to support improved business decision making. Some commentators use the term business intelligence to refer only to the reporting and analysis of data stored in the data warehouse. Because the industry has not reached agreement, we consistently use the phrase data warehouse/business intelligence (DW/BI) to mean the complete end-to-end system. Though some would argue that you can theoretically deliver BI without a data warehouse, and vice versa, that is ill-advised from our perspective. Linking the two together in the DW/BI acronym further reinforces their dependency." (Ralph Kimball, "The Data Warehouse Lifecycle Toolkit", 2008)

"A method used to analyze and interpret business performance data so that fact-based business decisions can be made. The business data referred to in BI is usually extracted from a variety of domains and databases, and presented in a way to bring about more efficient analysis." (Steven Haines, "The Product Manager's Desk Reference", 2008)

"A somewhat generic term used for computer programs that store, analyze, and broadcast data to users to answer business questions."  (Stuart Mudie et al, "BusinessObjects™ XI Release 2 for Dummies", 2008)

"Business intelligence is a set of methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information used to enable more effective strategic, tactical, and operational insights and decision making." (Boris Evelson, Forrester Research, 2008)

"Skills and technologies used to help organizations make better decisions by better understanding their business, their market, and their customers." (Tony Fisher, "The Data Asset", 2009)

"The collection of one or more reports or analyses, using data from the data warehouse, that provide insight into the performance of a business organization. These reports and analyses are typically interactive to enable further understanding of specific areas of interest. They are used to support business professionals in their decision-making processes." (Laura Reeves, "A Manager's Guide to Data Warehousing", 2009)

"BI combines products, technology, and methods to organize key information that management needs to improve profit and performance. More broadly, we think of BI as business information and business analyses within the context of key business processes that lead to decisions and actions and that result in improved business performance. In particular, BI means leveraging information assets within key business processes to achieve improved business performance." (Nancy Williams & Steve Williams, "The Profit Impact of Business Intelligence", 2010)

"Focuses on the collection of those transactions and forming them into a database structure that facilitates analysis." (Anthony D Giordano, "Data Integration Blueprint and Modeling: Techniques for a Scalable and Sustainable Architecture", 2010)

"Generally used synonymously with the information available in an enterprise for making strategic decisions." (Paulraj Ponniah, "Data Warehousing Fundamentals for IT Professionals", 2010)

"Using computer software systematically, throughout an organization, to get a handle on the mountains of data that flow from modern business. BI turns the raw data into ready-to-use business information that becomes an ongoing part of strategic decision-making." (Ken Withee, "Microsoft Business Intelligence For Dummies", 2010)

"Software that enables users to obtain enterprise-wide information for reporting, analytics, data mining, benchmarking, business performance management, and predictive analytics in order to support business decision making." (Janice M Roehl-Anderson, "IT Best Practices for Financial Managers", 2010)

"This is a term that describes a broad variety of analytical applications used by an enterprise to get intelligent and meaningful insight into how the business performed in the past or is currently performing. This insight is typically used to make decisions, giving a business a competitive advantage. BI covers a broad field such as Data Warehousing, data marts, text analytics, data mining, or business reporting to name just a few." (Martin Oberhofer et al, "The Art of Enterprise Information Architecture", 2010)

"A collection of data analysis methods and techniques used by businesses to improve decision making, forecasting, and operational processes in order to gain a competitive advantage in the marketplace." (John R Talburt, "Entity Resolution and Information Quality", 2011)

"A comprehensive, cohesive, and integrated set of tools and processes used to capture, collect, integrate, store, and analyze data with the purpose of generating and presenting information used to support business decision making." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management" 9th Ed., 2011)

"Category of applications for gathering, storing, analyzing, and providing access to data to help enterprise users make better decisions." (Linda Volonino & Efraim Turban, "Information Technology for Management" 8th Ed., 2011)

"Software products that create integrated systems across an organization or between an organization and its customers and suppliers to improve management of employee teams, customer service, and supply chains. May be used for strategic planning, budgeting, financial consolidation, decision support, and reporting to support diagnostic and interactive controls." (Leslie G Eldenburg & Susan K Wolcott, "Cost Management 2nd Ed", 2011)

[Strategic BI:] The application of BI tools to provide metrics to executives, often in conjunction with some formal method of business performance management, to help determine if a corporation is on target for meeting its goals and objectives. Used to support long-term corporate goals and objectives." (DAMA International, "The DAMA Dictionary of Data Management" 1st Ed., 2010)

"Business intelligence (BI) is a set of techniques that takes business data and creates information from those data so that managers can make decisions. In that way, organizations create business intelligence." (Michael S Gendron, "Business Intelligence Applied", 2012)

"Business intelligence taps information systems to extract and report data in organized ways that are helpful to decision makers." (John R Schermerhorn Jr, "Management" 12th Ed., 2012)

"Computer-based techniques used in identifying, extracting, and analyzing business data. Common functions of BI technologies are reporting, online analytical processing (OLAP), analytics, data and process mining, complex event processing, business performance management, benchmarking, and predictive analytics." (Craig S Mullins, "Database Administration: The Complete Guide to DBA Practices and Procedures" 2nd Ed., 2012)

"A broad classification of information-systems-based technologies that support the identification and presentation of insight. Common historical usage referred primarily to reporting-focused systems, but usage of the term has been broadened by some to include all forms of insight generation (including exploratory data analysis and predictive analytics)." (Evan Stubbs, Delivering Business Analytics: Practical Guidelines for Best Practice, 2013)

"A term often used to describe the range of analysis approaches used to process business data." (Kenneth A Shaw, "Integrated Management of Processes and Information", 2013)

"A broad category of applications and technologies for reporting, analyzing, and providing access to data to help enterprise users make better business decisions. BI applications include the activities of decision support systems, query and reporting, and online analytical processing (OLAP)." (Jim Davis & Aiman Zeid, "Business Transformation", 2014)

"A process for improving the decision-making process through enhanced data analysis." (Owen P. Hall Jr., "Teaching and Using Analytics in Management Education", 2014)

"Business intelligence is a set of theories, methodologies, architectures, and technologies that transform raw data into meaningful and useful information for business purposes."(Keith Holdaway, "Harness Oil and Gas Big Data with Analytics", 2014)

"The ability to collect, integrate, and organize the data in a way which received by the right source, at the right time, and via the right tool. It provides basic insights about the data by regenerating reports, queries, alerts, etc." (Shokoufeh Mirzaei, Defining a Business-Driven Optimization Problem, 2014) 

"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. It may include data summarization, visualization, and data interactions capability. Also known as descriptive analytics and reporting." (Brenda L Dietrich et al, "Analytics Across the Enterprise", 2014)

"A broad category of applications, technologies, and processes for integrated acquisition, interpretation, collation, analysis, and exploitation of data to help business users make better decisions in order to improve business operations, reduce uncertainty and apply past experience to develop an exact understanding of business dynamics." (Mandana Farzaneh et al, "Using Fuzzy Logic for Optimizing Business Intelligence Success in Multiple Investment Combinations", 2015)

"Business Intelligence, the set of tools and structures related to the management and the use of data for operational or analytical (decision-making) purposes." (Fernando Iafrate, "From Big Data to Smart Data", 2015)

"Business intelligence is a broad set of information technology (IT) solutions that includes tools for gathering, analyzing, and reporting information to the users about performance of the organization and its environment." (Anil K. Maheshwari, "Business Intelligence and Data Mining", 2015)

"Raw data derived from manufacturing and other business processes that has been organized and structured into meaningful information on which decisions can be based." (Mike Harwood, "Internet Security: How to Defend Against Attackers on the Web" 2nd Ed., 2015)

"Business intelligence is the process of delivering actionable business decisions from analytical manipulation and presentation of data within the confines of a business environment." (Ahmed Sherif, "Practical Business Intelligence", 2016)

"BI is a popularized, umbrella term that describes a set of concepts and methods used to improve business decision making by using fact-based support systems. The term is sometimes used interchangeably with briefing books and executive information systems. A Business Intelligence system is a data-driven DSS." (Daniel J Power & Ciara Heavin, "Decision Support, Analytics, and Business Intelligence" 3rd Ed., 2017)

"Umbrella term that describe a set of concepts and methods to improve business decision making by using fact-based ­decision support systems. Also, refers to a category of software tools that can be used to extract and analyze data from corporate databases." (Daniel J. Power & Ciara Heavin, "Data-Based Decision Making and Digital Transformation", 2018)

"Business intelligence is getting the right information to the right people at the right time so they can make decisions that ultimately improve performance." (Satyadhyan Chickerur et al, "Forecasting the Demand of Agricultural Crops/Commodity Using Business Intelligence Framework", 2019)

"A technological driven process for analyzing data and presenting information, in such a way that user can take immediate actions and unable decision making." (Neha Garg & Kamlesh Sharma, "Machine Learning in Text Analysis", 2020)

"A set of processes, technologies and tools comprising data warehousing, On-Line Analytical Processing, and information delivery in order to turn data into information and information into knowledge." (Nenad Stefanovic, "Big Data Analytics in Supply Chain Management", 2021)

"A catchall term encompassing a variety of tools, applications and methodologies that enable organizations to collect data from internal systems and external sources. BI can be used to prepare data for analysis, develop and run queries, and create reports, dashboards and visualizations with the end goal of providing results to decision makers and end users." (Insight Software)

"A process for analyzing data and presenting actionable insights to stakeholders in order to help them make more informed business decisions." (Solutions Review)

"A set of methodologies, processes, architectures, and technologies - supported by organizational structures, roles, and responsibilities - that transform raw data into meaningful and useful information used to enable more effective strategic, tactical, and operational insights and decision making that contribute to improving overall enterprise performance." (Forrester)

"Encompasses the technologies, applications and practices used in the collection, integration, analysis, and presentation of business information to support better business decision-making." (Accenture)

"Uses technologies, processes, and applications to analyze mostly internal, structured data and business processes to support decision-making. Common functions are reporting, online analytical processing, analytics, data mining, process mining, complex event processing, benchmarking, text mining, predictive analytics, and prescriptive analytics." (Board International)

"The activity of taking data from source systems and turning it into valuable information for business users." (BI System Builders)

"The applications, infrastructure, tools or processes for analyzing data and presenting information to help company executives, managers and others make more informed business decisions." (KDnuggets)

"Business intelligence (BI) combines business analytics, data mining, data visualization, data tools and infrastructure, and best practices to help organizations to make more data-driven decisions." (Tableau) [source]

"Business Intelligence (BI) encompasses the technologies, applications and practices used in the collection, integration, analysis, and presentation of business information to support better business decision-making." (Accenture)

"Business intelligence (BI) includes the applications, infrastructure, tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance." (Tibco) [source]

"Business intelligence involves using software to analyze data so companies can make informed decisions." (Xplenty) [source]

"Business Intelligence (BI), is a methodology which covers the compiling, analyzing and interpreting of business data in order to make better-informed decisions. BI data tends to be put together through extensive research across a wide range of sources like industry reports, customer feedback, actual usage data of the company’s products, and competitive research." (kloudless)

"Business intelligence is actually an environment in which business users receive data that is reliable, consistent, understandable, easily manipulated and timely. With this data, business users are able to conduct analyses that yield overall understanding of where the business has been, where it is now and where it will be in the near future. Business intelligence serves two main purposes. It monitors the financial and operational health of the organization (reports, alerts, alarms, analysis tools, key performance indicators and dashboards). It also regulates the operation of the organization providing two-way integration with operational systems and information feedback analysis." (Information Management)

"BI is a broad term that encompasses data mining, process analysis, performance benchmarking, and descriptive analytics. BI parses all the data generated by a business and presents easy-to-digest reports, performance measures, and trends driving management decisions. Business intelligence addresses the needs of casual users, including executives, managers, front-line workers, customers and suppliers. It delivers reports, dashboards and scorecards that are tailored to each user’s role and populated with metrics aligned with strategic objectives and goals. This top-down style is powered by a classic data warehousing structure that consolidates enterprise data and enforces information consistency by transforming shared data into a common data model (schema) and BI semantic layer (metadata)." (Teradata) [source]

"Business intelligence is a data-driven process for analyzing and understanding how organizations work and make better decisions based on real insights. Business intelligence, or BI, has become a popular term across industries, but it is a catch-all term that encompasses various processes, tools, and methodologies that let companies capture data, analyze it, and derive better answers to key questions." (Sisense) [source]

"Business intelligence is a software-driven process allowing organizations to analyze raw data from multiple sources, extracting insights that lead to more effective business decisions.  […] While the term 'business intelligence' describes both a methodology and a category of enterprise software, the primary activity in business intelligence is data analysis. Business intelligence tools and applications correlate data about business performance and process it to determine the best course of action for a wide range of business functions." (Informatica) [source]

"Business intelligence (BI) is a technology-driven process for analyzing data and presenting actionable information which helps executives, managers and other corporate end users make informed business decisions. BI encompasses a wide variety of tools, applications and methodologies that enable organizations to collect data from internal systems and external sources, prepare it for analysis, develop and run queries against that data and create reports, dashboards and data visualizations to make the analytical results available to corporate decision-makers, as well as operational workers." (Techtarget) [source]

"Business intelligence (BI) leverages software and services to transform data into actionable insights that inform an organization’s strategic and tactical business decisions. BI tools access and analyze data sets and present analytical findings in reports, summaries, dashboards, graphs, charts and maps to provide users with detailed intelligence about the state of the business." (CIO) [source]

"Business intelligence (BI) is the collection of processes, technologies, skills, and applications used to make informed, data-driven business decisions. BI includes data collection, data aggregation, analysis, and meaningful presentation that facilitates decision-making." (Talend) [source]

"Business intelligence is the process by which enterprises use strategies and technologies for analyzing current and historical data, with the objective of improving strategic decision-making and providing a competitive advantage." (OmiSci) [source]

"[...] business intelligence is the process of collecting business data and turning it into information that is meaningful and actionable towards a strategic goal. Or put even more simply, BI is the effective use of data and information to make sound business decisions." (Logi Analytics) [source]

12 February 2010

🕋Data Warehousing: Operational Data Store (Definitions)

"The operational data store is subject-oriented and contains current, integrated, consistent data that reflects the current state of its subject. Operational data stores are similar to enterprise data warehouses in that they may include data from different systems that has been made consistent. Operational data stores are different from enterprise data warehouses in that they are updated frequently to reflect the current state of the operational systems." (Microsoft Corporation, "Microsoft SQL Server 7.0 Data Warehouse Training Kit", 2000)

"A physical set of tables sitting between the operational systems and the data warehouse or a specially administered hot partition of the data warehouse itself. The main reason for an ODS is to provide immediate reporting of operational results if neither the operational system nor the regular data warehouse can provide satisfactory access. Because an ODS is necessarily an extract of the operational data, it also may play the role of source for the data warehouse." (Ralph Kimball & Margy Ross, "The Data Warehouse Toolkit" 2nd Ed., 2002)

"The operational data store is a subject-oriented, integrated, current, volatile collection of data used to support the operational and tactical decision-making process for the enterprise. It is the central point of data integration for business management, delivering a common view of enterprise data." (Claudia Imhoff et al, "Mastering Data Warehouse Design", 2003)

"A hybrid structure designed to support both operational transaction processing and analytical processing." (William H Inmon, "Building the Data Warehouse", 2005)

"A collection of data from operational systems, most often integrated together, that is used for some operational purpose. The most critical characteristic here is that this is used for some operational function. This operational dependency takes precedence and the ODS should not be considered a central component of the data warehousing environment. An ODS can be a clean, integrated source of data to be pulled into the data warehousing environment." (Laura Reeves, "A Manager's Guide to Data Warehousing", 2009)

"A database designed to integrate data from multiple sources to facilitate operations. This is as opposed to a data warehouse, which integrates data from multiple sources to facilitate reporting and analysis." (David C Hay, "Data Model Patterns: A Metadata Map", 2010)

"A database that is subject-oriented, read-only to end users, current (non-historical), volatile, and integrated; is separate from and derived from one or more systems of record; and supports day-today business operations and real-time decision making." (David Lyle & John G Schmidt, "Lean Integration", 2010)

"A DB system designed to integrate data from multiple sources to allow operational access to the data for operational reporting." (Martin Oberhofer et al, "The Art of Enterprise Information Architecture", 2010)

"Database for transaction processing systems that uses data warehouse concepts to provide clean data." (Linda Volonino & Efraim Turban, "Information Technology for Management" 8th Ed., 2011)

"A database designed to integrate data from multiple sources for additional operations on the data." (Craig S Mullins, "Database Administration", 2012)

"A data store that provides data from the original source in near real time." (Brenda L Dietrich et al, "Analytics Across the Enterprise", 2014)

"ODS is the decision support database that integrated operational data from multiple source systems used to capture operational data and is used primarily for near real time operational reporting and analytics. ODSs are used to measure the operations processes efficiencies. The integration pattern is at the lowest levels of granularity and can happen from near real-time to multiple times in a day." (Saumya Chaki, "Enterprise Information Management in Practice", 2015)

"A data store that integrates data from a range of sources, which is subsequently merged and cleaned to serve as the foundation for enterprise operational reporting. It is an important piece of an Enterprise Data Warehouse (EDW) used for enterprise analytical reporting." (David K Pham, "From Business Strategy to Information Technology Roadmap", 2016)

"An ODS system integrates operational or transactional data from multiple systems to support operational reporting." (John D Kelleher & Brendan Tierney, "Data science", 2018)

"An operational data store (ODS) is an alternative to having operational decision support system (DSS) applications access data directly from the database that supports transaction processing (TP). While both require a significant amount of planning, the ODS tends to focus on the operational requirements of a particular business process (for example, customer service), and on the need to allow updates and propagate those updates back to the source operational system from which the data elements were obtained. The data warehouse, on the other hand, provides an architecture for decision makers to access data to perform strategic analysis, which often involves historical and cross-functional data and the need to support many applications." (Gartner)

22 February 2008

Business Applications: Customer Relationship Management (Definitions)

"Operational and analytic processes that focus on better understanding and servicing customers in order to maximize mutually beneficial relationships with each customer." (Ralph Kimball & Margy Ross, "The Data Warehouse Toolkit" 2nd Ed., 2002)

"a popular DSS application designed to streamline customer and/or corporate relationships." (William H Inmon, "Building the Data Warehouse", 2005)

"A database system containing information on interactions with customers." (Glenn J Myatt, "Making Sense of Data", 2006)

"The infrastructure that enables the delineation of and increase in customer value, and the correct means by which to increase customer value and motivate valuable customers to remain loyal, indeed, to buy again." (Jill Dyché & Evan Levy, Customer Data Integration, 2006)

"The tracking and management of all the organization’s interactions with its customers in order to provide better service, encourage customer loyalty, and increase the organization’s long-term profit per customer." (Steve Williams & Nancy Williams, "The Profit Impact of Business Intelligence", 2007)

"A strategy devoted to the development and management of close relationships between customers and the company. In many cases, CRM is referred to as the automation tool that helps bring about this strategy." (Steven Haines, "The Product Manager's Desk Reference", 2008)

"Software intended to help you run your sales force and customer support." (Judith Hurwitz et al, "Service Oriented Architecture For Dummies" 2nd Ed., 2009)

"The technology and processes used to capture the details of interactions with customers and analyze that data to improve customer interaction, assess customer value, and build value and further loyalty." (Tony Fisher, "The Data Asset", 2009)

"A set of technologies and business processes designed to understand a customer, improve customer experience, and optimize customer-facing business processes across marketing, sales, and servicing channels." (Alex Berson & Lawrence Dubov, "Master Data Management and Data Governance", 2010)

"Refers to the set of procedures and computer applications designed to manage and improve customer service in an enterprise. Data warehousing, with integrated data about each customer, is eminently suitable for CRM." (Paulraj Ponniah, "Data Warehousing Fundamentals for IT Professionals", 2010)

"This is a packaged solution that delivers an end-to-end solution around contacting, understanding, and serving particular customer needs." (Martin Oberhofer et al, "The Art of Enterprise Information Architecture", 2010)

"Establishing relationships with individual customers and then using that information to treat different customers differently. Customer buying profiles and churn analysis are examples of decision support activities that can affect the success of customer relationships. Effective CRM is dependent on high quality master data about individuals and organizations (customer data integration)." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"The entire process of maximizing the value proposition to the customer through all interactions, both online and traditional. Effective CRM advocates one-to-one relationships and participation of customers in related business decisions." (Linda Volonino & Efraim Turban, "Information Technology for Management" 8th Ed., 2011)

"Software designed to help you run your sales force and customer support operations." (Marcia Kaufman et al, "Big Data For Dummies", 2013)

"The management of current and future customer interactions with a business. This can include sales support, warranty and technical support activity, Internet website, marketing, and product advertising." (Kenneth A Shaw, "Integrated Management of Processes and Information", 2013)

"Customer relationship management is a model for managing a company’s interactions with current and future customers. It involves using technology to organize, automate, and synchronize sales, marketing, customer service, and technical support." (Keith Holdaway, "Harness Oil and Gas Big Data with Analytics", 2014)

"System that manages the customer-related data along with their past, present, and future interactions with the organization." (Hamid R Arabnia et al, "Application of Big Data for National Security", 2015)

"A set of tools, techniques, and methodologies for understanding the needs and characteristics of customers in order to better serve them." (Robert M Grant, "Contemporary Strategy Analysis" 10th Ed., 2018)

"CRM is the practice of helping customers manage sales, service, and marketing processes effectively and efficiently so that they can grow their business and provide excellent customer service." (Srini Munagavalasa, "The Salesforce Business Analyst Handbook", 2022)
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About Me

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Koeln, NRW, Germany
IT Professional with more than 24 years experience in IT in the area of full life-cycle of Web/Desktop/Database Applications Development, Software Engineering, Consultancy, Data Management, Data Quality, Data Migrations, Reporting, ERP implementations & support, Team/Project/IT Management, etc.