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Prologue to Business Examination

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  1. Introduction to Business Analytics Chapter 3: Business Analytics and Data Visualization Matthew J. Liberatore Thomas Coghlan Fall 2008

  2. Learning Objectives • List and briefly describe the major BA methods and tools • Describe how online analytical processing (OLAP), data visualization, and multidimensionality can improve decision making • Describe geographical information systems (GIS) and their support to decision making

  3. Learning Objectives • Describe real-time BA • Explain how the Web relates to BA • Describe Web intelligence and Web analytics and their importance to organizations • Describe implementation issues related to BA and success factors for BA

  4. Lexmark Improves Operations with BI • Identify the challenges Lexmark faced regarding information flow • How were the information flows provided before and after implementation of the system? • Identify the decisions supported by the new system. • How can the new system improve customer service? • Go to and take the interactive tour of the SAS Retail Intelligence product. Compare it to Oracle Retail (see and Oracle Active Retail Intelligence in particular

  5. The Business Analytics (BA) Field: An Overview • Business Analytics The use of analytical methods, either manually or automatically, to derive relationships from data • Remember that we defined business analytics (BA) to include the access, reporting, and analysis of data supported by software to drive business performance and decision making

  6. The Business Analytics (BA) Field: An Overview

  7. The Business Analytics (BA) Field: An Overview • MicroStrategy’s classification of BA tools: The five styles of BI • Enterprise reporting • Cube analysis • Ad hoc querying and analysis • Statistical analysis and data mining • Report delivery and alerting

  8. The Business Analytics (BA) Field: An Overview

  9. The Business Analytics (BA) Field: An Overview • SAP’s classification of strategic enterprise management • Three levels of support • Operational • Managerial • Strategic

  10. The Business Analytics (BA) Field: An Overview • Executive information and support systems • Executive information systems (EIS) Provides rapid access to timely and relevant information aiding in monitoring an organization’s performance • Executive support systems (ESS) Also provides analysis support, communications, office automation, and intelligence support

  11. The Business Analytics (BA) Field: An Overview • Drill-down The investigation of information in detail (e.g., finding not only total sales but also sales by region, by product, or by salesperson). Finding the detailed sources

  12. Online Analytical Processing (OLAP) • Online analytical processing (OLAP) An information system that enables the user, while at a PC, to query the system, conduct an analysis, and so on. The result is generated in seconds • Some applications can be found at:

  13. Online Analytical Processing (OLAP) • OLAP versus OLTP • OLTP concentrates on processing repetitive transactions in large quantities and conducting simple manipulations • OLAP involves examining many data items complex relationships • OLAP may analyze relationships and look for patterns, trends, and exceptions • OLAP is a direct decision support method

  14. Reports and Queries • Reports • Routine reports • Ad hoc (or on-demand) reports • Multilingual support • Scorecards and dashboards • Report delivery and alerting • Report distribution through any touchpoint • Self-subscription as well as administrator-based distribution • Delivery on-demand, on-schedule, or on-event • Automatic content personalization

  15. Reports and Queries • Ad hoc query A query that cannot be determined prior to the moment the query is issued • Structured Query Language (SQL) A data definition and management language for relational databases. SQL front ends most relational DBMS

  16. Multidimensionality • Multidimensionality The ability to organize, present, and analyze data by several dimensions, such as sales by region, by product, by salesperson, and by time (four dimensions) • Multidimensional presentation • Dimensions • Measures • Time

  17. Multidimensionality • Multidimensional database A database in which the data are organized specifically to support easy and quick multidimensional analysis • Data cube A two-dimensional, three-dimensional, or higher-dimensional object in which each dimension of the data represents a measureof interest

  18. Multidimensionality • Cube A subset of highly interrelated data that is organized to allow users to combine any attributes in a cube (e.g., stores, products, customers, suppliers) with any metrics in the cube (e.g., sales, profit, units, age) to create various two-dimensional views, or slices, that can be displayed on a computer screen

  19. Multidimensionality

  20. Multidimensionality • Multidimensional tools and vendors • Tools with multidimensional capabilities often work in conjunction with database query systems and other OLAP tools • Temtec Executive Viewer

  21. Multidimensionality

  22. Multidimensionality • Limitations of dimensionality • The multidimensional database can take up significantly more computer storage room than a summarized relational database • Multidimensional products cost significantly more than standard relational products • Database loading consumes significant system resources and time, depending on data volume and the number of dimensions • Interfaces and maintenance are more complex in multidimensional databases than in relational databases

  23. Advanced Business Analytics • Data mining and predictive analysis • Data mining • Predictive analysis Use of tools that help determine the probable future outcome for an event or the likelihood of a situation occurring. These tools also identify relationships and patterns • Several data mining tools will be discussed later

  24. Data Visualization • Data visualization A graphical, animation, or video presentation of data and the results of data analysis • The ability to quickly identify important trends in corporate and market data can provide competitive advantage • Check their magnitude of trends by using predictive models that provide significant business advantages in applications that drive content, transactions, or processes

  25. Data Visualization • New directions in data visualization • In the 1990s data visualization has moved into: • Mainstream computing, where it is integrated with decision support tools and applications • Intelligent visualization, which includes data (information) interpretation

  26. Data Visualization

  27. Data Visualization

  28. Data Visualization • New directions in data visualization • Dashboards and scorecards • Visual analysis influence diagrams • Financial data visualization • Tree map examples: • •

  29. Geographic Information Systems (GIS) • Geographical information system (GIS) An information system that uses spatial data, such as digitized maps. A GIS is a combination of text, graphics, icons, and symbols on maps

  30. Geographic Information Systems (GIS) • As GIS tools become increasingly sophisticated and affordable, they help more companies and governments understand: • Precisely where their trucks, workers, and resources are located • Where they need to go to service a customer • The best way to get from here to there

  31. Geographic Information Systems (GIS) • GIS and decision making • GIS applications are used to improve decision making in the public and private sectors including: • Dispatch of emergency vehicles • Transit management • Facility site selection • Drought risk management • Wildlife management • Local governments use GIS applications for used mapping and other decision-making applications

  32. Geographic Information Systems (GIS) • GIS combined with GPS • Global positioning systems (GPS) Wireless devices that use satellites to enable users to detect the position on earth of items (e.g., cars or people) the devices are attached to, with reasonable precision

  33. Geographic Information Systems (GIS) • GIS and the Internet/intranets • Most major GIS software vendors provide Web access that hooks directly to their software • GIS can help the manager of a retail operation determine where to locate retail outlets • Some firms are deploying GIS on the Internet for internal use or for use by their customers (locate the closest store location) •

  34. Real-Time BI • The trend toward BI software producing real-time data updates for real-time analysis and real-time decision making is growing rapidly • Part of this push involves getting the right information to operational and tactical personnel so that they can use new BA tools and up-to-the-minute results to make decisions

  35. Real-Time BI • Concerns about real-time systems • An important issue in real-time computing is that not all data should be updated continuously • when reports are generated in real-time because one person’s results may not match another person’s causing confusion • Real-time data are necessary in many cases for the creation of ADS systems

  36. BA and the Web: Web Intelligence and Web Analytics • Using the Web in BA • Web analytics The application of business analytics activities to Web-based processes, including e-commerce

  37. BA and the Web: Web Intelligence and Web Analytics • Clickstream analysis The analysis of data that occur in the Web environment. • Clickstream data Data that provide a trail of the user’s activities and show the user’s browsing patterns (e.g., which sites are visited, which pages, how long)

  38. BA and the Web: Web Intelligence and Web Analytics

  39. Usage, Benefits, and Success of BA • Usage of BA • Almost all managers and executives can use some BA systems, but some find the tools too complicated to use or they are not trained properly. • Most businesses want a greater percentage of the enterprise to leverage analytics; most of the challenges related to technology adoption involve culture, people, and processes

  40. Usage, Benefits, and Success of BA • Success and usability of BA • Performance management systems (PMS) are BI tools that provide scorecards and other relevant information that decision makers use to determine their level of success in reaching their goals

  41. Usage, Benefits, and Success of BA • Why BI/BA projects fail • Failure to recognize BI projects as cross-organizational business initiatives and to understand that, as such, they differ from typical standalone solutions • Unengaged or weak business sponsors • Unavailable or unwilling business representatives from the functional areas

  42. Usage, Benefits, and Success of BA • Why BI/BA projects fail • Lack of skilled (or available) staff, or suboptimal staff utilization • No software release concept (i.e., no iterative development method) • No work breakdown structure (i.e., no methodology)

  43. Usage, Benefits, and Success of BA • Why BI/BA projects fail • No business analysis or standardization activities • No appreciation of the negative impact of “dirty data” on business profitability • No understanding of the necessity for and the use of metadata • Too much reliance on disparate methods and tools

  44. Usage, Benefits, and Success of BA • System development and the need for integration • Developing an effective BI decision support application can be fairly complex • Integration, whether of applications, data sources, or even development environment, is a major CSF for BI