1. Business Intelligence (BI) : Turning Data into Insight CIST 2100 SP2014

2. BI Defined: A comprehensive and integrated set of tools and processes used to collect, store, and analyze data to be used for fact based, informed, organizational decisions and processes (1). Coronel, C., Morris, S., & Rob, P. (2013)

3. Why Use BI? 1) Data everywhere… and on everything Technological Advances Copious Data Generation 2) Great… there’s data… now what do I do? GET SMARTER! Translate dense troves of data into valuable info Gain insight and use it for competitive advantage Better understand the organization, the customers, the employees, the supply-chain, the distribution channel, and on and on… Coronel, C., Morris, S., & Rob, P. (2013) Chauduri, S., Dayal, U., & Narasayya, V. (2011)

4. What else can BI help us accomplish? Other Objectes of BI Measure Performance –KPI Specific to the organization Set Quantifiable Goals Broaden view beyond the walls of organization focusing on external factors CDW LLC. (2013) Chauduri, S., Dayal, U., & Narasayya, V. (2011)

5. What is secret to BI? And some other stuff… (Organizational Structure and Culture)

6. Where to Get Data Documents: Procedures, Processes, Contracts Transaction Processing Systems Invoices Financial records Internet: e-mail, blogs, reviews, social media Customer Relationship Management (CRM) Supply Chain Management Economic Data Inventory Systems

7. Data Capture, Storage, Retrieval, and Transformation Modern Data Capture and Storage Digital Forms Databases Data warehouses Application Software

8. Databases: The Foundation for BI The Beginning – Why DB Were Created? Problem: Need better way to handle large data sets Solution: Database Idea of Relational DB Ted Codd 1970 Relational Algebra Table Structures Developmental DB work Charles Bachman receives Turing Award 1973 Wilton, P., & Colby, J. (2005).

9. Two Types of Organizational Databases: Operational and BI Both have very different structures and functions The Operational Database - RDBMS Primarily RDBMS Automate daily processes for individual tasks involving data Use transaction processing systems as data sources SQL and app software to store data Coronel, C., Morris, S., & Rob, P. (2013) Hoffer, J. A., Ramesh, V., & Topi, H. (2011)

10. BI Databases are very Different from Operational The Databases of BI Platform Very Large Databases Aggregation data from Operational Database Use of additional data sources, external to organization NoSQL RDBMS and others: Key-value and Column databases May, T.A. (2014, February, 10)

11. Operational Data Vs BI Data Operational Data Highly normalized – data decomposed into many tables Raw data – Reflects individual transactions and processes Low levels of redundancy Minimally distributed Short time span for each data entry BI Data Less normalized – fewer table More redundancies – allows for dimensionality Higher distribution – even cloud based Data is aggregated over larger time span (days, wks, mo, yrs) Coronel, C., Morris, S., & Rob, P. (2013) Olszak, C.M., & Ziemba, E. (2012)

12. Building and Implementing the Correct Platform Key Factors for Transforming Data into Information and Knowledge Designing platforms from the holistic view of the organization Human capital DBAs, Statisticians, Programmers, Business Analysts Ubiquitous information availability and dissemination Maintenance and transformation Yeoh, W., & Koronios, A. (2010) Olszak, C.M., & Ziemba, E. (2012)

13. Summary Foundation of BI is Data Data needs to be meaningful to the organization Data needs to be reformatted from operational data and outside sources Data needs to be stored in specialized large databases Thorough planning and understanding of the organization is a must for successful BI platforms Data needs to be widely available throughout organization to harness its full power Continued investment needed (training and infrastructure) to maintain competitive advantage

14. References 1.Coronel, C., Morris, S., & Rob, P. (2013). Database Systems: Design, Implementation, and Management 10 Ed. Boston, MA: Cengage Learning. 2.Chauduri, S., Dayal, U., & Narasayya, V. (2011). An Overview of Business Intelligence. Communications of the ACM. Volume 54(8), Pages 88-98 3.CDW LLC. (2013). Business Intelligence Shows its Smarts: New platforms and business-user tools are helping to defray the consequences of a less than robust economy. 4.Wilton, P., & Colby, J. (2005). Beginning SQL. Wiley Publishing 5.Hoffer, J. A., Ramesh, V., & Topi, H. (2011). Modern database management. Upper Saddle River, NJ: Pearson Education. 6.May, T.A. (2014, February, 10). The Path to Big Data Mastery. CIO. Retrieved from 7.Olszak, C.M., & Ziemba, E. (2012). Critical Success Factors for Implementing Business Intelligence Systems in Small and Medium Enterprises on the Example of Upper Silesia, Poland. Interdisciplinary Journal of Information, Knowledge, and Management. Volume 7. Pages 128-150. 8.Yeoh, W., & Koronios, A. (2010). Critical success factors for business intelligence systems. Journal of Computer Information Systems. Volume 50(3). Pages 23-32.