Unit 14 business intelligence 1 Introduction to business intelligence 1 What is Business Intelligence (BI) ? ▪ What is Business ▪ What is Intelligent 2 What is Business Intelligence (BI) ? ▪ the process for understanding the past & predicting the future based on the data available and using a broad category of technologies that use for • gather, store, access & analyze data to help business users to make better decisions • analyzing business performance through data-driven insight ▪ broad category of applications, which include the results of • decision support systems • query and reporting • online analytical processing (OLAP) • statistical analysis, forecasting, and data mining 3 BI systems can be ▪ Mission-critical and integral to an enterprise's operations or use occasionally to meet a special requirement ▪ Enterprise-wide or local to one division, department, or project ▪ Centrally initiated or driven by user demand 4 Why We need BI system ▪ to help the knowledge worker (executive, manager, analyst) make faster & better decisions ▪ Organizations need various kinds of information to support decisions and BI systems bring all required information to one location ▪ Decision-making speed is an important success factor in the information economy BI system optimize this process and provides right information to analyze it 5 Operational Databases Transactions Vs Analytical Database Transactions 6 What is Operational Database? Operational systems are generally designed for easy and efficient data storage. Because of that most of operational systems have: ▪ Data storage limited to few terabytes ▪ Optimized for fast data storage ▪ Have good referential integrity ▪ Minimize data duplication 7 Characteristic of Operational Database ▪ High volume of transactions. ▪ Small processing per transaction. ▪ Frequent updating of data. ▪ Data is always current. ▪ Transaction driven. ▪ Predictable query types. ▪ Static structure. ▪ Content varies. ▪ High accuracy. ▪ High availability. 8 What is Analytical Database (Data Warehouse)? ▪ Data store that stored historical data of organization. Specifically designed to support and enhance decision making process 9 Characteristic of Analytical Database (Data Warehouse) ▪ Small volume of transactions. ▪ Often huge processing per transaction. ▪ Data output level is summary. ▪ Data routinely added to the system, but hardly changed. ▪ Analysis driven ▪ Flexible results structure ▪ Fairly accurate' better than no result ▪ Medium availability ▪ Requires different database tools 10 Why We Need Data Warehouse? ▪ Use your knowledge and intelligent to provide answer to the question “why we should not use operational system for decision making”. 11 Why We Need Data Warehouse ▪ Data Warehouses offer the flexibility, that needed to cope with the Management demands. ▪ A major issue is that often there are many different OLTP(operational databases ) systems and other data storage in organization, and The Data Warehouse offers the opportunity to gather these operational databases together into one system with a unified structure. ▪ Because data is stored in a simplified aggregated format it allow reports to be written by staff who have a lesser computing background. ▪ Also analysis queries are consume a lot of resources. For the reason that running analysis queries on operational system will reduce it performance and brining down operational worker performance with it 12 Bibliography ▪ Boyer, J. (2010) Business Intelligence Strategy. MC Press (US). ▪ Marr, B. (2015) Big Data: Using Smart Big Data, Analytics and Metrics to Make Better Decisions and Improve Performance. 1st Ed. John Wiley & Sons, Ltd. ▪ Kaufmann,M. (2011)Data Mining Concepts and Techniques 3rd Ed. Elsevier ▪ Edureka, 2017. Data Warehouse Tutorial For Beginners. [video] Available at: https://www.youtube.com/watch?v=J326LIUrZM8[Accessed 1 May 2020]. ▪ Data Warehousing Module Outline. Sheffield Hallam University 13 Next Week ▪ Complete business intelligent frame work ▪ Operational Data Sources ▪ Extraction, Transformation, and Loading (ETL) Tools ▪ Data Warehouse and Data Marts ▪ Data Presentation ▪ Data , Information ,Knowledge and Intelligent 14