1. BUSINESS INTELLIGENCE

2. The new technology for understanding the past & predicting the future … BI is broad category of technologies that allows for gathering, storing, accessing & analyzing data to help business users make better decisions analyzing business performance through data-driven insight What is Business Intelligence??

3. BI is broad category of applications, which include the activities of decision support systems query and reporting online analytical processing (OLAP) statistical analysis, forecasting, and data mining. What is Business Intelligence??

4.  BI is the ability for organization to make all it’s capability and convert them into knowledge.  This produces a large amount of information that can lead to the development of new opportunities. What is Business Intelligence??

5.  It provides historical,current and productive view of business operation.  The goal of modern business intelligence is to support better business decision-making, Thus it called decision support system(DSS).

6. What happened? What is happening? Why did it happen? What will happen? What do I want to happen? Past Present Future Why BI? Five questions

7. Customer Inventory Operation External Credit Sales ETL tools Data Warehouse Marketing Data Mart Finance Data Mart Distribution Data Mart BI OLAP Reports Pivot Table

8. Operational Data Source: Business Intelligence system collects data from various sources including operation database, ERP, legacy apps, external database and etc.

9. Customer Inventory Operation External Credit Sales ETL tools Data Warehouse Marketing Data Mart Finance Data Mart Distribution Data Mart BI OLAP Reports Pivot Table

10. ETL tools (Extract, Transform, Load) are used to pull data from source database, transform the data so that it is compatible with the data warehouse and then load it into data warehouse.

11. Customer Inventory Operation External Credit Sales ETL tools Data Warehouse Marketing Data Mart Finance Data Mart Distribution Data Mart BI OLAP Reports Pivot Table

12. A Data Warehouse is a "Subject-Oriented, Integrated, Time- Variant, Nonvolatile collection of data in support of decision making". Data Warehouses tend to have these distinguishing features: (1) Use a subject oriented dimensional data model; (2) Contain publishable data from potentially multiple sources and; (3) Contain integrated reporting tools.

13. Customer Inventory Operation External Credit Sales ETL tools Data Warehouse Marketing Data Mart Finance Data Mart Distribution Data Mart BI OLAP Reports Pivot Table

14. A data mart is a repository of data gathered from operational data and other sources that is designed to serve a particular community of knowledge workers. The data may derive from an enterprise-wide database or data warehouse or be more specialized.

15. The emphasis of a data mart is on meeting the specific demands of a particular group of knowledge users in terms of analysis, content, presentation, and ease-of-use. Users of a data mart can expect to have data presented in terms that are familiar

16. Customer Inventory Operation External Credit Sales ETL tools Data Warehouse Marketing Data Mart Finance Data Mart Distribution Data Mart BI OLAP Reports Pivot Table

17. Literally, On-Line Analytical Processing. Designates a category of applications and technologies that allow the collection, storage, manipulation and reproduction of multidimensional data, with the goal of analysis.

18. Customer Inventory Operation External Credit Sales ETL tools Data Warehouse Marketing Data Mart Finance Data Mart Distribution Data Mart BI OLAP Reports Pivot Table

19. A pivot table is a great reporting tool that allows for “slicing and dicing” data. REPORT: It gives brief report about output

20.  Measurement  Analytic  Reporting Collaboration  Knowledge management

21.  Hotel/restaurant chain.  Food chain.  Retail stores chain.  Big industries.

22.  STRATEGIC 1.Continuous improvement of design making capabilities used to increase revenue & reduce cost 2.Better tools for knowledge worker 3.Leverage the amount of captured transactions & operation data

23. TACTICAL 1.Multidimensional analysis 2.Ad-hoc status reporting & what-if scenarios 3.Intuitive user interface

24. FUNCTIONAL SALES 1.Customer behavior 2.Sales force analysis MARKETING 1.Market & customer penetration 2.Product & service life cycle analysis FINANCE 1.Budgeting & planning 2.Business performance

25. HR IT 1.Customer click stream information 2.Integration of traditional business & e-business 1.HR performance evaluation 2.Compression analysis 3.Workforce planning & optimization FUNCTIONAL

26. Cost Pilling of historical data Complexity Limited use