Data Warehouses & OLAP

Transcription

1 Riadh Ben Messaoud

2 1. The Big Picture 2. Data Warehouse Philosophy 3. Data Warehouse Concepts 4. Warehousing Applications 5. Warehouse Schema Design 6. Business Intelligence Reporting 7. On-Line Analytical Processing 8. OLAP Applications 9. Data Warehouse Implementation 10. Warehousing Software Data Warehouses & OLAP 2

3 1. The Big Picture 2. Data Warehouse Philosophy 3. Data Warehouse Concepts 4. Warehousing Applications 5. Warehouse Schema Design 6. Business Intelligence Reporting 7. On-Line Analytical Processing 8. OLAP Applications 9. Data Warehouse Implementation 10. Warehousing Software Data Warehouses & OLAP 3

4 Successful implementation of DW technologies creates new possibilities for enterprises Applications that previously were not feasible due to the lack of integrated data are now possible Let s take a look at the different types of enterprises that implement DWs and the types of applications that they have deployed Data Warehouses & OLAP 4

5 THE EARLY ADOPTERS Telecommunication Analyzing network utilization, the calling patterns of their clients, and the profitability of their product offerings Required for formulating, modifying, and offering different subscription packages with special rates and incentives to different customers Data Warehouses & OLAP 5

6 THE EARLY ADOPTERS Banks Interested in managing the bank s asset and liability portfolios, analyzing product and customer profitability Profiling customers and households as a means of identifying target marketing and cross-selling opportunities Data Warehouses & OLAP 6

7 THE EARLY ADOPTERS Retail Interested in sales trends influenced by changing seasons, sales promotions, holidays, and competitor activities With customer discount cards, the retail sector is able to attribute previously anonymous purchases to individual customers Individual buying habits and likes are used as inputs to formulating sales promotions and guiding direct marketing activities Data Warehouses & OLAP 7

8 TYPES OF WAREHOUSING APPLICATIONS Performance trend analysis DW users can produce reports that compare current performance to historical figures Their analysis may highlight trends that reveal a major opportunity or confirm a suspected problem Such performance trend analysis capabilities are crucial to the success of planning activities (e.g., sales forecasting) Data Warehouses & OLAP 8

9 TYPES OF WAREHOUSING APPLICATIONS Cross-selling A DW provides an integrated view of the enterprise s many relationships with its customers By obtaining a clearer picture of customers and the services that they avail themselves of, the enterprise can identify opportunities for cross-selling additional products and services to existing customers Data Warehouses & OLAP 9

10 TYPES OF WAREHOUSING APPLICATIONS Customer profiling and target marketing Enterprise data can be integrated with census and demographic data to analyze and derive customer profiles These profiles consider factors such as age, gender, marital status, income brackets, purchasing history, and number of dependents Estimate how appealing customers will find a particular product Data Warehouses & OLAP 10

11 TYPES OF WAREHOUSING APPLICATIONS Promotions and product bundling The DW allows to analyze customers purchasing histories as an input to promotions and product bundling This is particularly helpful in the retail sector, where related products from different vendors can be bundled together and offered at a more attractive price The success of different promotions can be evaluated through the DW as well Data Warehouses & OLAP 11

12 TYPES OF WAREHOUSING APPLICATIONS Sales tracking and reporting Although enterprises have long been able to track and report on their sales performance, the ready availability of data in the warehouse dramatically simplifies this task Data Warehouses & OLAP 12

13 FINANCIAL ANALYSIS AND MANAGEMENT Risk analysis and management DW allow enterprises to analyze their risk exposure Banks loan departments want to manage their risk exposure to sectors or industries that are not performing well Insurance companies want to identify customer profiles who have consistently proven to be unprofitable and to adjust their pricing and product offerings accordingly Data Warehouses & OLAP 13

14 FINANCIAL ANALYSIS AND MANAGEMENT Profitability analysis If operating costs and revenues are tracked or allocated at a sufficiently detailed level in operational systems, a DW can be used for profitability analysis Users can slice and dice through warehouse data to analyze the enterprise s profitability by customer, agent or salesman, product, time period, geography, organizational unit, etc. Data Warehouses & OLAP 14

15 FINANCIAL ANALYSIS AND MANAGEMENT Exception reporting Through the use of exception reporting or alert systems, enterprise managers are made aware of important or significant events More than 10% drop in sales for the current month current year vs. same month, last year Learn about business situations before they escalate into major problems Data Warehouses & OLAP 15

16 FINANCIAL ANALYSIS AND MANAGEMENT Customer relationship management DW can be used as the basis for managing the enterprise s relationship with its many customers Customers appreciate enterprises that never forget special instructions, preferences, or requests Integrated customer data can serve as the basis for improving and growing the enterprise s relationships with each of its customers Data Warehouses & OLAP 16

17 SPECIALIZED APPLICATIONS OF DW TECHNOLOGY Call Center Integration Call Center applications face the daunting task of integrating data from many disparate sources to form a picture of the customer s relationship with the enterprise DW technologies are the appropriate IT architecture components to support call center applications At regular intervals, the ODS feeds the enterprise DW who can provide decisional information and reports Data Warehouses & OLAP 17

18 SPECIALIZED APPLICATIONS OF DW TECHNOLOGY Credit Bureau Systems Credit bureaus can use DW technologies for integrating negative customer data from many different enterprises Data are integrated, then stored in a repository that can be accessed by authorized users The credit bureau can also use DW technologies to mine and analyze the credit data to produce industry-specific and cross-industry reports (blacklisted customer) Data Warehouses & OLAP 18