Data Warehouse Expansion

Data Warehouse Expansion

Although earlier data warehouses concentrated on keeping summary data for high-level analysis. we now see larger and larger data warehouses being built by different businesses Now companies have the ability lo capture, cleanse, maintain, and use the vast amounts of data generated by their business transactions. The quantities or data kept in the data ware- houses continue to swell to the terabyte range. Data warehouses storing several terabytes of data are not uncommon in retail and telecommunications. 

Figure 3-1 Industries using data warehousing. 

For example, take the telecommunications industry. A telecommunications company generates hundreds of millions of call-detail transactions in a year. For promoting the proper products and services, the company needs to analyze these detailed transactions. The data warehouse for the company has to store data at the lowest level of detail.

Similarly, consider a retail chain with hundreds of stores. Every day, each store gener-ates many thousands of point-of-sale transactions. Again, another example is a company in the pharmaceutical industry that processes thousands of tests and measurements for getting product approvals from the government. Data warehouses in these industries tend to be very large.

Finally, let us look at the potential size of a typical Medicaid Fraud Control Unit of a large state. This organization is exclusively responsible for investigating and prosecuting health care fraud arising out of billions of dollars spent on Medicaid in that state. The unit also has to prosecute cases of patient abuse in nursing homes and monitor fraudulent 'billing practices by physicians, pharmacists, and other health care providers and vendors. Usually there are several regional offices. A fraud scheme detected in one region must be against all other regions. Can you imagine the size of data warehouse needed to supports such a fraud control unit? There could be many terabytes of data.