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Unit 13: Metadata and Data Warehouse Quality

The Data Warehouse Staging Area is temporary location where data from source systems notes
is copied. A staging area is mainly required in a Data Warehousing Architecture for timing
reasons. In short, all required data must be available before data can be integrated into the Data
Warehouse.
Due to varying business cycles, data processing cycles, hardware and network resource limitations
and geographical factors, it is not feasible to extract all the data from all Operational databases
at exactly the same time.

Example: It might be reasonable to extract sales data on a daily basis, however, daily
extracts might not be suitable for financial data that requires a month-end reconciliation process.
Similarly, it might be feasible to extract “customer” data from a database in Singapore at noon
eastern standard time, but this would not be feasible for “customer” data in a Chicago database.
Data in the Data Warehouse can be either persistent (i.e. remains around for a long period) or
transient (i.e. only remains around temporarily).
Not all business require a Data Warehouse Staging Area. For many businesses it is feasible to use
ETL to copy data directly from operational databases into the Data Warehouse.

Task Discuss metadata and its importance of source system and Data Staging area.

13.2.2 pros and cons of Data staging

The pros and cons of data staging are:
Pros
1. The staging process is handled in parallel with the transformation process.
2. The disk I/O is reduced in half because the staging table is only written to, as opposed to
written to and then extracted from again.
Cons
If the transformation process fails, then the staging process will also stop.

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Case Study at&t

the company
AT&T, a premier voice, video, and data communications company, was gearing up for
the next phase of telecommunications industry deregulation. It recognized that the path to
growth was paved with synergistic products and services, such as credit cards, e-commerce
offerings and integrated customer service. Moreover, it would need to offer a single support
number for all product and service inquiries.
These realizations drove AT&T to regard customers in a new light: not as individual
accounts, but as people who buy a family of products or services. To capitalize on the
opportunities this presented, AT&T needed to centralize its customer data and consistently
identify customers across touch points and accounts. The Integrated Customer View
project, with its customer data warehouse, answered these needs.
Contd...

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