Why Business Intelligence for Data Warehousing?

by Alena SemeshkoMarch 4, 2008

BI + DW = the right decisions

Business Intelligence (BI) is changing the way businesses work and think. BI implies not only moving data around and producing reporting services, but also keeping pace with the constantly changing and dynamic business requirements.

In the world of Business Intelligence, there’s no place for people who manage by gut. Auch that hurts, huh? But that’s true. People who use their intuition only or a gut feeling to make major decisions in business usually lose to those using BI in support of management decisions.

It’s like with cars: your serviceman knows exactly what that noise under your hood means and what has to be repaired or replaced in your car, while you might only suspect that something’s wrong with the engine or breaks or gearbox and if you were to repair your car, you’d be more likely to break something else than repair what’s broken.

Employing BI strategies and techniques, like, for instance, data warehousing (DW), provides the security and assurance you need to keep your business up and be sure of your decisions. When success depends on how quickly a company responds to rapidly changing market conditions, BI is where you turn for help. It fast-forwards the decision-making processes and provides you with the insight necessary to make the right decisions faster.

With the modern technologies of data integration, warehousing and analysis, you get a single complete view of your organization’s past, present, and potential future with the major problematic areas already figured out for you. All that is left is for this perspective to be put into action.

With Data Warehousing being an indispensible attribute of BI, I’d say it’s also one of the key components in making the company’s decision-making life cycle more efficient and productive.

 

Using Apatar for enterprise DW and BI

Apatar employs a powerful business rules–driven approach to ETL, which separates the business rules from the implementation details. Apatar’s architecture eliminates the need for a standalone ETL server and proprietary engine, and instead leverages the inherent power of your RDBMS engines. This combination provides the greatest productivity for both development and maintenance, as well as performance increase for the execution of data transformation and validation.

Apatar’s difference:

  • Productivity advantage and a short learning curve: the business rules–driven approach is shared throughout Apatar, regardless of data, event, or service orientation of each integration mechanism.
  • Shared, reusable metadata: with a single DataMaps repository, the consistency of the integration processes is guaranteed. The repository also promotes the reusability of business rules for data transformation and data validation across processes.
  • Open-source architecture: Unlike all proprietary data integration software and many open source solutions, Apatar is 100% open source with no proprietary source code.

Enterprise information integration (EII) is another technology that seems to be neglected in the SOA, mashup, and warehousing craze of the day. With the ability to integrate data from multiple data sources that EII tools like Apatar provide, and with the scalability of warehousing apps, you could work wonders.

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