One of the most important assets of any organization is its information. This asset is almost always used for two purposes: operational record keeping and analytical decision making. Simply speaking, the operational systems are where you put the data in, and the DW/BI system is where you get the data out.
Unfortunately, we still encounter supposed DW/BI systems that are mere copies of the operational systems of record stored on a separate hardware platform. Although these environments may address the need to isolate the operational and analytical environments for performance reasons, they do nothing to address the other inherent differences between the two types of systems.
Fundamental goals of data warehousing and business intelligence:
We collect tons of data, but we can’t access it.
We need to slice and dice the data every which way.
Business people need to get at the data easily.
Just show me what is important.
We spend entire meetings arguing about who has the right numbers rather than making decisions.
We want people to use information to support more fact-based decision making.
Understand the business users:
Understand their job responsibilities, goals, and objectives.
Determine the decisions that the business users want to make with the help of the DW/BI system.
Identify the “best” users who make effective, high-impact decisions.
Find potential new users and make them aware of the DW/BI system’s capabilities.
Deliver high-quality, relevant, and accessible information and analytics to
the business users:
Choose the most robust, actionable data to present in the DW/BI system,carefully selected from the vast universe of possible data sources in your organization.
Make the user interfaces and applications simple and template-driven,explicitly matched to the users’ cognitive processing profiles.
Make sure the data is accurate and can be trusted, labeling it consistently across the enterprise.
Continuously monitor the accuracy of the data and analyses.
Adapt to changing user profiles, requirements, and business priorities,along with the availability of new data sources.
Sustain the DW/BI environment:
Take a portion of the credit for the business decisions made using the DW/BI system, and use these successes to justify staffing and ongoing expenditures.
Update the DW/BI system on a regular basis.
Maintain the business users’ trust.
Keep the business users, executive sponsors, and IT management happy.
Definition of DWH:
The data warehouse is that portion of an overall Architect Data Environment that serves as the single integrated source of data for processing information. The data warehouse has specific characteristics that include the following:
Subject-Oriented: A data warehouse can be used to analyse a particular subject area. For example, "sales" can be a particular subject.
Integrated: A data warehouse integrates data from multiple data sources. For example, source A and source B may have different ways of identifying a product, but in a data warehouse, there will be only a single way of identifying a product.
Non-Volatile: Stable information that doesn’t change each time an operational process is executed.Information is consistent regardless of when the warehouse is accessed.
Time-Variant: Containing a history of the subject, as well as current information. Historical information is an important component of a data warehouse.Accessible: The primary purpose of a data warehouse is to provide readily accessible information to end-users.
Process-Oriented: It is important to view data warehousing as a process for delivery of information.The maintenance of a data warehouse is ongoing and iterative in nature.