Jan 28 2016
It is expected that most readers of this article, who are either IT-industry professionals or IT- technology users, are somewhat familiar with a data warehouse although they may not fully understand its role in data integration services or business intelligence. This article attempts to clear the doubts or misconceptions of those readers who are still unsure about implementing a data warehouse in their existing BI environment.
In an increasingly volatile business climate, the competitive advantage that one business has over its competitors comes from their timely decision-making capabilities about mission critical issues. But, the best business decisions can only be made when all the data, highly relevant to a particular decision or action, are readily available to the decision maker. These data may be located on widely distributed data silos across an enterprise, and quick data retrieval during a real-time decision making process is just not possible!
However, a data warehouse offers a solution to fast data retrieval from a common data repository, which may be a dedicated server containing multi-functional data in subject-specific “data marts.” The concept of data warehousing rests on the theory that distributed cross-functional business data can be periodically extracted from enterprise-wide operational processes and applications and copied to the dedicated data warehouse. Once the data has been collected in the data warehouse, it can be cleaned, formatted, organized, validated, summarized, reformatted, reorganized, and reconstructed with data from other sources. The final data deposits that rest on the data warehouse now becomes a great source of information for further analysis, insights, reports, and action-loaded dashboards.
Many experts have questioned the need for a data warehouse as it involves an expendable budget for reserving powerful computers for a data warehouse. The realized business benefits, however, more than justify the cost and efforts involved in building a data warehouse. The main features of a typical data warehouse are:
Although the early adopters of data warehouses found the technology expensive, time exhaustive and resource intensive, gradually the “risky image” of the data warehouse has evolved into a “solution enabler image.”
In an increasingly volatile business climate, the need for doing more with less and making better decisions than competitors is acute. Data warehouse technology enables direct access to actionable information, which makes a big difference to executive decision makers in time of crisis. That is why investing in a data warehouse even during economic downturns makes sense to every business.
Data warehouses aid business intelligence activities: The BI tools can directly access the enterprise-wide operational data in a single location and conduct fast data analysis and present reports that are easy to comprehend. In other words, data warehouses promote decision-ready information. You can find out more about data warehouses in enterprise business intelligence services here.
Data warehouses aid data integration activities: When businesses need toconsolidate cross-functional business data, reports, charts, or pre-built dashboards, a data warehouse is the only solution enabler for data integration service providers.
Business intelligence is the science and art of transforming information into insights, and insights into action. The entire job of behind-the-scene knowledge management in a front-end BI system is done by a data warehouse. The BI solution vendors may frequently underplay the role of a data warehouse for obvious reasons, but the huge user community understands the critical importance of this behind-the scene driver of business intelligence solutions. Read advanced data analytics to understand how data-management service providers use data warehouses to deliver custom BI solutions to clients with different needs.
Here is a quick recap of the earned business benefits of a data warehouse to the BI end user:
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