Anja Canfield-Budde from EdTech explains why business intelligence implementations can be lengthy and also provides some tips on how to help speed up the process.
Implementations of data warehouse and business intelligence solutions are necessarily complex for a variety of reasons. Unfortunately, that is not well understood by those who haven't implemented them.
The general view of business intelligence (BI) projects tends to be that a new, slick front-end analytical tool can be installed and start producing reports, cubes or dashboards within days or weeks.
What's not understood is that the front-end tool is just the tip of the iceberg. The real work — where the bulk of the effort (and time and cost) is incurred — is in gathering, integrating, organizing, modeling and defining the data to be used by the tool.
From an organizational perspective, BI projects cross many lines. They touch multiple business processes, merge data from separate operational systems potentially housed in disparate geographical locations, and integrate several business concepts.
Key business rules may not be understood or documented; data elements may have multiple, conflicting definitions; and the quality of the data throughout the enterprise must be managed within the BI solution. Given those complexities, a structured approach to designing, developing and deploying a solution is an absolute requirement.
The following steps have resulted in faster, better BI launches at the University of Washington while improving data quality and increasing confidence in the data across the organization.
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Source: EdTech Magazine
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