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How to reduce BI project time to production

If we are to look at the time it takes to bring a successful, complete Business Intelligence solution on the Microsoft platform to production in your environment, what components of building this solution would need to be accounted for in such a project?

Some of the most comprehensive examinations of the lifecycle of BI projects are available in the Kimball Group's Datawarehouse Toolkit books. But in a nutshell, what we mean in such cases is that what really makes a BI project complete and successful is to perform the necessary upfront analysis, interviews with the business stakeholders, build your data warehouse using proven dimensional modeling techniques and to build your schemas based on data models to support your intended BI application solution. Without the solid foundation to support your KPIs, measures, reports, etc. you will not be successful.

The Microsoft BI platform products fully support you to build these solutions: SQL Server (SSIS, SSRS, SSAS), PPS and Proclarity. But if you do not have the in-house staff, time or funds to invest in an end-to-end time & materials project to implement these solutions from scratch, or wish to cut down on your time to production, Microsoft offers pre-built BI solutions called Microsoft Enterprise Cube (MEC) solutions.

MEC solutions allow you to implement the Microsoft BI solution platform based on popular scenarios such as Churn Management, Customer Segmentation and Profitability Analysis with Microsoft Services or Microsoft BI partners. The intent is to provide you with 70% or so of what you need to get started around these scenarios including the database schemas, data models, KPIs, reports and workflow. In this way, you can bring your solution to production in your environment in 16-18 calendar weeks by utlizing the MEC data models and analytics.

This is not to say that your project lifecycle with this approach to BI solutions does not include analysis and modeling. Instead, we look at the efforts involved around extending an existing data model, star schema and cube structure. Since these are based on industry best practices and standards, standing up such a complete scenario takes much less time, effort and risk.

There are no good shortcuts in the BI project lifecycle. But there are methods to solve your business problems with BI scenarios in a much quicker method using a prebuilt solution like that we are speaking of here with MEC.

Happy Thanksgiving and I will report back in December with some further musings around Microsoft BI solutions ... BR, Mark K

 

Published Monday, November 12, 2007 6:45 PM by makrom

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About makrom

* 15 years in information technology and software engineering * Joined Microsoft March 2006 * 3 years creating solutions for Agilent Technologies * 7 years managing architecture for Cingular Wireless * 4 years engineering software for Dun & Bradstreet * Born and raised in PA/NJ area near Philadelphia * Attended Temple U, U of Phoenix and DeSales University * Currenlty in 2nd year of MBA * Moved to Seattle area 2007 * Love baseball, football and technology ... Not necessarily in that order :)

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