Data Marting and BI Development: Part 2

So when we talk about Data Marts and Data Warehouses we're really talking about decision making systems. These software systems provide business decision makers with the data necessary to make well informed decisions.  This may take the form of customer data, performance data, sales data, etc.  All of these things support business decisions and strategies.  The main difference between a mart and a warehouse is that a Data Mart is only concerned with a single subject matter area.  So from my above list, we'd create a Data Mart for sales, another for internal performance indicators, and yet a third for customer data.  All of these marts together would constitute a Data Warehouse.

Now following the previous example and applying it to our current environment here at work, we'll be producing multiple "Data Marts" for each subject area in the company.  I use the quotations to indicate that what we're doing is not traditional Data Marting, but a hybrid approach that will leverage SharePoint as the BI compilation and exposition platform along with Performance Point and SQL Server Reporting Services.  Now what we are doing will differ from a structured Data Mart because all of this data is coming from live systems and is completely dynamic in nature day to day.  Traditionally, Data Mart content is modified in purely a static data context (data modified as data).  But our implementation will be collating data from multiple systems internally and exposing in in a central BI Center.  I suppose you could call it a distributed Data Mart Model.

By leveraging a system like this, our executive team will be able to make decisions based on data that is dynamically gathered in real-time from all the internal business processes we leverage.  Decisions will be made more quickly, costs will be limited because we will be mitigating decisions made with false or outdated data, and our ability to react in the ever-changing world of consultant will greatly increase.

Stay tuned for Part 3 when I start talking about the 2 rules of Data Marts and how they apply in a real world scenario!