5 Data Warehouse Design Mistakes to Avoid

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Mistake 4: Not having the right team

In any integration project, it's vital that everyone knows their roles and is able to communicate their pain points effectively. To that end, the primary data warehouse team will build data marts rapidly to achieve high ROI, making use of reusable components such as conformed dimensions, conformed facts and high-level transformation objects.

The team should include ETL engineers, who write processes and load data — ultimately, they are responsible for the quality of the data that enters and leaves the data warehouse. You will also need reports/dashboard engineers who build reports and dashboards, as well as a program manager, and data modelers who build out data models as per best practice. It's also important to have a separate maintenance and enhancement team that responds to user requests for enhancement to completed data marts. Additional team members should include data warehouse administrators, DBAs, source system experts, data stewards, training support personnel and business analysts.

A data warehouse lies at the base of any business intelligence (BI) implementation project. And if you are designing your data warehouse to help you visualize your company's most relevant data (as well as streamline workflows — which can help your company cut down on redundancies significantly), then you need to map out all the areas where there is a potential for your project to fail, before you begin building.

In this article, Himanshu Sareen, CEO at Icreon Tech, has identified five design mistakes that companies should avoid.


Related Topics : APC, Resellers, Data Replication, Extract Transform and Load, Structured Data Integration

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