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Blog: Krish Krishnan

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Data Warehouse Architecture

Let us look at "ever hot" topic of Data Warehouse Architecture. What I define as the Data Warehouse Architecture, is a different perspective. The data warehouse ecosystem consists of layers of infrastructure ie. hardware, network, databases, storage, filesystems, operating systems, business intelligence tools and visualization layers. This is the first half of the spectrum. The second half of this spectrum is the data architecture, data model, data loading, data aggregation, data visualization, master data, metadata which presents a complete inside out perspective of the data warehouse architecture.

Why do we need to look at this entire ecosystem rather than specific aspects. In my humble opinion, the data warehouse architecture is the backbone of your business intelligence solutions. If this backbone is not designed and built with the appropriate layers and the right sizing, there are other issues downstream which result in complex end solutions.

We as an industry have built data warehouses and datamarts to solve the ever growing need for more information in the enterprise. As we continue to mature and grow in providing solutions, let us look at the holistic picture than the silo that needs a solution. As a part of this channel, I will be covering an entire spectrum of the architecture layers across the data warehouse.

  Posted by kkrishnan on April 3, 2008 5:14 PM |

Comments

Krish, It was nice meeting you at Gartner BI summit last week. If you look at the second part of the eco-system you mention, Let's say the data part, we all know what we must do with the design part of the architecture. simply apply the industry best practices about modelling, loading, etc. And because this is known, and the same for each project, you did not look very surprised when you heard that this is automated and thus available by a tool. That is a real good backbone for valuable BI solutions.

Posted by: Gertjan Vlug | April 8, 2008 6:43 AM

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