Blog: Krish Krishnan« March 2008 | Main | May 2008 » April 21, 2008Its all about the architectureWhenever one looks at Mt.Rushmore or the Eiffel tower, one admires the architecture and the technical finesse behind these constructions. Similarly when we see a fully functional data warehouse with all the bells and whistles on the input and output side, which provides sustained performance, we call it the perfect balance between hardware and software architectures. When it comes to data warehousing and business intelligence programs, the tools that are needed to implement the pervasive side of the solution is one piece of the giant puzzle. The core of any initiative in this spectrum lies with the architecture. Why do we emphasize on the architecture? in a nutshell, if the architecture blueprint for the data warehouse is not defined and designed correctly, it starts slowing down the multiple layers of data processing leaving the users frustrated and IT baffled. Incorrectly designed systems often lead to program failures and that often gets blamed on poor requirements definition and so on. Hence in the end of the day it is all about the architectures. April 16, 2008Microsoft Unveils its Cloud forayMicrosoft has started its plans to compete in the cloud i.e internet cloud computing. With the announcement of SSDS featuring SQL Server services with storage being offered on pay per use, Microsoft joins amazon and Google in the cloud quest. While there may be differences in all the three offerings from the three vendors, the concept and Web 2.0 behind it as a key driver is powerful. Let us watch the moves as they happen. Yahoo! hope you are listening to all this chatter. April 15, 2008Successful Chargeback ModelsI have been looking at this model of building a data warehouse by organizations where a corporate data warehouse is built and all its users are grouped by divisions or departments and charged for using the data warehouse. This is certainly a good model for the data warehouse team, especially if a corporate It team is owning the data warehouse. But there are a few issues that arise from this model 1. A business case - For every change in this environment a business case is needed. Without a strong business case, no changes are feasible in the data warehouse. Simple changes maybe an easy in, but anything new or complex will need investigations and sponsorship. 2. IT driven and business used - The data warehouse largely becomes IT driven. This may not be a good idea, since the business usage will be not embraced by all users. The business may also try to use workarounds to get the data and the information they need How do you enable a successful chargeback model 1. Organizational Alignment - A key driver, that I have always emphasized on, this is a critical component. 2. Business stakeholders - Involve a business stakeholder in every steering committee and make the business own facets of the problem. This will ensure that even if IT drives the solution, business owns the problem. 3. Roles and Deliverables - A set of clearly defined roles and deliverables will be needed to clarify who owns what components. 4. Defined SLAs - Another key component is the definition of service level agreements on data, availability etc that need to be defined. For a successful chargeback model to be implemented, a few ideas are outlined here, more analysis and customization of the concepts will be needed to make this a possibility in the real world. April 3, 2008Data Warehouse ArchitectureLet 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. |