Data warehouse planning is practiced more as an art than as a science. Art is something that one learns with a gifted skill to pursue the craft and deliver the end product. While science is something that anyone with the correct logical algorithm can apply to create the end product. Consultants step in with their own set of questions and start a psychometric analysis class in the office of a CxO of the company, this is a typical way in which most of the data warehouse planning and assessment starts. The end users or the analysts with the organizations have very little clue of why the questions are being asked and what would they derive from it. If someone from the IT Operations of the enterprise approaches the consulting firm regarding the credibility of the process, consultants would pull out a Data Warehouse Toolkit book and justify their theory, making clients almost perceive that data warehouse planning is an art not a science.
How can data warehouse planning become a science ? If the regular set of processes defined to plan and asses data warehouse engineering are available, and the same processes are built into a tool in the form of a workflow, then it becomes science. Any reasonably experienced data architect / BI analysts can use the tool, understand and fill up the workflow with data points and create an assessment, plan the model and come out with a prototype to evaluate the design of a prospective data warehouse.
In the Microsoft BI world, till date the most easy and popular tool of choice for planning a data warehouse, in my knowledge, has been the data warehouse modeling worksheet available from Kimball's Data Warehouse Toolkit book. This worksheet helps at the requirements gathering and modeling level, but not much at the planning level.
How can data warehouse planning become a science ? If the regular set of processes defined to plan and asses data warehouse engineering are available, and the same processes are built into a tool in the form of a workflow, then it becomes science. Any reasonably experienced data architect / BI analysts can use the tool, understand and fill up the workflow with data points and create an assessment, plan the model and come out with a prototype to evaluate the design of a prospective data warehouse.
In the Microsoft BI world, till date the most easy and popular tool of choice for planning a data warehouse, in my knowledge, has been the data warehouse modeling worksheet available from Kimball's Data Warehouse Toolkit book. This worksheet helps at the requirements gathering and modeling level, but not much at the planning level.
The motivation of this post is a new tool that has hit the BI market, and the name is WhereScape 3D. Presently as of the draft of this post, this tool is available as a free trial beta. I gave a try to this tool, and it seems quite of the modeling flavor. In my personal opinion, the tool is not that self explanatory even for a BI Analyst to start using it in a fast track manner, it would require the analyst to learn the tool for a day or two and then start capturing requirements and planning for the warehouse. The striking features is the documentation part, and its one of the unique tools I have come across till date that help the user in modeling the requirements itself to plan the DW right from source systems to data mart. You can read more about this tool from here and download the same from here.
At this time, I am not sure too much about how effective is the tool, but I am pretty impressed by the value it aims to bring to the table and that is indeed one area that has not been targeted by BI product vendors till date. I am sure this is the start of a new race where vendors would start converting enterprise class DW to science, rather than restricting it as art !!
2 comments:
Hi,
Thanks for taking the time to have a play with WhereScape 3D. As you have said, it is early days in the data warehouse planning market, but we are convinced of its value. Planning is a very wide area, and are working to make WhereScape 3D easier to engage with. The mechanism we are using for this is "use cases" which preconfigure the software for specific usages, and which we are also writing up tutorials for. You will soon see other use cases coming from us such as validate a data model (aimed at answering the questions "Is this generic data model actually going to work for my business/How much effort is it going to be to implement this data model?/What problems will I hit when I start to implement this model.")
After that look out for the linkage between planning and building. If you think the documentation is good, wait until you see how fast you can build something you are proud of when you plan it right.
Michael Whitehead
CEO and Founder, WhereScape Software
Awesome Article Sidharth....
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