Accurate, available data is the cornerstone to an effective BI or other data project. Insource can help you achieve it. In our ‘Secrets’ series of blog posts, we look at some of the key factors you need to focus on to ensure best practice for your data management.
In our last blog, we explored the idea of Data Warehouse Automation, and how it can help your business build an effective Data Warehouse in less time, with less hassle. However, this is only a useful advantage if your source data is reliable and accurate in the first place. You need a way to guarantee this happens, so you’re not wasting your time or doubting your data.
The process of ensuring this is known as 'Data Preparation'. It’s the process of taking your raw source data; cleansing and enriching it and producing a reliable dataset against which all data initiatives can then be reliably based. So the process underpins all of your data projects not just data warehousing and BI. Though in fairness most implementations start out with the need for Business Intelligence and develop from there.
Use Automated Data Preparation to build your data preparation process
Implementing a separate data preparation process from the business of producing output through, for example data warehousing, enables more clearly focussed development. This focus helps to ensure success.
But it’s not easy. If built correctly, a data preparation process should not only support the current data needs of the business it should also be able to absorb new data sources as they become necessary for inclusion, and this should be possible without major re-engineering. On top of this, in the event that any of the source operational applications change, the data preparation process should assist and ease the migration from one application to another providing business continuity across the migration boundary.
This makes architectural design and development an extremely tough challenge. New technologies in the form of “Automated Data Preparation” assist in streamlining and automating the development process. They simplify the production process through automation techniques and contribute to a successful outcome, despite what the statistics say!