Tag Archives: Data Warehousing
In my last blog, we discussed the ever changing face of data warehousing. As the data warehouse evolves, so does the decision support system that is built on the platform of the data warehouse. We are moving from historical and analytical decision support to event driven decision support.
What this means is, instead of observing patterns and trends from historical data and then influencing changes in your business workflow, you will introduce data as events occur in your operational systems into the data warehouse, and take instant measurements and provide the results for analysis and decision support.
Event driven data integration will require significant data architecture and data mapping efforts from operational systems to the data warehouse. There are multiple ways to implement this with ETL/ELT/CDC types of technologies. But do not forget that you will need to pay attention to data quality, metadata and master data management in addition to all the other details. Last but not least; you will need to remember that all of this needs to happen with extreme agility. (more…)
Technology vendors like to talk about platforms, because platforms imply a broader footprint both in terms of functional capabilities and in terms of implementation usage. Platforms also sound more “strategic,” even if the practical implications are vague. But the term “platform” can also be simple marketing hype. How do you know when a software “platform” is really a platform? More specifically, do data integration platforms exist now?