Another brief post this week on an area that we do not focus on very often: data transformation. Data transformation is a relatively mundane yet fundamental data management capability – particularly when dealing with similar data from multiple sources. Three simple examples: System A represents Male and Female and 0 and 1, while System B…
Late last year I attended a Data Management Review webinar discussing the impending BCBS 239 deadline, and the implications for banks in 2016. One of the speakers observed that BCBS 239 is largely designed to bring banks in line with sound data management principles already practiced in other industries such as the pharmaceutical industry, Drug…
Attendees at the recent Big Data and Analytics in Banking agree that the lack of Hadoop skills remains one of the biggest obstacles to the adoption of big data analytics in South Africa. While developing big data and analytics skills is important, companies investigating big data can reduce the impact of the skills shortage by…
Hadoop is a highly scalable, NoSQL database used to perform high speed analytics against large volumes of data. Hadoop works on the principle of schema on read, not schema on write. Any data (structured or unstructured) can be stored in Hadoop with out developing a schema. This cuts the development time scales, reduces risk complexity…
Earlier this month, Forrester Consultant, Boris Evelson ( @bevelson ), commented that business has finally won the battle with IT over who will control Business Intelligence and Analytics. The reason – businesses agree that the customer is the priority – and that BI must support the priorities and needs of customer facing staff. [Tweet This]…
A number of independent experts have commented recently on the need for an enterprise data quality approach that goes beyond trying to fix data as you load it into the data warehouse. A recent announcement by American pharmaceutical giant, Pfizer inc, that it is replacing traditional ETL with a data virtualisation approach is a response…
Many large system implementations are driven due to a perception (fueled by the sales team) that the new system will miraculously address data quality issues (in the existing system) that inhibit business’ ability to function effectively. We have, for example, seen a number of client replacing existing billing systems with large ERP packages. Similarly, a lot of…
