Many organisations today are responding to the widely heralded need for timely, trusted and accurate data to drive their business initiatives; be it operational efficiency, compliance or growth through M&A. Underpinning this drive will invariably be a series of data integration projects to address the specific needs of these initiatives. (more…)
Still fresh in the minds of many today, SARS was probably the largest global epidemic of the decade when it took place between November 2002 and July 2003. According to the statistics of the World Health Organisation, there were altogether 8,086 known infected cases and 774 deaths, during the near year-long battle against this fatal respiratory disease.
The bird flu, or avian influenza, strain H5N1, was even more destructive when approximately 60 per cent of humans known to have been infected with it died. In fact, warnings from the United Nations in 2005 further estimated that a global outbreak of avian influenza can easily claim up to 150 million lives, should it ever take place. (more…)
Last week I wrote about the need to adopt and develop a risk-based management framework within which to execute data migration initiatives. I also looked at how a tools-based approach provided the essential building blocks with which to build such a framework.
This week let’s talk about how such an approach can help substantially address the first of our common pain points; “data discovery is skipped due to time or resource constraints.”
The net effect of this omission is easily and neatly summarized in the “code, load & explode” truism. This is where the migration process is coded to invalid data assumptions about its structure, content or compliance to known business rules; and not the reality. The actual reality is often only encountered at some significant milestone in a project where remediation is often very costly in terms of resource and budget. Both of which can significantly impact the ability to meet anticipated timelines. (more…)
Over the last few months I have had a large number of discussions regarding the best approach for achieving successful data migrations. There have been three concepts that come up most frequently, and they are:
- business or legacy system-orientated
- big bang versus incremental
- staged or non-staged, etc.
These are valid considerations and deserve serious deliberation; however, by focusing directly on the mechanics, many projects, in my experience, miss completely what I believe to be the fundamental goal of any data migration, that of risk management. (more…)
Alice: Would you tell me, please, which way I ought to go from here?
The Cheshire Cat: That depends a good deal on where you want to get to
Alice: I don’t much care where.
The Cheshire Cat: Then it doesn’t much matter which way you go
– Lewis Carroll, Alice’s Adventures in Wonderland
When confronted with the problem of how to address their data quality issues many organisations are faced with a similar dilemma to that which confronted Alice during her travels in Wonderland; “I know that I need to do something, but I don’t know where to start”. Knowing where to start and, equally importantly, the size of the problem as well as where an organisation needs to go are critical factors in ensuring that their data quality journey takes them where they need to be at the price they are prepared to pay.
When planning their “journey” organisations need to address the issue of data quality holistically by considering each of the three DQ pillars in turn; firstly “People”, then “Ideas” and finally “Technology”. Many DQ initiatives have failed as the primary focus has been on delivering a technical solution. However without the right framework in place and operated by the right people this approach will never deliver the results that organisations need. Time and time again within the IT industry it has been proved that the pure application of technology will never solve business issues, as technology in itself will never win the “war”, it is always the right people with the right ideas who use the technology in the right way.