Business intelligence (BI) is too important to get wrong. Corporates invested millions in setting up BI systems to deliver the information on which primary - and critical - business decisions can be based.
Yet many systems have failed to realise their potential, partly because until a few years ago, data warehousing was a new technology while the scope of BI had yet to be defined.
"However, the answer to disappointing performance is not to shut down data warehouses and scrap BI projects: too much has been invested in them. The answer is to revitalise the data warehouse and re-engineer the BI project," says Martin Rennhackkamp, data warehousing specialist, author and managing director of specialist data warehousing and BI consultants, Prescient Business Technologies Ltd.
Prescient is a business partner of SAS Institute SA, the local operation of the world's largest privately held software company that provides solutions which enable customers to transform data from all areas of their business into intelligence.
According to Rennhackkamp, 88% of decision-makers report that the information they are given from their data warehouses and BI systems contains erroneous or missing data. In addition, only one third of decision-makers feel they have the right amount of information they need to make important decisions.
"The problem is that in the past, the focus of data warehousing and BI projects was on providing better information to the business. Experience has shown that the focus should rather be on the data warehouse and BI providing value and delivering a measurable return on the corporate investment in the technology," he explains.
Data warehouse revitalisation, he continues, is not a quick fix. It's a process designed to get the BI programme back on track, to correct past mistakes, remove dead wood and, ultimately, deliver the required information to the business.
"It's about moving the data warehouse forward with a focus on business needs rather than on data," he says.
"Most first-generation data warehouses - those which have been in operation for several years and have been at the mercy of various managers, users and developers with different approaches - are often in desperate need of revitalisation.
"Not only are they likely to be a maze of different technologies, but it's an engineering truth that even the best-designed and implemented project will be affected by entropy over time. Entropy is the phenomenon of steady deterioration of a system, no matter how good it was originally, as parts are tinkered with to deliver a newly identified requirements," he adds.
Today, thanks to modern data warehouse design, it is easier to prevent entropy at the outset. Modern data warehouse systems are flexible enough to change with changing business needs, and are also able to scale up to the sizes required with modern data volumes. Older data warehouses, however, have to be 'patched' on an ongoing basis.
Rennhackkamp also believes that it's time to revitalise the data warehouse when it no longer delivers a return on investment or when the business direction has changed since the data warehouse was initially designed.
"In many instances, data warehouses have taken years to build. Now the time has come to move from the building to the usage stage - and that's when corporates are discovering shortcomings in their data warehouse design and implementation.
"The data warehouse must move forward. It must be focused on meeting business needs such as enhancing revenues, reducing operating costs, gaining competitive advantage, increasing market share, improving service and growing the business.
"And the only way to achieve this and ensure that the data warehouse and BI system deliver value, is to assess the needs of the business and evaluate usage of the data warehouse, its organisation and programmes as well as its technical architecture, infrastructure architecture and ultimately, the quality of its data," Rennhackkamp concludes.
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