The nature of BI is set to change
Instead of building business applications focusing on process automation, intelligence will in future be increasingly built directly into business processes such as approving loans, extending credit, or routing vehicles.
This is the view of Stanley Chew, MD of Oracle Singapore, who according to a Computer World report believes there will be a shift to industry-specific solutions built on leading BI platforms and data models adhering to industry standards.
Chew predicts that in future, key performance indicators and commonly needed reports will be pre-packaged as solutions leveraging on a platform that can be modified to take account of a specific business requirement. Further, predictive analytics, which will enable the simplification and automation of data mining, is the future of BI, Chew believes.
BI gets entertaining
In the film, television and music sectors of the entertainment industry the pace of technological change continues to be rapid and using BI can mean the difference between staying relevant or becoming obsolete, reports the B-eye-network
According to the report, rapid technological change has made entertainment more portable and accessible than ever, with the result that formerly successful business models are becoming less profitable and even obsolete.
However, the report says technology is also making it possible for producers and retailers to target more specific market segments, with BI becoming increasingly important.
Data integration still a challenge
Data integration remains a major challenge for corporations, according to a recent report by The Data Warehousing Institute (TDWI).
A Wall Street & Technology report says the study, which surveyed 672 IT and business users across multiple industries, reports that nearly 70% of respondents identified data integration as a high inhibitor of new-application implementation.
The report says data integration can be a significant barrier to success, with the top three integration issues facing corporations being data quality and security; lack of a business case and inadequate funding; and poor data integration infrastructure.
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