Real-time demands require real-time solutions, as they say. Increasingly, that's the creed of business intelligence.
Intelligence gained through analysis of the wrong data is ineffective and therefore is not, strictly speaking, "intelligence." Successful BI experts understand this much, at minimum: You've got to pick the right data to monitor and analyze, or applying the tools of analysis is a wasted effort. This is true for every level of business intelligence practitioner -- and more so for those whose enterprises want to be able to react to information in "real time."
I'm going to avoid getting hung up on whether real-time enterprises actually exist (they don't, but I'll save that for some other editorial). But suffice it to say that more and more, businesses want to carry out the whole cycle from data generation to business reaction -- gathering information, reporting it, analyzing it, and acting on it -- if not in real time, then at the very least really, really fast.
To do that, you’ve got to be looking at the right data. As Gartner group VP and research fellow Kenneth McGee outlines in a story we ran recently, that means a lot more than deploying some dashboard tool. To avoid business surprises like sales shortfalls or inventory out-of-stocks, managers need to stay vigilant to the warning signals that precede them. McGee clearly outlines a process for identifying what data to monitor in real time in order to spot those advance warnings.
Such guidelines can be hugely valuable to IT professionals whose managerial-side bosses want to avoid unexpected business disasters (which is all of them) and expect IT to help them do it (which is an increasing portion of them). McGee's plan entails not just determining and prioritizing business goals and the metrics that gauge them, but also understanding whether real-time information on those metrics allows an effective response at all.
The Agile ArchiveWhen it comes to managing data, donít look at backup and archiving systems as burdens and cost centers. A well-designed archive can enhance data protection and restores, ease search and e-discovery efforts, and save money by intelligently moving data from expensive primary storage systems.
2014 Analytics, BI, and Information Management SurveyITís tried for years to simplify data analytics and business intelligence efforts. Have visual analysis tools and Hadoop and NoSQL databases helped? Respondents to our 2014 InformationWeek Analytics, Business Intelligence, and Information Management Survey have a mixed outlook.
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