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A bevy of non-traditional business intelligence players are entering the market as analytics across business silos merge. It's worth considering the new entrants.
You've heard about two-tier ERP plans where you relegate your installed SAP and Oracle systems to plumbing as divisions are launched on cloud systems that connect to on-premise systems. That approach, popularized by NetSuite, is beginning to be mimicked with business intelligence on-premise systems.
It doesn't take a renegade to see why a two-tier business intelligence (BI) plan may make sense. Consider the following:
- Business analysts are increasingly coming to IT for reporting on the business.
- IT has to pull from clunky BI systems and data warehouses for information.
- The information isn't real-time.
- And culling that data isn't self service since BI has been the realm of the chosen few analysts who know the systems.
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Meanwhile, the IT department has quietly been taking control of the situation as IT and application performance monitoring systems add visualization capabilities and easier to use interfaces. Consider:
- AppDynamics, which has a $100 million booking run rate, launched transaction analytics and a platform that goes beyond application intelligence to business analytics.
- New Relic also launched a business analytics platform and noted that the answers to your key business questions are in your software already.
- Tableau reported a strong quarter and CEO Christian Chabot said:
I think one of the reasons is that Tableau's market proposition to customers is a way of doing business intelligence work, analytic work, and executive dashboarding in a framework that is much more agile, easier to use and more self service. IT departments are increasingly championing this as the style they want to roll forward with. Because too often IT departments have, in essence, become a report factory for the rest of the company.
- Splunk, which started being used as an IT log file monitoring system, is being used for business purposes. The company also has improved its visualization tools on its platform.
- Big data is forcing traditional approaches to data warehousing and analytics to be rethought.
The upshot here is that new applications demand new intelligence systems. Traditional business intelligence may not be able to keep up. In other words, you may want to start testing out IT and application monitoring systems as quasi BI tools. These analytics' silos won't last for long. It's time to start pondering next steps and evaluating options beyond what you already have installed.
Ultimately, these players are going to increasingly collide.