The abundance of data and the increased usage of data mean that every business now is a data driven analytics business, and every user is an analytics user.
For the first time, in the 2016 Magic Quadrant for BI and Analytics, Gartner points to a fundamental shift away from traditional legacy platforms in favor of more modern BI solutions that deliver greater ease of use, speed and agility.
The abundance of data and the increased usage of data mean that every business now is a data driven analytics business, and every user is an analytics user.
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For the first time, in the 2016 Magic Quadrant for BI and Analytics, Gartner points to a fundamental shift away from traditional legacy platforms in favor of more modern BI solutions that deliver greater ease of use, speed and agility.
However, there is a lot of confusion about what constitutes a Modern Analytics Solution. Is it the use of Hadoop? Is it analytics on the cloud? Is it the use of data science? The truth is that you can build a fancy Hadoop based analytics solution on the cloud that is not the least bit modern. Leveraging these technological advances is not sufficient to create a modern analytics solution.
So what constitutes a Modern Analytics Solution? Here are some characteristics that make sense:
1) Agility
The solution should be built iteratively. The software development world has moved from a waterfall to an agile methodology. But the world of data and analytics are still, for the most part, designing elaborate data warehouses and data marts to serve business needs. The problem with this approach is that business is changing faster than the IT teams can react. Be agile – involve business – make small iterations, and fail fast.
2) Dynamic
Modern analytics solutions should be dynamic. The idea is to design the solution in a way that business users can influence the behavior of the solution as business changes without having to go to IT. This doesn’t necessarily mean that you put developer tools in the hands of business users. The solution has to be dynamic from the ground up to take business inputs and adapt.
3) Forward-Looking
Modern analytics solutions should be forward-looking. Yes, you can learn from the past. But modern solutions help you connect the dots to the future. In Today’s world, technology is advanced enough to predict and prescribe alternatives for actions and make those connections. The final decision is still with the business user until the system is trusted enough to act on her behalf.
4) Technology
Technology is still important. There have been big innovations in some key areas like cloud, massive data processing, distributed computing, and advanced analytics. It is prudent to leverage all the help you can to aid the business user make better decisions.
The only problem is that in practice, these solutions become more about the technology and less about the outcomes. A business user making the right decision at the right time is invaluable to the company. And that is the only purpose a modern analytics solution should have.
Learn more on how Saama builds Modern Analytics Solutions here.
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