Please don’t throw the baby out with the bath water. Wait, I can state that better. Please don’t throw out the countless hours and money you have spent integrating and reporting on one of your most valuable assets in favor of a new and untested architecture that has promised to springboard your analytic capability into the next millennium. All you have to do is replace your existing investments with a data lake, map-reduced by Hadoop and streamed into a no-SQL platform running machine learning in the cloud and you are all set. Right? As my grandfather always said, "if it sounds too good to be true then it probably is."
Many of the new approaches and technologies designed to help springboard your analytic capability are truly amazing. Predictive Analytics, Machine Learning, Hadoop, data streaming ,no-SQL, the cloud, Data Lakes, and others all bring capabilities the average business could only dream of less than a decade ago. To leverage their power, it helps to start with a solid foundation.
You have spent years and invested in conventional approaches that may have yielded mixed results. You probably have less flexibility and slower turnaround for new analytics than you were hoping, the visualizations may not tell a story to you, you still can’t see into the future and adding new data sources still takes an act of congress. Often, the new technologies and approaches can quickly fill in those gaps for you quickly when used in partnership with your existing solutions.
Now if you really want to start over, go for it. Like many people in IT, I enjoy trying out new technologies. But if it is quick and scalable results you seek you need to determine how you can take your requirements, couple them with your existing capabilities and blending new technologies to create rapid and scalable business results.
Often a quick assessment of these factors can help you define a pragmatic plan and get you on your way to getting more value from your information. A partner such as Triverus can help bring a fresh perspective and broad experience. Regardless of who you select, be wary of anyone who tells you that to get results that are too good to be true, you first have to throw your information out with the bathwater.