Why is there a gap between Big Data and business intelligence tools?


Why is there a gap between Big Data and business intelligence tools?

We are at a turning point in the data industry. Many organizations get minimal returns on their data and analytics investments. They spent a lot to store, clean, and manage their data, but thousands upon thousands of data points were wasted. Over the past decade, business intelligence (BI) tools have enabled organizations to examine data to determine changes in their businesses. A stakeholder can use the BI tool to determine what caused the drop in sales in the third quarter. But these tools lack the critical ability to tell businesses why sales are falling. This "gap" lies in the why. 

 It's essential to understand why the industry is starting to move to new tools. Current BI tools give organizations only half of what they need - they tell the organization there's a fire, but they don't tell them why. This is where intelligence decides to come into play. 

 Business Intelligence fills the void left by Big Data and BI tools. Using the power of machine learning and cloud computing, tools like Sisu not only reveal how metrics or KPIs are changing but also why the changes are happening. It helps organizations use their data. Because business intelligence tools scale to so many calculations, they help organizations analyze enterprise-wide data in real-time and leverage the results to bolster decision-making. With the comprehensive, contextual ability to understand why certain parts of their business work the way they do, business leaders can determine the best course of action.

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