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Eliminating Bottlenecks in Analytics

For many organizations, analytics processes are riddled with roadblocks. There are many valid reasons why these roadblocks existed in the past, and they were often based on technical limitations. Even though storage and compute capacity have increased dramatically, many of the approaches that were designed for the constraints of the past are still in place today. It’s time to rethink analytics processes to minimize or eliminate these roadblocks so that individuals in line-of-business functions can access data to make decisions more easily and more quickly.

Organizations need to process more data more quickly than ever before. Yet our research shows that accessing and preparing data continue to be two of the most time-consuming parts of making data available for analysis. One reason these tasks become time consuming is due to the effort needed to transform the data from its original form into a form that supports analytics processes.

 
 

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About the Author

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David Menninger

SVP and Research Director
Ventana Research

David Menninger is responsible for the overall direction of research on data and analytics technologies at Ventana Research. He covers major areas including artificial learning and machine learning, big data, business intelligence, collaboration, data science and information management along with the additional specific research categories including blockchain, data governance, data lakes, data preparation, embedded analytics, natural language processing (NLP) and IoT.