It doesn’t take a genius to understand that the data warehouses and data marts of the past were of little use.

Their data was typically too old, the processing too cumbersome, and the costs too high.Today’s cloud-based data analytics have the ability to do things in real time, databases can operate at the “speed of need,” and even small enterprises can bind data analytics processing with the latest “cool kids” technology such as machine learning and predictive algorithms.[ The essentials from InfoWorld: How to choose the right data-integration tools • How Cosmos DB ensures data consistency in the global cloud. | Go deep into analytics and big data with the InfoWorld Big Data and Analytics Report newsletter. ]
I don’t want to rain on this parade, but it turns out the path to cloud-based data analytics is a longer and harder road than many enterprises projected.

As a result, failures are beginning to come up on my radar as IT encounters cost overruns, the technology fails to meet expectations, and just the sheer volume of data proves problematic. Here’s why.To read this article in full, please click here

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