Organizations with massive volumes of data stored in Hadoop need a way to extract value from all that information. And that’s where analytics comes in.
With big data analytics, you can implement data mining, predictive analytics, text mining, forecasting and optimization to explore options and make the best possible business decisions.
This paper gets you started, laying out eight considerations to think about when it comes to Hadoop and big data analytics, including:
- The importance of in-memory analytics.
- How to optimize your data preparation processes.
- Uncovering insights through big data exploration.
- The skill sets needed to derive benefits from Hadoop.
- And more!
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