Database Reference
In-Depth Information
Chapter 12
Big Data Analytics
What You Will Learn in This Chapter
• Exploring Data Mining and Predictive Analytics
• Using the Mahout Machine Learning Library
• Building a Recommendation Engine on Hadoop
Up to this point, the focus has been on building a foundation that enables
you to capture and store large volumes of disparate data. When this data is
collected, as you have seen in previous chapters, it can be easily summarized
and aggregated using tools built in to the Hadoop ecosystem.
Although this is noteworthy, it alone hardly justifies the time or investment
requiredtoimplementabigdatasolutioninyourorganization.Therealvalue
forbusinessesinbringingthisdatatogetheristhatitcanbeminedforhidden
patterns, correlations, and other interesting information that can facilitate
better business decision making.
This chapter covers how you can use HDInsight and Hadoop as a big data
analytics platform by taking advantage of the Mahout machine learning
library to deliver predictive analytics, such as implementing a
recommendation engine, and to perform more common data mining in the
form of clustering and classification.
Data Science, Data Mining, and Predictive Analytics
Included in just about every big data discussion, the art of data science is
onethatisbuiltonmultipledisciplines.Variousskillsinvolvingmathematics,
statistics, and computer science are combined to allow practitioners in this
field, known as data scientists, to broadly explore data and patterns.
Two of the most common techniques used by data scientists to unveil these
patterns are data mining and predictive analytics.
