IN THIS CHAPTER
Identifying technological trends in predictive analytics
Exploring predictive analytics as a service
Applying open-source tools
Selecting a large-scale big data framework
At a broad level, big data is the mass of data generated at every moment. It includes — for openers — data emerging in real time from
And that list barely scratches the surface; think of big data as a growing worldwide layer of data. What to do with it all? Answer: Start by using predictive analytics as a means to extract valuable information from the mass of big data, find patterns in the data, learn new insights, and predict future outcomes.
Here's a familiar example: You might have noticed ads appearing on websites while you're browsing that “just happen” to mention products that you already intended to buy. No magic at work here; the sites that show such ads are utilizing predictive analytics to data-mine (dig up insights from) big data: your buying patterns leave a trail of valuable data online; the well-targeted ads show that someone is using that data.
This chapter shows you how predictive analytics can crack the big-data nut and extract the nutmeat. First we guide you through a number of trends in the predictive analytics market ...