Chapter 7 EXAMPLES OF BIG DATA

LEARNING OBJECTIVES

After completing this chapter, you should be able to do the following:

     Identify how companies are currently using Big Data.

     Distinguish how organizations can apply the Big Data examples in the chapter to their organizations.

INTRODUCTION

The year 2016 was the year that Big Data was no longer a buzzword. Technology and the capacity to manage data have caught up to the point that everyone can now use Big Data—not just the early adopters.1

This year, 2017, will see an increase in data mining and collection and an ever-increasing amount of data that can be tailored to specific tasks. There will also be increased risk of data breaches. Established and emerging companies are using data to inform decision making, drive customer engagement, close sales, predict spending patterns, and increase revenue.

Additionally, machine learning and artificial intelligence will be key players in data analysis. Forbes predicts an increase in CDO (Chief Data Officers), analysists, programmers, and specialists with Big Data knowledge, though they see the demand for Big Data staffing tapering off as infrastructure and machines become adjusted to the new data load.2

The focus will be on fine-tuning big data into more manageable information, such as "fast data" and "actionable data" to cut down on the extra noise that some companies are getting overwhelmed by when they ask the wrong questions of their data.3

This chapter includes examples ...

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