#FREE Techniques and Concepts of Big Data #IT #Hadoop

Big data is big news. But what is big data, and how do we use it? Simply put, big data is data that, by virtue of its velocity, volume, or variety (the three Vs), cannot be easily stored or analyzed with traditional methods. Spreadsheets and relational databases just don’t cut it with big data. In this course, Barton Poulson tells you the methods that do work, introducing all the techniques and concepts involved in capturing, storing, manipulating, and analyzing big data, including data mining and predictive analytics. He explains big data’s relationship to data science, statistics, and programing; its uses in marketing, scientific research, and tools like Amazon’s recommendation engine; and the ethical issues that lie behind its use.
This course qualifies for 2 Category A professional development units (PDUs) through lynda.com, PMI Registered Education Provider #4101.

LEVEL –  Beginner

COURSE TOPICS:

What makes big data “big”
Understanding how big data impacts consumers, businesses, and research
Exploring the intersection of data science and big data
Facing big data’s ethical challenges
Understanding the sources and structures of big data
Storing big data
Prepping big data for analysis

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LEARN THIS COURSE FOR FREE *10 days of free unlimited access to “Techniques and Concepts of Big Data”

Instructor’s Welcome Note:

– Hi, I’m Barton Poulson, and I’d like to welcome you to Techniques and Concepts of Big Data. Big Data refers to data that, because of its size, speed, or format– that is, its volume, velocity, or variety– cannot be easily stored, manipulated or analyzed with traditional methods, like spreadsheets, relational databases, or common statistical software. We’ll take a look at a practical definition of Big Data, how it relates to fields like data science, statistics and programming, and the variety of people and skills involved with Big Data.
We’ll also discuss how Big Data has been used in fields such as marketing and scientific research; how Big Data influences customer services, like recommendation engines; and the ethical issues raised by Big Data. Finally, we’ll go over common methods for generating or capturing Big Data, storing and manipulating Big Data, and analyzing and visualizing Big Data, including data-mining and predictive analytics. The applications of Big Data have been extraordinary, and its possibilities are immense. This overview should help you get excited about what Big Data can do for you.
And with that in mind, let’s get started with Techniques and Concepts of Big Data.

 

 

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