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4/25/2016
07:06 AM
Jessica Davis
Jessica Davis
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10 Big Data Books To Boost Your Career

People with big data and data science skills are some of the most sought after professionals because demand is outstripping supply. Here are 10 books that can help you learn everything about the emerging field and the tools you will need to conquer it.
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(Image: MichaelJay/iStockphoto)

(Image: MichaelJay/iStockphoto)

Data science and analytics are some of the top in-demand job categories in the technology industry today. Indeed, demand is higher than supply for these specialists, and many data science master's degree programs have sprouted in the past few years. The online learning curriculum has expanded significantly, too, with offerings from the big MOOC providers (massive open online course) such as Coursera and Udemy, as well as vendors who offer the technologies that enable big data, such as MapR and Confluent, among many others.

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But aside from formal education, either online or offline, there are other ways to learn about this emerging field, and to gain some of the skills you need if this is the next step for you on your career journey. If you're an executive leading a team of data scientists, you might need better grounding to learn about the technology the group's members use to do their jobs.

InformationWeek has put together a collection of essential reading for data scientists, business analysts, executives, and others who are interested in this rapidly growing field.

Our collection features 10 books to help you understand everything from the ramifications of widespread algorithms and models for our future society, to how to use some of the most popular languages and tools to generate insights from data.

What are the essential skills for data scientists to possess? What are some of the key recipes for R users to leverage in their work? How can you use data to tell stories that compel your audience to action? How can you work with big data technologies such as Apache Hadoop and Apache Spark?

What are the cultural and economic ramifications of a future world where so many decisions are based on a black box of algorithms? Take a look at this list to find out. Are there any that you will add to your reading list? Did we miss any? Let us know in the comments below.

Jessica Davis is a Senior Editor at InformationWeek. She covers enterprise IT leadership, careers, artificial intelligence, data and analytics, and enterprise software. She has spent a career covering the intersection of business and technology. Follow her on twitter: ... View Full Bio

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