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How to Tame the Big Data Beast It is one of those topics we can't escape -- and with good reason.

By Bernard Marr

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LinkedIn Influencer, Bernard Marr, published this post originally on LinkedIn.

'Big Data' is one of those topics we can't escape - and with good reason. With the increasing amount of data available to us today, understanding and leveraging big data has become more important than ever.

Among all the hype it is sometimes useful to step back and reflect on what exactly is Big Data, and how do we leverage it so that we can glean insights about business and society?

I have picked three slide decks that anyone interested in big data should read to make sense of it all.

Big Data 101

Get your bearings with this great introduction to big data. It's a nice selection of visual slides that help to put big data into context, and highlight the importance of big data for business and society. It starts by defining big data and then illustrating how "big' big data really is.

Related: Big Data For Small Business - Why It Matters! (LinkedIn)

Turning Data Into Value

In this deck, I break big data down into its simplest terms. I give examples of the different types of data we can now collect and analyse, and then provide practical real world examples of how big data is being used by companies today to turn data into value. For example, you can better understand your customers, optimize your business processes or even improve sports performance and national security.

The Future of Big Data

Big data is not just about data - it's about opportunities. SAP's Timo Elliott looks at big data trends in this deck, and covers the opportunities of data for business, including empowering employees and leveraging business networks.

Related: One Simple Trick To Have Successful Conversations (LinkedIn)

Bernard Marr

Author, Keynote Speaker and Consultant in Strategy, Performance Management, Analytics and Big Data

Bernard Marr is a best-selling author, keynote speaker and consultant in strategy, performance management, analytics, key performance indicators (KPIs) and big data.

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