Why Big Data Should Be Called Mixed Data

Big Data is here to stay, and it is having a profound effect on businesses and societies. That having said; there are still so many organisations that have no clue about what Big Data is. Big Data means different things for different people, organisations and industries. While it is true

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5 Easy Steps to Embed Big Data in Your Business

For many organisations, it is still difficult to understand what Big Data is and how it should be incorporated into their business. This is quite understandable, as Big Data offers such radical and disruptive new possibilities as well as requires a dramatic cultural change for many organisations. The past weeks

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Why Trust and Data Breaches Don't Get Along

If you want to retain the trust of your customers, you better make sure that you don’t have any data breaches. As this infographic [http://www.safenet-inc.com/resources/data-protection/customer-loyalty-data-breaches-infographic/] , developed by Gemalto, shows, data breaches have a significant impact [https://www.thedigitalspeaker.com/need-end-end-quantum-resistant-encryption/] on consumer trust,

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4 Use Cases of Big Data and High Performance Computing

With the amount of data that organizations have to deal, with expected to grow into the exabytes in the coming year(s), we will need better technology. Bring in High-Performance Computing, or HPC in short, and a completely new world opens for you. HPC is dramatically changing the playing field.

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7 Important Big Data Trends for 2016

It is the end of the year again and that means it is time for the Big Data trends for next year. I did that for 2014 [https://datafloq.com/read/big-data-trends-2014/124], I did it for 2015 [https://datafloq.com/read/five-big-data-trends-2015/661] and now it is time for

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How Data Lakes Open New Possibilities for Your Organisation

In the past years, I have seen a flood of information on data lakes, and it looks like it is becoming as much of a buzzword as Big Data [https://www.thedigitalspeaker.com/3vs-sufficient-describe-big-data/]. I described data lakes [https://datafloq.com/read/five-big-data-trends-2015/661] as a growing trend in 2015

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Why The 3V’s Are Not Sufficient To Describe Big Data

It is generally accepted that big data can be explained according to three V’s: Velocity, Variety and Volume. In a 2001 research report, META Group (now Gartner) analyst Doug Laney defined big data as being three-dimensional, i.e. increasing volume (amount of data), velocity (speed of data in and

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