Year: 2017

Visit the Caringo Team at SC17

Visit the Caringo Team at SC17

We are having a great time at SC17 and hope you are too if you are here. Here’s a short video from our team on the ground so you can see just what’s going on in our booth. Come by and visit us in booth 1001 if you are at

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10 Predictions For AI, Big Data, And Analytics in 2018

10 Predictions For AI, Big Data, And Analytics in 2018

A new Forrester Research report, Predictions 2018: The Honeymoon For AI Is Over, predicts that in 2018 enterprises will finally move beyond the hype to recognize that AI requires hard work—planning, deploying, and governing it correctly. But Forrester also promises improvements: Better human and machine collaboration due to improved interfaces; enhancing

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Three Essential Cloud Security Techniques for Law Firms

Three Essential Cloud Security Techniques for Law Firms

As I mentioned in an earlier post, law firms have become more frequent targets for external attackers, but that doesn’t necessarily mean that they are limited to on-premises data management strategies. By combining a cloud provider’s security expertise and practices with additional security measures, businesses can gain the cost and efficiency

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The 3 Changing Characteristics of HPC Storage

The 3 Changing Characteristics of HPC Storage

Historically in the High-Performance Computing (HPC) space, storage was evaluated by cost vs performance. Most of the budget was spent on high-performance storage because it meant faster time to results. Once data sets were rendered, modeled or any other form of analysis was performed, the data either stayed on the

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Partha Sen: Big Data: Drilling for value

Partha Sen: Big Data: Drilling for value

Blindly adopting a big data strategy can do more harm than good for your organisation says Fuzzy Logix CEO Partha Sen in ITProPortal.com The post Partha Sen: Big Data: Drilling for value appeared first on Fuzzy Logix.

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Partha Sen: Five Data Challenges Every Index Provider Faces

Partha Sen: Five Data Challenges Every Index Provider Faces

Fuzzy Logix Founder and CEO Partha Sen in TradersMagazine.com on the five data challenges every index provider faces. The post Partha Sen: Five Data Challenges Every Index Provider Faces appeared first on Fuzzy Logix.

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Doing more with less – how would Alexander the Great have tackled today’s big data challenge?

Doing more with less – how would Alexander the Great have tackled today’s big data challenge?

When your business demands faster insights on less budget, what is the answer? The post Doing more with less – how would Alexander the Great have tackled today’s big data challenge? appeared first on Fuzzy Logix.

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Big Data: Drilling for value

Big Data: Drilling for value

Data in the 21st Century is like Oil in the 18th Century: an immensely, untapped valuable asset, according to Wired, amongst others.  Like oil, for those who see data’s fundamental value and learn to extract and use it there will be huge rewards. And, indeed for some time now, the lure of

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Dali Wireless Uses SDN to Virtualize the Fronthaul

Dali Wireless Uses SDN to Virtualize the Fronthaul

It’s no secret that mobile operators are exploring virtualizing the radio access network (vRAN) to cut costs and make their networks more efficient. Dali Wireless believes it can take that a step further by streamlining the fronthaul network. Fronthaul is the connection from the base station baseband processing units (BBUs)

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The World Series of HPC: SC17

The World Series of HPC: SC17

Fall is in the air and while my hometown Houston Astros are duking it out with the LA Dodgers in the 113th Major League Baseball World Series, I’m focused on preparation for what could be called the world series of high-performance computing (HPC)—the SC17 conference. It takes a lot of

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When Silicon Valley came to Wall Street

When Silicon Valley came to Wall Street

Gilead Sciences recently reached an $11.9bn agreement to acquire Kite Pharma for a 50 per cent premium to its monthly average stock price. Five days before the US takeover was announced, an artificially intelligent computer predicted it. The algorithm, developed by Dataminr, a New York-based technology group, had noticed unusual

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