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Big Data

The Salient Aspects of Big Data Management

July 30, 2015 by Anand Srivastava

Throughout history men have acted in the best interests of their fellow man and become pioneers of many innovative ideas. One such pioneering feat was brought about by a genuine need to have people connected to one another, a trend expected from a highly social species. This foresight resulted in the development of the internet which guzzled and regurgitated information with such rapidity and in such copious volumes, users began to see the wisdom of collecting and storing it.[read more]

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Attackers Are in Your Network: Leverage Big Data to Get Them Out

July 29, 2015 by Mike Potts

Cyber attacks are detrimental to a company's security. Lancope's StealthWatch monitoring system collects and analyses network data to protect a company's information. Monitoring normal network activity allows the system to quickly detect security threats. This initial detection allows for early action in responding to cyber attacks.[read more]

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It’s Your Life, Starring Your Data

July 27, 2015 by Tamara Dull
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At a recent EPIC Champions of Freedom privacy event, Apple’s CEO Tim Cook finger-wagged some of his Silicon Valley neighbors—without mentioning names Facebook and Google—on how they were using their users’ data. “They’re gobbling up everything they can learn about you and trying to monetize it. We think that’s wrong. And it’s not the kind of company that Apple wants to be,” Cook said.[read more]

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Managing Big Data? Make Sure You Know the Challenges

July 27, 2015 by Gunjan Tripathi
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The ability to collect massive amounts of data has grown exponentially with the advent of the Internet and the number of people who use it. Data collection happens almost as a side effect of other computing activities.[read more]

Compensation of Data Scientists: Insights from the Past Year

July 24, 2015 by Linda Burtch

We are pleased to present our update to the first-of-its-kind 2014 report, The Burtch Works Study: Salaries of Data Scientists. This year, we compiled information on 371 data scientists for whom we know compensation as well as in-depth demographic information and job characteristics.[read more]

How Big Data is Shaping the Future of the Learning and Development Industry

July 22, 2015 by Brigg Patten

As big data helps to uncover employees’ potential and abilities, employers are able to carefully adapt not only their training methods but also their employee engagement levels and incentives, optimizing both the company’s overall performance as well as employee morale.[read more]

Using Procurement Analytics to Simplify Your Supplier Reconciliation

July 20, 2015 by Keith Peterson

Ask finance managers to name a necessary evil of their responsibilities and many will cite reconciling goods received against invoices not received (“GR-NI”). The GR-NI issue is time-consuming to manage but not exactly mission critical to finding new business.[read more]

The (Foreseeable) Future of Cloud Computing Explained

July 20, 2015 by Rick Delgado

The idea of connecting the world with information and data is not a new one and goes back to the 60s when the person credited with developing the first web connection, J.C.R Licklider, thought of interconnecting virtually everyone at any location or site. While the internet seems like what Licklider had in mind, cloud computing is clearly turning out to be another idea that’s probably what the pioneer had in mind.[read more]

Challenges of Working with Big Data: Beyond the 3Vs

July 16, 2015 by Venky Ganti
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Among many challenges in working with big data, the 3V’s (Volume, Velocity, and Variety) have gotten a lot of attention. Googling yields many results worth reading. Almost all of these focus on technological challenges in managing and processing big data. In this post, I would like to highlight a different set issues that make working with big data challenging, even if the underlying infrastructure is admirably able to handle all three V’s.[read more]

Big Data: Where Did All The Water Go?

July 15, 2015 by Shawn Gordon

Nighttime Flow Analysis works by using an optimal time to analyze for leaks. This is typically at night, when household water consumption is significantly low. At the lowest point, the observed GPM from the area is entered into the solution. By comparing this observation to the expected flow, the utility can iterate through different Sub-DMA configurations and target the problems so they are fixed much sooner.[read more]

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4 Big Companies Using Big Data Successfully

July 14, 2015 by Jessica Oaks
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When you're networking it's all about who you know but when it comes to actually doing business, these days it's all about what you know. That's because business decisions are now more than ever before data driven, and so the companies that are collecting it and analyzing it are the ones poised to rocket past the competition. Want proof? A global study commissioned by CA Technologies revealed that a whopping 90% of firms surveyed are seeing benefits thanks to big data implementation.[read more]

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Is Text Analytics the Next Frontier for Big Data?

July 14, 2015 by Jonathan Buckley

While the idea of text analytics may intimidate some organizations, quite a few vendors have popped up offering their services taking advantage of the technology. It’s a growing industry, one that’s predicted to be worth more than $6 billion by the year 2020. As long as companies start with a small portion of data and know exactly what type of information they want to find out, they’ll place themselves in an advantageous position.[read more]

Unlocking Big Data Means Truly Understanding the Customer Journey [INFOGRAPHIC]

July 13, 2015 by Andre Bourque

End-to-end big data analytics application provider Datameer found the most prevalent use case for big data is to better understand customer analytics. With consumers now interacting with companies across multiple, measurable channels, their interactions produce data that businesses can use to better respond to and anticipate customer needs.[read more]

Taking the Mystery Out of Big Data

July 10, 2015 by Doug Lautzenheiser
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In the not-so-distant past, firms tracked their own internal transactions and master data (products, customers, employees, and so forth) but little else. Companies probably only had very large databases if their industry called for high-volume and high-speed applications such as telecommunication, shipping, or point of sales. Even then, these transactions were all formatted in a standard way and could be saved inside the relational database IBM designed in the 1960s.[read more]

How Data Is Helping Sports Teams Increase ROI, Even in Off-Season

July 10, 2015 by Trips Reddy

Learn how the Florida Panthers are unifying data from disparate systems, third-party vendors and social media sites, so they can see who’s buying tickets, attending games and interacting with their content. This enables the Panthers to get a “360-degree fan view,” communicate one-to-one with them, sell thousands of tickets, find sponsorships and match the right experiences with the right fans.[read more]