Sign up | Login with →

First Look: SAS Factory Miner

June 26, 2015 by James Taylor

I got a briefing on SAS Factory Miner, to be officially released in July. SAS Factory Miner is designed to help organizations scale their analytic efforts, enabling them to solve more problems, faster, more accurately and without adding resources. SAS generally presents the analytic lifecycle with two main loops – a discovery one and a deployment one – both fed with data.[read more]

exclusive

Adopting a User Behavior Analytics (UBA) Solution

June 25, 2015 by Idan Tendler

The key to stopping hackers & rogue employees already exists in the enterprise in the form of user related data repositories. With the right analytics that focus on user behavior, security analysts can gain much needed context to better understand the insider threats they face on a daily basis.[read more]

exclusive

Don’t Let Big Data Become a Big Security Concern

June 24, 2015 by Daniel Matthews

Sometimes it takes massive failure to raise an alarm. The recent pillaging of up to 14 million federal employee social security numbers—which some have suggested was an act of cyber-espionage—is just one example among many in the ‘massive failure’ department.[read more]

exclusive

Big Data: The Amazing Numbers in 2015

June 23, 2015 by Bernard Marr

The Big Data Guru column.

Big data is growing — in fact, the sector is growing so fast and we are producing data so voraciously, that no one can afford to ignore it as a “fad” any more. And, it’s going to affect all companies, large and small, across all segments of the market — from healthcare to public safety, and retail to wholesale.[read more]

exclusive

Privacy Concerns Are Slowing Big Data Adoption Within Healthcare

June 23, 2015 by Jonathan Buckley

The problem is a lack of transparency and openness that exists in the healthcare system. Most patients don’t understand how their information is being used, or what data is shared. They don’t know if their identities remain private and if hospitals are treating their documents carefully with proper security measures in place. That’s a lot of ambiguity for such important and sensitive material.[read more]

Taking Control of Your CRM Data

June 23, 2015 by Martin Doyle

CRMs are supposed to be used to achieve better efficiency. By investing time in the CRM, sales teams should be able to identify leads, retain existing customers and successfully recruit new clients to the fold. Sadly, many CRMs fail to perform well. No system could feasibly solve every problem in your business, but if the CRM is creaking under the weight of dirty data, it could actually be hindering progress.[read more]

Even Chocolate Needs Smart Data

June 25, 2015 by Andre Bourque

How do you sell chipotle-accented chocolates and truffles with bourbon mash to those in the chocolate-loving populace who dream of pepper-laced confections and Kentucky sauced nuggets? You get smarter. The chocolate business, it turns out, is a lot like other conservative industries. Medical, construction, financial trading, and others are often reluctant to try the latest "new fangled" marketing techniques. Chocolate is the same way.[read more]

Taking the Cloud Apart: What Works for Your Business?

June 25, 2015 by Simon Mitchell

Just like real clouds ‘The Cloud’ is made up of many clouds, some overlapping and some merging into others with no obvious boundaries. Mouse-Over each for an explanation. A Standard Operating Environment (SOE) and a Management Platform (MP) are at the centre of modern IT. With an SOE you can provision new servers in seconds and remove them when you no longer need them. An MP is essential for controlling an infrastructure that may run into thousands of virtual machines.[read more]

exclusive

The Importance of Cleaning Up Your Dark Data

June 24, 2015 by Rick Delgado

Few trends have had as big of an impact on businesses as big data. Companies of all shapes and sizes have taken to big data with eagerness as they realize how much it can benefit their organizations. There’s little disputing big data’s impressive advantages, from opening up new avenues of innovation to increasing business productivity.[read more]

Figure Out Why You Should Use Big Data Before You Figure Out How

June 24, 2015 by RK Paleru
1

This is about the approaches to “big-data” technology. However, I start with a little detour and analogy on innovation. The purpose of this analogy is to trigger “Enterprise IT Organizations” to think outside convention before embarking on a journey to adopt or build “big-data," “data management,” “data integration” and related services.[read more]

exclusive

Big Data in Automobiles: Use-Cases for Today and Opportunities for the Future

June 22, 2015 by Anand Srinivasan
1

Location analytics is a big thing in General Motors these days. A spatial analysis of the data available with the company showed that their customers will drive two hours to buy a car. However, they may not be ready to drive down so far for a servicing. Also, customers will be ready to drive this far, bypassing a more convenient dealership, if they know they can save $500.[read more]

exclusive

Big Data Hadoop Use Cases in the Oil and Gas Industry

June 22, 2015 by Dave Mendle
1

While U.S. oil production has begun expanding - so much so that the International Energy Agency predicts that by 2016 the US will surpass Saudi Arabia and Russia - the rest of the world’s oil production has ceased to expand. In an effort to streamline and optimize oil and gas production methods, advances in instrumentation, process automation, collaboration, and data management are being developed.[read more]

exclusive

How Big Data Benefits Businesses

June 22, 2015 by Anand Srivastava
3

Big data has a huge potential to benefit businesses in any industry. It is much more than just a massive amount of data. Combining sets of data will give businesses real insights that can be used in making decisions and improving their financial condition. Before you can understand how big data can benefit your organization, it is important to know what big data really is. Big data can be best explained according to the 3 Vs – Volume, Variety and Velocity.[read more]