Go Big Data, or be left behind, that was the chorus we heard over the last 10 days. We listened as industry analysts told us how leveraging Big Data and Analytics could help grow the bottom line; we learned how Facebook’s Graph Search might help you get found by recruiters (at the expense of your privacy); we watched Big Data vendors buy what they didn't want to build (or couldn't build fast enough); and we saw a NoSQL vendor with great promise get a humongous investment.
But enough of the summarizing. Without further ado, here’s big news from the world of Big Data that we found notable.
Want To Sell Some Software and Services? Think Human Resources And Staffing
Organizations that use high impact talent analytics outpace the competition by as much as 30 percent says a study conducted by Bersin by Deloitte, a research and consulting firm empowering Human Resource (HR) organizations to drive bottom-line impact.
But, despite that, not enough companies are leveraging data as part of their Human Capital strategies.
Just 14 percent of organizations in our study use advanced or predictive analytics to solve talent challenges and to plan their future workforce initiatives,” says Josh Bersin, a principal at the company.
Karen O’Leonard , a lead analyst at Bersin, reports that the company’s research shows that organizations with sophisticated talent analytics functions see improvements in recruiting, leadership pipelines and talent mobility. She adds that, "building capability in this area has become a critical priority for business and HR leaders; and will likely differentiate high-performing organizations in the future.”
SaaS Incentive & Performance Provider Xactly Deploys MapR’s Hadoop Distro
Variable compensation (like commissions, bonuses, profit sharing …) is a big line item at many companies — having the right figures and the right formulas is a must, both for the company and for its workers.
But for companies who have to manage billions of transactions per month, with second generation technologies the processes are slow, expensive and hard to scale.
Not so with Hadoop.
Ron Rasmussen, VP of engineering at Xactly Corporation says that with MapR’s Hadoop distro the company is able to run billions of transactions through their systems architecture worldwide 24x7. "The new data paradigm provided by MapR allowed us to perform data science at scale. We can iterate through our new insights algorithms much faster,” he says.
He adds that queries that used to take hours for their data science team now take minutes to process.
With this level of performance we can provide not only industry-leading deep analytics but also the new groundbreaking Xactly Insights™ and benchmarking solutions so a customer can see how it performs compared to others in similar industries.”
Work4 is Ready to Help Recruiters Separate the Chaff from the Grain
There’s a high probability that the best job candidate for any particular job has a profile on Facebook. But finding that person amongst 1.2 billion profiles isn’t easy.
Work4 makes it easier.
The company launched Graph Search Recruiter, a service which leverages Facebook’s Graph Search (algorithms built by Data Scientists) and Facebook’s member database to locate likely candidates and contact them. Read our article on Work4 here.
And in case you haven’t heard, Facebook changed your privacy settings this week. Users can no longer hide from appearing in Graph Search results. This makes Work4 extremely powerful.
Pivotal Goes Shopping
When it comes to buying mobile technologies, some purchase US$ 310,000 cell phones like the Vertu Cobra, others, like EMC spinoff Pivotal use their cash to acquire companies. Late last week, Pivotal bought Xtreme Labs, a mobile development and strategy shop that has built apps for Groupon, Microsoft and IAC.
Why? Because having a mobile play is a must, and Pivotal needs Xtreme’s talent to build Enterprise-grade mobile and Cloud solutions for its Big Data play.
IBM Buys The Now Factory
Communications service providers, aka CSPs, (though you and I know them as mobile service providers like Verizon, AT&T, T-Mobile and the like) are serious about squeezing insights out of their Big Data. And IBM doesn’t want its customers to have an Information problem they can’t help solve.
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