Big Data / Features

The award-winning CIO at Schindler Group is using digital tools -- sensors, analytics, mobile -- to take the No. 2 elevator company to the top.

Sports fans increasingly prefer watching games from home or at the bar rather than the stadium. Teams are tackling this trend by turning to big data and smart stadiums to make the in-stadium experience more compelling.

Three key areas that deserve special attention

A new data-processing solution from Mesosphere leverages Spark, Kafka, and Cassandra -- but eschews Hadoop -- for enterprise level real-time big-data needs

A bid made early this month by IBM to acquire Merge Healthcare could radically change the practice of medicine. Its effects might take shape through the first practical applications of artificial intelligence -- not in the diagnosis of disease, at least not at first, but in the streamlining of care.

1.The concept is still quite new. The term data lake, credited to Pentaho CTO James Dixon, has been bandied about for several years. But the idea of data lakes as corporate resources is still in its infancy, according to IDC analyst Ashish Nadkarni. A data lake is defined as a massive--and relatively cheap--storage repository, such as Hadoop, that can hold all types of data until it is needed for business analytics or data mining. A data lake holds data in its rawest form, unprocessed and ungoverned.

Big Data. Predictive analytics. Real-time. Actionable insight. There's a buzzword smorgasbord around the use of data to derive value. It doesn't help that sometimes the benefits can be esoteric, or at least hard to visualize. But sometimes the benefits are crystal clear, as in the fight against sepsis, one of the leading killers in the US.

Studies show that around 40% of products fail. But what if product designers could understand what features are most and least popular, which components tend to fail sooner than others, and how customers actually use products versus how designers think they use them? And, what if product developers could then utilize these insights to develop products that perform better, potentially cost less and, most importantly, are aligned with actual customer needs?

If you want to understand what it takes to collect, track and analyze reams of data, just check the weather. There are constant fluctuations, scores of data points and intense interest from all over the planet. Analyze the data correctly and someone in the state of Washington knows whether or not to wear a raincoat. Do it poorly and there might be a massive traffic pileup from people driving too fast on slick roads.

The recent Demo Traction event showcased a host of young companies that are gaining market momentum.  Each gave their pitch and then answered to a panel of judges.  If it is important for you to stay on the up and up with emerging technologies, this is must watch stuff.

Most financial service firms, which includes banking and insurance companies, are engaged in a big data project to increase the pace of innovation and uncover game-changing business outcomes. The pressing challenge now is how to drive more continuous value and unearth opportunities more rapidly. 

In these heady days of Big Data, a lot of organisations treat data collection like a Pokémon game: Gotta catch it all. But Dane Atkinson, CEO of cross-platform marketing analytics specialist, SumAll, says most organizations need to think wide, not big, when it comes to data.

A lot of security processes failed during the <a href="http://www.computerworld.com/article/2486959/cybercrime-hacking/target-says-hackers-likely-accessed-40-million-cards.html">breach of Target's systems</a> during last year's holiday season, but one surprising revelation was that the <a href="http://www.computerworld.com/article/2488641/malware-vulnerabilities/major-companies--like-target--often-fail-to-act-on-malware-alerts.html">retailer actually did receive</a> security alerts about the malware in its system. Yet because the security team was bombarded with alerts -- estimated at hundreds per day -- it couldn't adequately prioritize them.

Big data and analytics in 2015 will be less about collecting everything and anything and more about focusing on the most relevant data for actionable insights, according to analysts.

Anant Jhingran is no fan of the term 'data scientist.'

Long the purview of deep-pocketed enterprises, business intelligence software is increasingly making its way into small-and medium-sized businesses. These firms credit cloud technology, which tends to be both cheaper and easier to manage than on-premises BI systems.

As data volumes grow, figuring out how to unlock value becomes vastly important. Hadoop enables the processing of large data sets in a distributed environment and has become almost synonymous with big data. Here are 10 startups with solutions for unlocking big data value.

With the help of DigiWorksCorp, the Norman Rockwell Museum leveraged its transactional data and big data analytics to increase second-time purchasers by 150 percent and revenue by 49 percent.

Ever since President Obama signed the Open Data Executive Order, government agencies have been making their vast data stores available to the public. These once-secret data sets are proving a valuable business resource, too.

Job applicant tracking systems capture massive amounts of info on candidates. But all that data doesn't help if the best candidates aren't able or willing to complete the process. Going more simple and streamlined can make it easier to find talent.