From Amazon to Splunk, here's a look at the big data innovators that are now pushing Hadoop, NoSQL and big data analytics to the next level.
6 of 15
Datameer Stays Ahead Of The Analytics Curve Having lots of data is one thing. Storing it all in one scalable place, like Hadoop, is better. But the real value in big data is being able to structure, explore and make use of that data without delay. That's where Datameer comes in.
Datameer's platform for analytics on Hadoop provides modules for data integration (with relational databases, mainframes, social network sources and so on), a spreadsheet-style data analysis environment and a development-and-authoring environment for creating dashboards and data visualizations. The big draw is the spreadsheet-driven data analysis environment, which provides more than 200 analytic functions, from simple joins to predictive analytics.
Datameer customer Sears Holdings reports that it can develop in three days interactive reports that would take six to 12 weeks to develop using conventional OLAP tools. What's more, the spreadsheet-style interface gives business users a point-and-click tool for analyzing data within Hadoop. Through a recent partnership with Workday, Datameer is poised to embed its capabilities into that cloud vendor's enterprise applications. We'll be watching for breakthrough results.
6 Tools to Protect Big DataMost IT teams have their conventional databases covered in terms of security and business continuity. But as we enter the era of big data, Hadoop, and NoSQL, protection schemes need to evolve. In fact, big data could drive the next big security strategy shift.
Big Data Brings Big Security ProblemsWhy should big data be more difficult to secure? In a word, variety. But the business wonít wait to use it to predict customer behavior, find correlations across disparate data sources, predict fraud or financial risk, and more.
InformationWeek Tech Digest, Nov. 10, 2014Just 30% of respondents to our new survey say their companies are very or extremely effective at identifying critical data and analyzing it to make decisions, down from 42% in 2013. What gives?