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.
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Splunk Has The Pulse Of Machine Data Splunk got its start offering an IT tool designed to help data center managers spot and solve problems with servers, messaging queues, websites and other systems. But as the big data trend starting gathering steam, Splunk recognized that its technology could also answer all sorts of questions tied to high-scale machine data (a big factor in the company's successful 2012 IPO).
Splunk employs a unique language and its core tools are geared to IT types, but those power users can set up metrics and dashboards that business users can tap to better understand e-commerce traffic, search results, ad campaign effectiveness and other machine-data-related business conditions.
There's an overlap with Hadoop in that Splunk has its own proprietary machine-data repository, but database expert Curt Monash says Splunk is working on ways to work with Hadoop that go beyond the two-way integrations currently available. That would presumably leave Splunk free to pursue analytics while diminishing the need for redundant infrastructure. We'll be watching for that important release.
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.