October 01, 2013, 4:30 PM — Splunk continues to enhance its flagship machine data search engine so it can be used by business analysts and managers, in addition to its typical audience of system and network administrators.
The newly released Splunks Enterprise 6 includes new capabilities to easily visualize data, as well as a framework to build Web applications based on Splunk data, said Sanjay Mehta, the company's vice president of product marketing.
General business managers may also have a lot to learn from machine data, Mehta explained. For instance, for marketing executives, Splunk could provide a list of what types of smartphones are being using to access an organization's Web application, giving a manager a better idea of which phones to optimize for.
The Splunk search engine made its name for being able to easily search through log files and other forms of machine-generated data, allowing administrators to more easily pinpoint trouble spots or detect operational trends.
At the Splunk annual user conference, being held this week in Las Vegas, the company announced a number of new customers, including financial firm IG Group, U.S. wireless telecommunications provider T-Mobile, the U.S. Department of Energy's Oak Ridge National Laboratory, and Latin American online retail giant B2W.
For the past few years, Splunk has been adding more business intelligence capabilities to its namesake engine. Mehta would not offer an estimate of the percentage of Splunk's users deploying the software for analyzing data for purposes other than system administration, but did say it was a growing percentage of the user base.
One new feature, called Pivot, provides an easy way to build visual representations of data, through a drag-and-drop interface. Users can query different data sources and build reports -- without learning the Splunk query language.
Splunk Pivot can visualize and compare data sets using bar charts, pie charts, gauges and other common formats for data visualization. When the chart is clicked on, Splunk provides access to the underlying data set. Users can also import information from other sources, such as data from relational databases, to add to the data set being examined.
The software also allows users to build data models. The models help users better understand the relationships between different fields of data. The user interface has also been updated to make it easier to personalize.