Lavastorm Adds Features for Hadoop and MongoDB Users

 
 
By Nathan Eddy  |  Posted 2014-08-11 Email Print this article Print
 
 
 
 
 
 
 
lavastorm and data analytics

For MongoDB users, their business analysts will be able to extract data from MongoDB using Lavastorm’s visual controls.

Data management and analytics software Lavastorm added features to extend the capabilities of its analytics engine including the ability to extract data from Hadoop and MongoDB, a NoSQL database.

The new capabilities are part of the latest round of updates to the company’s Analytics Engine, which gives business analysts self-service control over complex data so that they can integrate diverse data, discover more in-depth insights as well as detect anomalies, outliers or patterns.

Business analysts can also package their data acquisition and analysis components for drag-and-drop reuse across their organization.

For businesses using Hadoop, their business analysts will now be able to use the visual environment of the Analytics Engine, the company’s data discovery solution, to find data within Hadoop and acquire data from the cluster using Hive query language, rather than relying on IT-developed MapReduce routines.

Hadoop capabilities include a visual control to sample data from a Hive distributed data warehouse using the popular Hive query language as an alternative to SQL. A query control allows business users to query their Hadoop infrastructure and access data in the Hadoop file system just as they would data in any other data source.

A join control helps users correlate, combine, and filter data from multiple tables in Hive and bring that data into the Lavastorm Analytics Engine’s visual analytic environment so that it can be combined with data from other sources and analyzed.

For MongoDB users, their business analysts will be able to extract data from MongoDB using Lavastorm’s visual controls.

Capabilities include visual controls to obtain metadata from MongoDB sources, to query data in a MongoDB source, and to update MongoDB sources.

With these additional features, businesses have the ability to bring the result set from Hadoop into the Analytics Engine’s visual analytic environment where they can combine the Hadoop results with additional data and create business rules to cleanse and analyze the data.

"Data analytics should be important to every business – it is the source of increasing amount of innovation around the world," Drew Rockwell, CEO of Lavastorm, Analytics, told eWEEK. "It is a great time for a SMB to get into analytics because agile tools designed for business users to use and not IT allows them to remove the IT bottleneck and not tax already stretched budgets."

Rockwell said in the future, more real-time insights and business decisions across a growing number of industries will be based off analytics, and predictive analytics will also start to become more prevalent as businesses will not only want analytics to help uncover insights from the past and present, but will look for the analytic benefits to spill over to the future.

"For example, one of our retail customers used our data discovery platform to create automated analytics applications that sifts through volumes of point of sale data and flags potential fraud," Rockwell said. "It not only saves much manual labor, but it has been 100 percent accurate in identifying situations where theft or policy breaches were taking place."

 
 
 
 
 
 
 
 
 
 
 
 
 

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