Lavastorm Brings Big Data Analytics to Businesses Using Hadoop & MongoDB

BOSTON, Mass., Aug. 5 — Lavastorm Analytics, a leading agile data management and analytics software company, today announced new features that extend the capabilities of its analytics engine and bring the power of big data analytics to business managers and analysts. These professionals are now able to easily extract data from Hadoop and MongoDB, a NoSQL database, and quickly integrate it with virtually any other data source enabling the fastest, most accurate way to discover insights in big data sources and transform them into business improvements.

“The days of the traditional data warehouse being the single, all-encompasing data source for the enterprise are over. Hadoop and MongoDB have proven themselves as cost-effective systems to store data, but extracting data from them has until now been limited to the domain of a sophisticated IT group or data scientist,” said Drew Rockwell, CEO of Lavastorm. “With the support we’ve added to the Lavastorm Analytics Engine, business analysts can now easily access data from these valuable sources and use it to enhance any analysis, discover new patterns or insights, translate insights into specific actions, and track results. Our goal is to help business users easily bring the widest variety of data to their analytic challenges, and Hadoop and MongoDB have become essential sources in the quest for actionable insight.”

For businesses using Hadoop, their business analysts will now be able to use the visual environment of the Lavastorm 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. Likewise, for MongoDB users, their business analysts will be able to extract data from MongoDB using Lavastorm’s visual controls. In both cases, business analysts benefit from rapid big data integration and insight discovery capabilities and can easily combine and enrich data from these sources with data from other enterprise or third-party sources. This will be especially valuable to businesses that have been using Hadoop or MongoDB as cheaper alternatives to traditional data warehouses. Business analysts can also package their data acquisition and analysis components for drag-and-drop reuse across their organization.

“Many companies are now relying on Hadoop and MongoDB to hold vast amounts of data, but they struggle to make it accessible to business users who know how to work with that data to improve their businesses. Lavastorm gives us the ability to ‘operationalize’ these data sources so that we can bring this data closer to business operations and use it to draw various insights on how to improve operations in sales, marketing, customer service, strategic planning, and other departments,” said Abhijit Shetti, VP and Global Head – Analytics, MphasiS. “Being able to quickly gather our data from within these systems and compare it to other data is going to reveal new ways to improve business operations and uncover previously unrealized issues.”

Features of the new updates:

• 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 metadata query control helps users find what data sources are available and view data down to the field level. 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.
• MongoDB capabilities include visual controls to obtain metadata from MongoDB sources, to query data in a MongoDB source, and to update MongoDB sources.

With these capabilities, analysts can use the parallel processing power of Hadoop to process big data sets in situ, without having to move the data. In addition, they can bring the result set from Hadoop into the Lavastorm Analytics Engine’s visual analytic environment where they can combine the Hadoop results with additional data and create complex business rules that they can use to cleanse and analyze the data. By using data in Hadoop and MongoDB, organizations have been known to improve operational efficiency, design innovative new products or services, better understand customer dynamics and more.

The new capabilities are part of the latest round of updates to the Lavastorm Analytics Engine, which gives business analysts self-service control over complex data so that they can rapidly integrate diverse data, easily discover elusive insights and continuously detect anomalies, outliers or patterns. The enhancements expand the engine’s Analytics Library, a collection of visual controls that can be quickly configured and assembled to create analytics applications, allowing analysts to create analytic applications ten times faster than if they used traditional development tools. The library contains objects that allow the user to acquire, prepare, transform, analyze and publish data.