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JasperSoft Expands Data Connections for Embedded Analytics
Users can speed up analysis by accessing their data directly or with data virtualization.
Posted Feb 11, 2014
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JasperSoft, a provider of commercial open-source business intelligence tools, announced a product update that will dramatically expand the number of ways users can connect JasperSoft’s embedded analytics to many popular database technology products.

Users can access databases directly or natively; through ETL (extract, transform, and load); or through data virtualization that allows analysis of multiple databases without creating a data warehouse. The three ways of accessing will work for Hadoop’s Hive, MongoDB, and Cassandra. JasperSoft already has a dozen or so connections to other products, like Amazon's data warehouse service Redshift. It is available either on premises or as a cloud deployment, with versions available on Amazon Web Services and Microsoft Windows Azure since the fall.

"We found from working with our developer community that they wanted more flexibility," explains Mike Boyarski, JasperSoft’s director of product marketing.

After looking at download statistics and conducting surveys, JasperSoft chose Hive, MongoDB, and Cassandra as areas of focus when it came to connections.

Direct, or native connections allow users to "point JasperSoft at a data engine, run a query, and display the results as fast as possible. It's about real-time access to data. You can take advantage of speed, since there’s no moving data around. You're just putting a query directly against engine," Boyarski explains. These direct connections are the "unique value proposition" for JasperSoft, and a key area of focus.

For users who want to move one or more data sources into a data warehouse and then perform analysis there, they can now do so with Hive, MongoDB, and Cassandra. While this area has been traditionally one on which many companies have focused, Boyarski sees the trend going towards direct connections and data virtualizations since they don't involve moving or copying data.

Users can now pull data from more than one database and perform analysis without moving it to a database first with data virtualization. The tool will also allow less experienced users to run analysis on a single database without learning native languages. "You can combine sales CRM data with something that's part of a social analytic feed, where typically those sources are separate," Boyarski offers as an example.

JasperSoft's product updates will give users more flexibility in the programs with which they work and more speed, with the ultimate goal of bringing more analysis to more people. "The story is to connect your data in the most flexible way possible and embed that insight so that people who are the sales rep, marketing manager, nurse, or educator can consume that visualization inside the application, and it's not some specialty application only a data scientist resource can access," Boyarski envisions.

JasperSoft is open-source, with 400,000 community members. Boyarski estimates the open-source version is powering 130,000 software apps, 2,000 of which are paid subscribers. Traditionally, JasperSoft’s open-source solution has been popular among technology projects that start out unfunded and without sponsorship. Pro upgrades can happen after a project becomes a success.

Boyarski, who has seen the immense popularity of big data as a buzzword rise in the past few years, is now seeing more action backing up the big data talk. "In the past year, things have really picked up. People are starting to spend real money on big data," he says.


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