ReadWriteEnterprise

IBM's Netezza division today announced a new appliance that allows organizations to analyze up to 10 petabytes of data in a matter of minutes. The technology is designed to help industries uncover patterns and trends from large data sets and is the first new product since IBM acquired the company last winter.

IBM Netezza and Revolution Analytics announced today at the Predictive Analytics World event that the two companies are working together to integrate the statistical programming language R into Netezza's Netezza TwinFin data warehouse appliance. The companies want to make it possible use R to process data on the data warehouse  appliance without moving to another system. This should enable much faster data processing.

Although no release data has been set, representatives from the companies say work on the project has begun in earnest. Select customers will beta test the integration in the coming months.

Jaspersoft, vendors of the open core business intelligence application of the same name, today announced new reporting tools designed to handle big data. It's adding more than a dozen connectors for databases such as Cassandra, Hadoop and Netezza. The connectors will enable people to use Jaspersofts' native syntax to query big data sources. This is a big step forward for Jaspersoft users wanting to work with big data, and should make Jaspersoft an attractive option for organizations looking for an off-the-shelf big data BI tool. The connectors are available from Jaspersoft's open source site.

IBM announced today that it is acquiring data warehousing company Netezza for $1.7 billion, continuing Big Blue's steady diet of acquisitions. Netezza will complement IBM's more expensive ISAS package and competes directly with the comparably priced Exadata from Oracle.

"Big data and data warehousing are at the core of every analytics problem," says Altimeter Group co-founder and analyst R "Ray" Wang. And Bitcurrent analyst Alistair Croll told us: "A lot of the CIOs I've spoken with recently tell me they feel more and more like a service bureau for their marketing departments. There's just so much information floating around, and chewing on it is hard work." So what does this deal mean for the future of big data in the enterprise?