While there’s a lot of interest these days in all things related to analytics, the cost of building out the infrastructure needed to tap into all that data has given more than a few organizations cause for pause.
To address this challenge, Teradata this week announced Teradata Database 14.10, which now includes 1,000 in-database analytics algorithms, enhanced access to native XML data, streamlined temporal analytics, and the ability to run geospatial data faster and more easily. Out of those 1,000 algorithms, 600 of them are being provided by Fuzzy Logix, which specializes in developing algorithms that can be embedded in databases. Teradata also plans to include those algorithms in its Aster Data massively parallel database platform in 2014.
In addition, Teradata announced that it has inked an alliance with Revolution Analytics to create an instance of its database that is optimized to run analytics applications in parallel based on the open source R programming language.
According to Chris Twogood, vice president of product and services marketing for Teradata, SQL remains the language of business IT. Not only are most organizations loath to abandon their investments in SQL, they would much rather extend them into other classes of data types.
In the case of Teradata, Twogood says that means being able to dynamically join different classes of data together via the Teradata management framework. The end result, says Twogood, is not just the ability to consume more data, but to also analyze that data at a much greater depth.
In addition, Twogood says that approach also makes storage management more efficient while providing a central framework through which coming into compliance with any number of regulations is that much simpler.
These days, data management has never been more complex with Big Data, the Internet of Things, and various other collections of information available. That’s why it’s even more integral for IT organizations to find a way to effectively manage all that data across the enterprise via what is becoming one unified, but federated, data warehouse.