IBM is launching a new platform called the Integrated Analytics System, a new unified data solution designed to give users fast, easy access to advanced data science capabilities.
The system, which comes with a variety of data science tools built-in, allows data scientists to get up and running quickly to develop and deploy their advanced analytics models in-place, directly where the data resides for greater performance.
Because it is based on the IBM common SQL engine, clients can use the system to easily move workloads to the public cloud to begin automating their businesses with machine learning.
At the heart of the Integrated Analytics System are the IBM Data Science Experience, Apache Spark, and the Db2 Warehouse, all of which have been optimized to work together with straight forward management.
The Data Science Experience provides a set of critical data science tools and a collaborative work space through which data scientists can create new analytic models that developers can use to build intelligent applications quickly and easily.
The inclusion of Apache Spark enables in-memory data processing, which speeds analytic applications by allowing analytics to be processed directly where the data resides.
New to this class of offerings are machine learning capabilities that come with both the Data Science Experience and Spark embedded on the system.
Having machine learning processing embedded means that data does not need to be moved to the analytics processing, reducing the associated processes and wait times for analytics to run and respond. This simplifies the process of training and evaluating predictive models, as well as the testing, deployment and training as it is all done in-place.
The integrated architecture of the new system combines software enhancements such as asymmetric massively parallel processing (AMPP) with IBM Power technology and flash memory storage hardware and builds on the IBM PureData System for Analytics, and the previous IBM Netezza data warehouse offerings.
It also supports a wide range of data types and data services, including everything from the Watson Data Platform and IBM Db2 Warehouse On Cloud, to Hadoop and IBM BigSQL. Like these solutions, the Integrated Analytics System is built with the IBM common SQL engine, enabling users to seamlessly integrate the unit with cloud-based warehouse solutions.
Business users and IT operators will benefit the most from this platform, according to Rob Thomas, general manager at IBM.
“You can point this as a data set and then your ability to get to that outcome is really simple,” Thomas said. “Business users are going to love it. The management and administration of this system is incredibly easy because it is packaged up top to bottom as an analytic system. For IT operations the headaches of changing data centers, machines, rebuilding workflows, or ETL, all that goes away.”
In the future IBM will release a solution that enables better integration to other data sources and boost cognitive assist abilities.
“This is all about making machine learning really easy, that’s the design point, and that’s what we’ll continue to focus on,” Thomas said.
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