The formal launch of the DataOps Suite, following a soft launch in late 2020, marks the integration of Hitachi Vantara’s data products into a single microservices-based architecture.

Today, Hitachi Vantara is announcing the general availability of their new Lumada DataOps Suite.  It lowers the cost of data operations by using AI-driven data management to improve data flow and productivity, for both data analysts and Line of Business leaders, who are able to use the suite themselves through its self-service capabilities.

The Lumada DataOps Suite’s official launch follows a soft launch in November 2020.

“This announcement is the culmination of a journey we have been on, which has brought all our old products into a single microservices-based architecture,” said said Radhika Krishnan, Chief Product Officer at Hitachi Vantara. “We are dramatically resetting our data management, as was seen with our acquisition of io-Tahoe a month ago. We are now going after two market segments – enterprise and industrial –  and once we have our complete profile of services, we can leverage them on broadly on things like fraud detection or industrial applications. That’s what we are going after.”

The Lumada platform has been around for years, as something of a niche offering for the company, but they have recently been expanding Lumada’s capabilities and use cases within a unified data architecture which responds to the demands of modern multi-cloud environment with an integrated data management layer.

“Cloud is introducing significant shifts in way customers operate,” Krishnan said. “Data lakes are no longer just on-prem, and the amount of time needed to ingest and process data takes an inordinate amount of time. That means that the amount of time spent deriving insights is cut to 1/3 to 1/4 of the available time, with the rest being spent cleansing and curating the data. The new suite is geared to addressing all of these issues.”

Leveraging AI to automate processes such as data discovery and cataloging lowers risk and decreases storage cost because data is intelligently labeled, governed and cross-referenced for version control and deduplication efforts. With time consuming manual tasks now automated.

The Lumada DataOps Suite eliminates manual tasks by leveraging AI. Using ‘fingerprint’ tagging technology that came with the 2020 acquisition of Waterline Data. It provides faster data discovery, and better data rationalization, to reduce both storage costs and risk.

“The platform lets you use the single pipeline to not just ingest but establish a profile as well,” Krishnan said. “Because you don’t have to use different tools, just our singular fabric, it’s simpler and quicker. We support multi-cloud deployments as well. We always supported AWS and Google, and have now added support for the Azure cloud as well.”

The Lumada DataOps Suite is powered by the new 9.2 version of Pentaho, Hitachi’s enterprise data integration and analytics platform. It provides updated data store support for Cloudera Data Platform and for HPE Ezmeral Data Fabric [formerly MapR]. Logging enhancements for Pentaho Business Analytics also improve installation cycles by bringing automated upgrades that lower maintenance costs and consolidate multiple licenses into one. They have also enhanced the Pentaho ‘kettle’ engine to greatly speed up query processing.

“We have made additions to the Lumada catalogue as well, enhanced the search capability, and when we announce the combined product with io-Tahoe, there will be additional capabilities,” Krishnan said.

“Pentaho is part of the Lumada suite, but for customers who want to buy Pentaho standalone, they can do that,” Krishnan added. “We have a large instal base and didn’t want to force them into a data suite path.”

Krishnan related how an investment bank customer in the U.S. made use of the suite.

“They had a lot of data siloes, which made it challenging to make decisions, as data access was slow and there were clunky pipelines,” she said. “They used us across 300 registered users and were able to ingest and process a huge amount of data with no custom coding, because of the singular pipeline and the reducing of risk from customized work in individual data lakes.”

Lumada had not been a huge channel product for Hitachi Vantara historically, but Krishnan said that has changed.

“We have pledged a significant emphasis on enhancing our channels since I came on board, and have exceeded our goals there, especially in LatAm, Asia Pacific and DACH,” she indicated. We now have many boutique data partners with specialization in data services, and our engagements with SIs and GSIs are also off to a very good start. We have engaged with some of the top GSIs in the data space. Our goal is to push our channel business to a very substantial growth number, both in the present year and again next year.”