Santa Clara, CA-based Hitachi Vantara, a unit of Japanese conglomerate Hitachi Global, announced on June 23rd that it had acquired data governance player Io-Tahoe, based in New York. Io-Tahoe had been a unit of Centrica, a UK-based energy services company operating under brands including British Gas and Centrica Hive. Terms of the acquisition were not disclosed. The Io-Tahoe platform’s capabilities will become part of Hitachi’s Lumada DataOps portfolio.
ZDNet spoke with Hitachi Vantara’s Chief Product Officer and General Manager, Radhika Krishnan, who explained that the Io-Tahoe technology will compliment Hitachi Vantara’s existing platform and accelerate development of its data management prowess by as much as three years. Hitachi Vantara was formed by the merger of Hitachi Data Systems, Hitachi Insight Group, the previously independent BI provider Pentaho and, later, Hitachi Consulting Services. It has been focused on helping enterprise customers with their Industrial Internet of Things (IIoT) implementations and be in their overall digital transformation efforts. Its Lumada brand provides the umbrella for these varied assets.
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Wall Street-inspired application of AI
Io-Tahoe has long focused on the application of artificial intelligence to determine data lineage within and between data sources. It had also addressed data management functionality including data quality, data catalog, business glossary and sensitive data detection. While the platform worked well with metadata-based discovery, its specialty was finding patterns in the data itself, to automate the management of data not already well-documented or even well-understood.
Io-Tahoe’s original founders had cut their teeth in the New York banking world and headed up data and systems integration efforts that resulted from a series of acquisitions of smaller banks. The automated lineage and discovery was motivated by curing the pain points the founders themselves has experienced. I know this because, in full disclosure, Io-Tahoe was a client of my firm Blue Badge Insights, beginning shortly after its acquisition by Centrica.
The bottom line on Waterline
When I worked with the company, I definitely looked upon Waterline Data as an Io-Tahoe competitor, so it’s interesting that Hitachi Vantara has acquired both companies (it acquired Waterline Data in March, 2020). When I asked Krishnan how the two would coexist, she explained that Lumada Data Catalog (as the Waterline product has come to be called) is focused on data classification (which Waterline Data had called data “fingerprinting”) and core data catalog functionality, whereas Io-Tahoe’s platform was broader, focusing on a number of data management/data governance areas of functionality. Because of this, Krishnan believes the two can coexist, and even blend.
My guess is that’s true and that Io-Tahoe’s AI intellectual property — much of which is patented or patent-pending — can be combined with what was Waterline’s, to great advantage. The only way enterprises can hope to master and manage their data estates is by automating as much of their discovery, lineage, classification and cataloging as possible. The key to such automation is the smart application of AI , and the combination of Hitachi Vantara’s customer base and Io-Tahoe’s technology is coming together in the right place and at the right time.
Catalog sales
The Hitachi/Io-Tahoe deal is part of a larger trend, as a number of previously independent data catalog vendors have been acquired. In addition to Waterline Data and Io-Tahoe’s acquisition by Hitachi Vantara, Dell Boomi acquired Unifi Software in 2020 and Precisely (f.k.a. SyncSort) just this month announced its agreement to acquire Infogix. In addition, Microsoft acquired data security company BlueTalon in 2019 and, through that company’s leadership team, has fashioned its own data catalog and governance solution, Azure Purview.
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This consolidation wave makes two things clear: (1) data catalogs are very much at home within larger data management platforms and (2) data management is becoming critical to large enterprise technology companies as data volumes, data complexity and data protection regulations are on the increase.
