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For data to be useful, organizations need to be able to trust that the data is accurate and authentic, which is the main purpose of data integrity software.
Among the many vendors in the data integrity market is Precisely, based in Pearl River, N.Y., which has a long history in the market. The company was founded in 1968 with a focus on sorting data for mainframes and was known as Syncsort until it was rebranded as Precisely in May 2020.
Precisely had grown its software assets both from its own development, as well as acquisitions over the years. Notable purchases have included Trillium Software in 2016 and data software assets from Pitney Bowes in 2019.
The vendor's ownership has followed a meandering path over the years. In 2015, Syncsort/Precisely was acquired by Clearlake Capital Group, which in turn sold the company to Centerbridge Partners in 2017.
On March 3, 2021, Precisely revealed that Clearlake Capital Group, along with private equity firm TA Associates, would be reacquiring Precisely from Centerbridge.
Financial terms of the deal were not publicly disclosed, though an unconfirmed Wall Street Journal report valued the deal at $3.5 billion. In this Q&A, Eric Yuan, the COO of Precisely, discusses the challenges and opportunities of data integrity technology.
What do you see as the significance of Precisely being acquired and what impact will it have on the data integrity software business?
Eric Yau: We're one of the largest businesses now in the data management and data integrity market; we've got 12,000 customers, and over 2,000 employees. Our mission in simple terms is we help deliver trusted data to our customer base.
As far as what we see as a benefit for us from the investment, I think what it means is that we have an ability to draw additional capital, to be able to build new innovation and create new capabilities. We might also now look to acquire some additional businesses to be able to help us make our customers' problems easier, and hopefully accelerate that journey that they're on.
So, I think it's really huge news around validating the challenges that our customers have and our offering to help solve them.
How do you define data integrity and the related concept of data trust?
Yau: What we see as the biggest challenge today, is that customers have access to large volumes of data, but they still cannot trust their data. Our focus is really to solve that and give our customers trust in the data that they are using for analytic purposes to make decisions.
What enables data integrity and data trust are three core things. The first is accuracy of data, the second is consistency and the third is context.
We deliver within our data integrity suite multiple capabilities that enable those three things. One such capability is with data integration that enables data to move from transactional systems and operational environments over to analytic warehouses. We also offer capabilities to be able to help organizations understand the quality of their data. Then there is what we call location intelligence, where we begin to enrich the data to be able to help support critical business decisions. In almost all cases, mission-critical business decisions have a location element to it.
Eric YauCOO, Precisely
For Precisely, as a vendor of data integrity software, what is the intersection of data integrity and data governance?
Yau: We see data governance as a very closely related topic and we have a very strong partnership with Collibra, which is a leading vendor in the space. Our relationship with Collibra is both technical, as well as in go-to-market efforts.
As a strategy, we're very partner-driven. Our focus is making sure that we identify what we believe to be the strongest players in the spaces that are adjacent to ours and develop good go-to-market relationships and technical integrations.
What has been the impact of the COVID-19 pandemic on digital trust at Precisely?
Yau: What we've seen with COVID is the accelerated push around digital transformation. Companies are recognizing that getting the right data to support business decision-making is absolutely critical.
People have been telling us what's more important now more than ever, not to say it wasn't important before, is being able to reliably get data quickly into their decision environments, including data warehouses, machine learning models and other business workflows.