Syncsort Doubles Down on Data Quality with Pitney Bowes Buy
Here’s a stat to ponder: With its $700-million acquisition of Pitney Bowes’ software and data business now complete, Syncsort becomes the second biggest vendor in the data quality space, per 2018 figures from IDC. But when you consider what else Pitney Bowes brings to the table besides data quality tools – including master data management (MDM), geo-location services, and third-party data – it’s no wonder that CEO Josh Rogers is so excited.
It’s not that Rogers was dissatisfied with Syncsort’s capabilities before acquiring Pitney Bowes data and software business. Syncsort had done a good job of building integration tools to help customers move data from transactional systems, including IBM System z mainframe and Power Systems servers, into the new generation of analytic engines, like Hadoop, Splunk, and Snowflake.
And let’s not forget that Syncsort added data quality capabilities with its acquisition of Trillium three years ago. But there were still some gaps in the lineup — gaps that have now been filled with the Pitney Bowes deal, which has Rogers genuinely excited.
“The Pitney Bowes business brings together this collection of really interesting capabilities around the data quality, cleaning, matching, discovery space, and more MDM capabilities,” he told Datanami. “We didn’t have that [MDM] capability before. But they also have this really interesting location analytics capability…and very robust data enrichment, third-party data that you can actually append for more context.”
When you add Pitney Bowes’ ability to add more intelligence and context to the data to Syncsort’s existing integration plumbing and data quality tools, Syncsort is ready to serve a bigger slice of the data management needs of its customer base, which now exceeds 11,000 organizations. And it also gives Syncsort a more complete data management story to tell prospective clients.
“When you combine [Pitney Bowes’ offerings] with the Syncsort capabilities, you have a few different things that happen,” Rogers said. “The first is you have a really impressive capability across that whole supply chain of data. I can help you optimize the systems that produce the data. I can help you move the data into the system that can analyze the data. And I can help you understand, cleanse, and enrich the data on the way in for maximum insight.
“I really like that combination of capabilities,” he continued. “It also creates a very large scale-data management business, one of the largest data management businesses in the world, north of $600 million of revenue, more than 2,000 employees operating in 26 countries.” (Syncsort also plays in the Power Systems high availability and security spaces, which aren’t factored into that equation.)
There is some overlap in the data quality department, between the Trillium data matching engine and the Pitney Bowes Spectrum offering, according to Rogers. Trillium has strong profiling and matching capabilities, he said, Rogers, while Pitney Bowes brings strengths in other areas, including data discovery, MDM, geo-location, and third-party data.
Both the Trillium and Pitney Bowes data matching engines will be maintained going forward, but the company will also pick the best features from both and combine them into one or the other offering, according to Rogers. “We will continue to support both matching engines,” he said. “But on a go-forward basis, there will be one single product that will carry features forward. That will play out over time.”
Considering how critical the data quality problem is right now, having multiple entries in the data quality department may not be such a bad thing. According to Rogers, data quality is the number one problem impacting big data analytics projects at this point in time.
“Just look at the big data space and what stalls people getting value out of it,” he said. “It’s not the ability to store the data. It’s not their ability to process the data. To some extent it’s their ability to integrate the data. But it’s the quality of the data. Can I really get good insights? And do I trust this data?”
Data quality continues to be “an incredibly powerful challenge that customers have to address,” Rogers said. “And it’s only becoming more important to fix it because as I start to think about pumping this data not into dashboards or reports, but into AI system that are going to make decisions on my behalf. Well, gosh, I better have that data right.”
Syncsort still doesn’t have a dog in the data catalog fight. But Rogers is happy to lean on Syncsort’s partner Collibra to provide those capabilities.
“To really understand the data, you’ve got to get the experts involved,” he said. “So how do you engage business users with data, and that generally manifests itself as a data governance program at enterprises. When you look at folks like Collibra, who are building a business-user focused environment for business users to understand, access, and leverage data in your organizations, now you’ve got the experts involved.”
It’s hard to overestimate the importance of having good, clean data, especially in light of the ongoing data explosion that is generating data of all shapes, sizes, and quality levels, as well as the new legal requirements around data governance. Having tools and techniques in place to synthesize that data is critical if an organization wants to leverage that data.
“The ability to derive actionable human intelligence from data requires ensuring that it has been integrated from all relevant sources, is representative and high quality, and has been enriched with additional context and information,” writes Paige Bartley, an analyst with 451 Research, in an August brief on Syncsort’s acquisition of Pitney Bowes.
“Syncsort, as a longtime player in the data management space, is further addressing these issues with the acquisition of Pitney Bowes’ Software Solutions assets – technology that complements existing data-quality capabilities to provide additional context and enrichment for data, as well as leverage customer data and preferences to drive business outcomes.”
As big data lurches forward into the AI era, companies are coming to the unfortunate conclusion that they aren’t going anywhere if their data is a mess. Vendors that can help companies straighten out their data as the first order of business, as Syncsort and others are doing, will likely find a steady supply of business for years to come.