The Cube - Strata Conference 2012 - Sandy Steier, 1010data, with Dave Vellante and Jeff Kelly
1010data (pronounced Ten-ten data) is a SaaS big data management and analysis provider created by two former Wall Street analysts in 2000, before either Software-as-a-Service or big data existed as industry terms. It has more than 200 blue-chip customers in finance, retail, customer packaged goods, healthcare, and telecom, including Bank of America, J.P Morgan/Chase, AutoZone, RiteAid, and Dollar General. Some of these companies use 1010data as their data warehouse, while others use it in part to share data with supply chain members and remote subsidiaries.
It’s primary user interface uses the spreadsheet analogy, leading to the image of the “trillion row spreadsheet,” although co-founder and CEO Sandy Steier admitted in a live webcast (see full interview below) on SiliconAngle.tv from the Strata Conference that the largest actual display in a single sheet is about a half trillion rows. And it really is not a spreadsheet, it simply has a user interface that looks like one.
Actually, Steier said, the underlying database uses a combination of old technologies, some of which IBM used 35 years ago but stopped using “to the detriment of IBM and the market.” He and cofounder and CTO Joel Kaplan built the base system for their own use on Wall Street and became more interested in the potential of what they had built than in their financial industry jobs.
Their clients send them data either via FTP or on physical media. Once loaded, which happens quickly, the data becomes available to the client’s market analysts and researchers online over secure connections, either in the spreadsheet analog or as a database. Steier said it offers several advantages including that analysts do not need to use complex programming but can work with the data directly and see results quickly, even when working with very large databases, so they can refine their analysis. And because it operates on the Internet, the data is easily shared with multiple locations and with supply chain members and business partners, which is difficult to do with internal data warehouses. This makes it attractive, for instance, to retailers with large numbers of store locations spread across wide geographies.
1010data’s technology also does not limit it to structured data, despite the spreadsheet analogy. So the advent of big data, which often involves large amounts of data generated in the cloud, as well as SaaS cloud computing, has generated new market opportunities for the company.
“There was always big data,” Steier said to Wikibon Chief Analyst David Vellante and SiliconAngle CEO John Furrier. “But the data is getting bigger, and traditional technologies are beginning to fail, while people are using it in a more sophisticated way.”
If one company starts finding competitive advantage through big data analysis, he says, then all that company’s competitors have to start their own big data projects to catch up. “It is a feedback loop that drives customers to us, especially as they start discovering the limitations of relational databases.
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Sandy Steier | Strata Data Conference 2012
The Cube - Strata Conference 2012 - Sandy Steier, 1010data, with Dave Vellante and Jeff Kelly
1010data (pronounced Ten-ten data) is a SaaS big data management and analysis provider created by two former Wall Street analysts in 2000, before either Software-as-a-Service or big data existed as industry terms. It has more than 200 blue-chip customers in finance, retail, customer packaged goods, healthcare, and telecom, including Bank of America, J.P Morgan/Chase, AutoZone, RiteAid, and Dollar General. Some of these companies use 1010data as their data warehouse, while others use it in part to share data with supply chain members and remote subsidiaries.
It’s primary user interface uses the spreadsheet analogy, leading to the image of the “trillion row spreadsheet,” although co-founder and CEO Sandy Steier admitted in a live webcast (see full interview below) on SiliconAngle.tv from the Strata Conference that the largest actual display in a single sheet is about a half trillion rows. And it really is not a spreadsheet, it simply has a user interface that looks like one.
Actually, Steier said, the underlying database uses a combination of old technologies, some of which IBM used 35 years ago but stopped using “to the detriment of IBM and the market.” He and cofounder and CTO Joel Kaplan built the base system for their own use on Wall Street and became more interested in the potential of what they had built than in their financial industry jobs.
Their clients send them data either via FTP or on physical media. Once loaded, which happens quickly, the data becomes available to the client’s market analysts and researchers online over secure connections, either in the spreadsheet analog or as a database. Steier said it offers several advantages including that analysts do not need to use complex programming but can work with the data directly and see results quickly, even when working with very large databases, so they can refine their analysis. And because it operates on the Internet, the data is easily shared with multiple locations and with supply chain members and business partners, which is difficult to do with internal data warehouses. This makes it attractive, for instance, to retailers with large numbers of store locations spread across wide geographies.
1010data’s technology also does not limit it to structured data, despite the spreadsheet analogy. So the advent of big data, which often involves large amounts of data generated in the cloud, as well as SaaS cloud computing, has generated new market opportunities for the company.
“There was always big data,” Steier said to Wikibon Chief Analyst David Vellante and SiliconAngle CEO John Furrier. “But the data is getting bigger, and traditional technologies are beginning to fail, while people are using it in a more sophisticated way.”
If one company starts finding competitive advantage through big data analysis, he says, then all that company’s competitors have to start their own big data projects to catch up. “It is a feedback loop that drives customers to us, especially as they start discovering the limitations of relational databases.