01. Srikant Kanthadai, Capgemini, visits #theCUBE!. (00:18)
02. Steve Jones, Capgemini, visits #theCUBE!. (00:35)
03. The Big Data Journey and the Current Trends. (00:45)
04. Data Trends Outside the US. (03:04)
05. Data Governance and Value in the Context of Big Data. (06:57)
06. Fail Fast Methodology and Horizontal Disruption. (12:37)
07. What Do Clients Understand as Data Asset?. (13:36)
08. From Data Swamp to Quality Data. (16:45)
09. How Capgemini Engages with the Customer. (18:42)
Track List created with http://www.vinjavideo.com.
--- ---
Context trumps raw data for quality | #infa16
by Nelson Williams | May 24, 2016
When it comes to business, data is the oil in the gears. It makes everything else run. However, a surprising number of businesses don’t know how to find the true value of their data. Either the company allows the data to fall into an unmanaged swamp or they curate perfect data without any meaning attached. Both are a peril of data without context.
To shed some light on how data and context interact, John Furrier (@furrier) and Peter Burris (@plburris), cohosts of theCUBE, from the SiliconANGLE Media team, visited the Informatica World 2016 conference in San Francisco. There, they met with Srikant Kanthadai, global head of Data Management at Capgemini North America, Inc., and Steve Jones, global VP of Big Data at Capgemini.
Building on contextual quality
The discussion opened up with Kanthadai explaining that Big Data needs quality in the context built on top of the data itself. Bad data can turn good by bringing in the right context. It’s contextual quality companies need, not pure data quality, he said.
“The myth is that you don’t have a data swamp,” Jones said. He described how legacy hardware and processes could hold back a business from using its data properly. He mentioned a cultural difference where Europe, while going all-in on new technology, also took some time to think about where it wanted to get to and the right way to do it.
Defining data assets by outcomes
The ability to understand the totality of data within an organization is essentially zero, Jones said. In terms of valuing data as an individual piece, it’s based on what the company can do with it. “We’ve had 30 years trying to say it’s the data object that has value and that’s never, ever happened,” he said
The reality, Jones continued, is that today, how do you show the business the value of the pieces? When you demonstrate an outcome that shows the value of the data. “There are absolutely quantifiable outcomes,” he said.
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Steve Jones & Srikant Kanthadai, Capgemini - #infa16 - #theCUBE
01. Srikant Kanthadai, Capgemini, visits #theCUBE!. (00:18)
02. Steve Jones, Capgemini, visits #theCUBE!. (00:35)
03. The Big Data Journey and the Current Trends. (00:45)
04. Data Trends Outside the US. (03:04)
05. Data Governance and Value in the Context of Big Data. (06:57)
06. Fail Fast Methodology and Horizontal Disruption. (12:37)
07. What Do Clients Understand as Data Asset?. (13:36)
08. From Data Swamp to Quality Data. (16:45)
09. How Capgemini Engages with the Customer. (18:42)
Track List created with http://www.vinjavideo.com.
--- ---
Context trumps raw data for quality | #infa16
by Nelson Williams | May 24, 2016
When it comes to business, data is the oil in the gears. It makes everything else run. However, a surprising number of businesses don’t know how to find the true value of their data. Either the company allows the data to fall into an unmanaged swamp or they curate perfect data without any meaning attached. Both are a peril of data without context.
To shed some light on how data and context interact, John Furrier (@furrier) and Peter Burris (@plburris), cohosts of theCUBE, from the SiliconANGLE Media team, visited the Informatica World 2016 conference in San Francisco. There, they met with Srikant Kanthadai, global head of Data Management at Capgemini North America, Inc., and Steve Jones, global VP of Big Data at Capgemini.
Building on contextual quality
The discussion opened up with Kanthadai explaining that Big Data needs quality in the context built on top of the data itself. Bad data can turn good by bringing in the right context. It’s contextual quality companies need, not pure data quality, he said.
“The myth is that you don’t have a data swamp,” Jones said. He described how legacy hardware and processes could hold back a business from using its data properly. He mentioned a cultural difference where Europe, while going all-in on new technology, also took some time to think about where it wanted to get to and the right way to do it.
Defining data assets by outcomes
The ability to understand the totality of data within an organization is essentially zero, Jones said. In terms of valuing data as an individual piece, it’s based on what the company can do with it. “We’ve had 30 years trying to say it’s the data object that has value and that’s never, ever happened,” he said
The reality, Jones continued, is that today, how do you show the business the value of the pieces? When you demonstrate an outcome that shows the value of the data. “There are absolutely quantifiable outcomes,” he said.
