John Santaferraro, Actian, at BigDataSV 2014 with John Furrier and Dave Vellante
@thecube
#BigDataSV
Time is the new gold standard for big data success. John Santaferraro, Vice President of Solutions & Product Marketing at Actian joins John Furrier and Dave Vellante in theCUBE, discussing the importance of rapid innovation. The co-hosts also explore the progression from Big Data 1.0 to 2.0.
“It used to be you could transform yourself every five or 10 years, now you have to innovate constantly,” says Santaferraro. The need for accelerated innovation is furthering the shift from Big Data 1.0 to 2.0.
According to Santaferraro, Big Data 2.0 stems from Big Data 1.0. Thus far, the industry has shown that users can store massive amounts of data at an affordable price and scale that to no end. As all of this data has poured into the data reservoir, companies have naturally been using data discovery and provisioning out of that reservoir. Santaferraro explains, “Big Data 2.0 is about making that shift to the point where we take those big data projects that are stored in the lab, and move them to production; to move it towards real-time operational engines.”
Vellante inquires about the best and worst of Big Data 1.0. Santaferraro reiterates that Big Data 1.0 effectively provided massive scale at reasonable cost. Among the various challenges, skill-set shortages was an important concern. Simply put, not everyone is well-trained in java and python programming. Additionally, there were enterprise shortcomings, especially for data security.
For Big Data 2.0 to succeed, it must be accessible to the masses and “abstract away complexity,” according to Santaferraro. Given a shortage of data scientists, new technologies must provide ways for business analysts to get insights without having to be data experts. Another step for Big Data 2.0 involves enhancing performance with a batch oriented system. Both of these considerations, in general, will make data more usable.
Actian has already simplified data analysis. “You can literally be a business analyst and drag and drop the pieces and put them in a data flow, in a workflow,” says Santaferraro. The Actian platform literally discerns where the data is, where to get the best performance and delivers results. He adds, “Our task as Actian is to go out to our customers and the broad community and start educating them about analytics 101. So, they don’t have to become a data scientist who creates and writes algorithms … Analytics 101 is about helping people understand how to use the algorithm and not just be able to create them.”
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John Santaferraro - BigDataSV 2014 - theCUBE
John Santaferraro, Actian, at BigDataSV 2014 with John Furrier and Dave Vellante
@thecube
#BigDataSV
Time is the new gold standard for big data success. John Santaferraro, Vice President of Solutions & Product Marketing at Actian joins John Furrier and Dave Vellante in theCUBE, discussing the importance of rapid innovation. The co-hosts also explore the progression from Big Data 1.0 to 2.0.
“It used to be you could transform yourself every five or 10 years, now you have to innovate constantly,” says Santaferraro. The need for accelerated innovation is furthering the shift from Big Data 1.0 to 2.0.
According to Santaferraro, Big Data 2.0 stems from Big Data 1.0. Thus far, the industry has shown that users can store massive amounts of data at an affordable price and scale that to no end. As all of this data has poured into the data reservoir, companies have naturally been using data discovery and provisioning out of that reservoir. Santaferraro explains, “Big Data 2.0 is about making that shift to the point where we take those big data projects that are stored in the lab, and move them to production; to move it towards real-time operational engines.”
Vellante inquires about the best and worst of Big Data 1.0. Santaferraro reiterates that Big Data 1.0 effectively provided massive scale at reasonable cost. Among the various challenges, skill-set shortages was an important concern. Simply put, not everyone is well-trained in java and python programming. Additionally, there were enterprise shortcomings, especially for data security.
For Big Data 2.0 to succeed, it must be accessible to the masses and “abstract away complexity,” according to Santaferraro. Given a shortage of data scientists, new technologies must provide ways for business analysts to get insights without having to be data experts. Another step for Big Data 2.0 involves enhancing performance with a batch oriented system. Both of these considerations, in general, will make data more usable.
Actian has already simplified data analysis. “You can literally be a business analyst and drag and drop the pieces and put them in a data flow, in a workflow,” says Santaferraro. The Actian platform literally discerns where the data is, where to get the best performance and delivers results. He adds, “Our task as Actian is to go out to our customers and the broad community and start educating them about analytics 101. So, they don’t have to become a data scientist who creates and writes algorithms … Analytics 101 is about helping people understand how to use the algorithm and not just be able to create them.”
