On Big Data and the IoT: Interview with Bill Franks (Part 2)
MAR 19, 2015 07:09 AM
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On Big Data and the IoT: Interview with Bill Franks (Part 2)
 
Roberto V. Zicari, editor of ODBMS.org, spoke with Bill Franks, Chief Analytics Officer for Teradata, about data warehouses, Hadoop, the Internet of Things, and Teradata`s perspective on the world of big data. Roberto is Full Professor of Database and Information Systems at Frankfurt University. He was for over 15 years the representative of the OMG in Europe. 
 
What are the key differentiators of the Teradata database core architecture?
 
Bill Franks: As I said, the Teradata DW was differentiated from the start – uniquely architected for analytics from day one. However, I would add that Teradata continues to broaden our differentiation: we’ve built the best data orchestration software in the industry (Teradata Unity and QueryGrid). The orchestration software is key – because it enables our customers to choose a file system that they use to store the data in – and the analytics that they apply to that data independently — and marry them together with software.
 
It helps reduce the complexity of connecting to, accessing, understanding interfaces and getting value from multiple analytical systems. Another differentiator is Teradata Intelligent Memory, introduced two years ago. TIM is the world’s first extended memory technology beyond cache to increase query performance.
 
Users can configure the exact amount of in-memory capability needed for critical workloads – based on temperature – hot or cold data. The list goes on. I would say that our data technology really does focus on how data is best used – and what proficient users need most.
 
Is SQL really the right language to handle Big Data Analytics?
 
Bill Franks: In some cases yes and in some cases no. We want users to be able to utilize whatever language or platform is best for any given task. There are many big data requirements that perfectly fit SQL and many that don’t. The key is enabling scalable access to the data and flexibility in approach.
 
Most people are aware that there is a big effort to add a SQL interface to Hadoop. What most haven’t realized is how far we’ve also come the other direction. For some time, Teradata has allowed C and Java processing directly against our database platforms via User Defined Functions and other similar extensions. We are now also enabling other languages such as R and Python to be executed within a Teradata context. What is possible today is so far beyond what was possible even 5 or 10 years ago.
 
How do you see the adoption of Cloud for Analytics?
 
Bill Franks: We are aggressively rolling out our own cloud offerings across our product suites. Many of our enterprise customers also configure our products as a private cloud behind their firewall. Adoption will be mixed based on the type of data and nature of work being done. 
 
Anything involving sensitive data is still typically not allowed outside a firewall. If you think back to the issue raised in a prior question of having to be able to combine data for analytics, you can’t really have some data locked behind a firewall and some data locked outside it. 
 
The real driver behind the cloud is that people want flexible, pay on demand access to analysis platforms. We have multiple ways to provide that to our clients, of which our cloud offerings are only one option. We have some other novel pricing and licensing options the help customers get access to the resources they require for analytics.
 
What are the most important data challenges posed by the Internet of Things (IoT)?
 
Bill Franks: Perhaps the biggest challenge is that the IOT has the potential to generate orders of magnitude more data than any other source in existence today.
 
So, in the world of the IOT we will test the limits of ‘big.’ At the same time, much of the data generated by the IOT will have low value in the short term and no value in the long term. One of the biggest challenges will be determining which pieces of the information generated by a given sensor actually matters to your business and for how long. 
 
In the long run, it is likely that only a small fraction of the raw data produced by the IOT will be stored beyond a few moments of immediate usage. For example, why keep the sensor readings that help navigate my car into a tight parking spot? 
 
Once I’m safely in the spot, I really don’t ever need to revisit that data again. If I hit a car in front of me, I might make an exception and keep the data so that the cause can be identified.
 
Could you mention some successful Big Data projects you have recently completed with customers?
 
Bill Franks: We are seeing a lot of very interesting analytics come about. We’ve helped health organizations discover genetic patterns associated with disease, we’ve helped manufacturers reduce cost and increase customer satisfaction by building predictive maintenance algorithms, we’ve helped cable providers identify valuable consumer viewing habits.
 
I could go on and on. A great place to see some of the examples, and even hear from some of the companies and people behind it, is at our website.
 
Bill Franks is the Chief Analytics Officer for Teradata, where he provides insight on trends in the analytics and big data space and helps clients understand how Teradata and its analytic partners can support their efforts. His focus is to translate complex analytics into terms that business users can understand and work with organizations to implement their analytics effectively. His work has spanned many industries for companies ranging from Fortune 100 companies to small non-profits. Franks also helps determine Teradata’s strategies in the areas of analytics and big data.
 
Prof. Roberto V. Zicari is editor of odbms.org, which is designed to meet the fast-growing need for resources focusing on Big Data, Analytical Data Platforms, Scalable Cloud platforms, NewSQL databases, NoSQL datastores, Object databases, Object-relational bindings, and new approaches to concurrency control. Roberto is Full Professor of Database and Information Systems at Frankfurt University. He was for over 15 years the representative of the OMG in Europe. Previously, Roberto served as associate professor at Politecnico di Milano, Italy; Visiting scientist at IBM Almaden Research Center, USA; the University of California at Berkeley, USA; Visiting professor at EPFL in Lausanne, Switzerland; the National University of Mexico City, Mexico; and the Copenhagen Business School, Denmark.
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