Talking Data

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Looking at NoSQL and big data analytics challenges

This episode of the Talking Data podcast looks at obstacles to NoSQL, as well as big data analytics challenges that software architects confront with Hadoop.

Modern NoSQL databases were forged by brilliant and hard-driving software teams within Web-era legends, such as Google, Facebook and DoubleClick. The Hadoop framework sprang from the same well, as teams found conventional SQL relational databases were falling short when their operations scaled up drastically.

This edition of the Talking Data podcast looks at the obstacles that NoSQL technology faces as it tries to go mainstream, as well as the big data analytics challenges software architects confront when NoSQL, Hadoop and other new tools change the standard ways of development.

First, the podcast covers trends from the NoSQL Now 2015 conference. Attendees at this event in San Jose, Calif., pointed to issues of SQL support, durability and skills as necessary to make NoSQL a real player in the enterprise. Clearly, NoSQL will need to retain the bits that made it a favorable alternative to SQL in the first place, but some of the data management traits that tamed SQL may need to be included before NoSQL finds mainstream adoption.

But more than NoSQL was on the agenda at the NoSQL Now conference. An associated conference looked at "smart data," which is an off-shoot of analytics comprising advanced technology elements, such as learning systems, knowledge graphs and semantic data lakes.

Second on the podcast agenda is the topic of big data analytics challenges, as seen from an architectural perspective. Central to this discussion is an appearance by consultant Mark Madsen, who recently addressed a chapter meeting of TDWI in Boston. Madsen said the new models of analytics break up the commercial data warehouses and databases as we know them into interchangeable components.

This is a different model of processing, he noted. And it requires changes in mind-sets among data practitioners.

"It leads you to very different architectural decisions," Madsen said. "The moment you introduce these kinds of capabilities, you introduce change. Suddenly, you have to start thinking again."

Madsen tells SearchDataManagement reporter Jack Vaughan that the new model requires some rethinking of established data truths. Join Vaughan and his SearchBusinessAnalytics colleague, Ed Burns, in this edition of Talking Data.

Next Steps

Taking a deeper dive into big data analytics and NoSQL challenges

What more does Mark Madsen have to say on data architecture?

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This was last published in September 2015

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