Drill to Detail Ep.13 ‘Apache Drill, MapR + Bringing Data Discovery to Hadoop & NoSQL’ with Special Guest Neeraja Rentachintala

Mark Rittman is joined by MapR's Neeraja Rentachintala to talk about Apache Drill, Apache Arrow, MapR-DB, extending Hadoop-based data discovery to self-describing file formats and NoSQL databases, and why MapR backed Drill as their strategic SQL-on-Hadoop platform technology.

Drill to Detail Ep.10 'Oracle's Big Data Reboot, and Data Storytelling' With Special Guest Stewart Bryson

Mark Rittman is joined once more by Stewart Bryson, talking about Oracle's recent reboot of it's cloud big data platform at Oracle Openworld 2016, thoughts on DataFlowML and comparisons with Google's Cloud DataFlow and Amazon Kinesis, and data storytelling with Oracle Data Visualisation Desktop 2.0

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Drill to Detail Ep.9 'Streamsets, Data-in-Motion and Data Drift' with Special Guest Pat Patterson

Mark Rittman is joined by StreamSets' Pat Patterson, talking about data in motion and doing it at scale, the story behind StreamSets and the problem of data drift, and the challenges involved in managing dataflows at scale as a continuous operation.

Drill to Detail Ep.8 'Self-Service BI, Data Prep & Big Data Vendor Strategy' with Special Guest Jen Underwood

Mark Rittman is joined by Jen Underwood to discuss the aftermath of the Gartner BI&A Magic Quadrant 2016 and the rise of self-service, Mode-2 analytics; innovation in predictive analytics and data preparation tools, and how the big data cloud vendors are differentiating themselves (or not).

Drill to Detail Ep.4 'Reference Architectures Revisited' with Special Guest Andrew Bond

In this episode I'm joined by Andrew Bond from Oracle's Enterprise Architecture team, to look back at the Oracle Information Management & Big Data Reference Architecture we collaborated on back in 2014 and ask ourselves what's changed, what parts of the architecture had the most impact and adoption in the market, and what are the challenges Andrew and his team see customers trying to overcome when deploying big data applications in the enterprise.