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Introduction to Spring Data

Mark Pollack provides a guided tour plus demos of the Spring Data feature set.

Mark Pollack
on Mar 07, 2013

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01:18:22
Making Hadoop Real Time with Scala & GridGain

Nikita Ivanov shows adding real-time capabilities to Hadoop through a demo application streaming word counting on a 2-nodes cluster.

Nikita Ivanov
on Mar 04, 2013

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37:29
Apache Cassandra Anti Patterns

Matthew Dennis covers the most common mistakes made with Cassandra that he has noticed being made both in deployment and code.

Matthew Dennis
on Feb 22, 2013

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23:45
How to Build Big Data Pipelines for Hadoop Using OSS

Costin Leau discusses Big Data, current available tools for dealing with it, and how Spring can be used to create Big Data pipelines.

Costin Leau
on Feb 08, 2013

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01:11:51
F# Big Data Scripting

Matthew Moloney shares some of the F# tools built at Microsoft Research for dealing with Big Data.

Matthew Moloney
on Jan 18, 2013

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01:00:56
The Evolving Panorama of Data

Rebecca Parsons proposes taking a different look at data, using different approaches and tools, then looks at some of the ways social data is used these days.

Rebecca Parsons
on Jan 17, 2013

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40:46
Scaling Scalability: Evolving Twitter Analytics

Dmitriy Ryaboy shares some of the lessons learned scaling Twitter’s analytics infrastructure: Data loves a schema, Make data sources discoverable, and Make costs visible.

Dmitriy Ryaboy
on Jan 13, 2013

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45:19
Lean Data Architecture: Minimize Investment, Maximize Value

Manvir Singh Grewal and Brandon Byars propose a business intelligence workflow along with Lean principles and practices for implementing a data warehouse and reporting capability.

Manvir Singh Grewal Brandon Byars
on Jan 04, 2013

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53:59
Storm: Distributed and Fault-Tolerant Real-time Computation

Nathan Marz introduces Twitter Storm, outlining its architecture and use cases, and takes a look at future features to be made available.

Nathan Marz
on Jan 04, 2013

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51:48
Extending the Enterprise Data Warehouse with Hadoop

Rob Lancaster explains the steps made by Orbitz in order to bridge the gap between their data in the data warehouse and the data in Hadoop.

Rob Lancaster
on Dec 27, 2012

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47:25
Big Data Problems in Monitoring at eBay

Bhaven Avalani and Yuri Finklestein discuss 4 aspects encountered at eBay when dealing with monitoring data: reduction of data entropy, robust data distribution, metric extraction, efficient storage.

Bhaven Avalani Yuri Finklestein
on Dec 21, 2012

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50:16
100% Big Data, 0% Hadoop, 0% Java

Pavlo Baron presents a big data case, a solution and the tools for collecting, mining and storing large amounts of data without using Hadoop or Java.

Pavlo Baron
on Dec 20, 2012

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41:03