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Big Data Cloud August 11th Meetup – Hadoop powered Engines; 100+ Attendees; Corporate Sponsorships & Giveaways

BigDataCloud’s theme of “Hadoop Powered Predictions & Recommendations Engines” attracted over 100 people to the meetup last night, sponsored by LexisNexis & ThirdEyeCloud. The attendees thronged the LexisNexis’s booth about its newly debuted HPCC Systems & got an understanding of how its Hadoop alternative can actually solve “Big Data” challenges in enterprises. The attendees also had a chance to “meet & gr ...

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Implementing Hadoop MapReduce based solutions at your enterprise?

Hadoop technologies have started to mature and many of us are now tasked at implementing Hadoop MapReduce based solutions at our respective organizations. From our own practical experiences, we can tell that the going is not going to be as smooth as you might have expected. That’s what peaked our interest in this webinar by Platform Computing: Top Issues IT faces with Hadoop MapReduce This webinar claims th ...

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Byte Sized Hadoop classes – for as low as $125/class!

Third Eye is launching "Byte Sized Hadoop" classes – for as low as $125/class! These Hadoop classes will be offered byte-sized, 3 hours each, after work hours & conducted by industry veterans with a practical "from-the-trenches" approach. BigDataCloud meetup attendees have heard & met the instructors individually: Paul Baclace - presented "Optimizing bursty Hadoop analysis demands for big data using A ...

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Moving an Elephant: Large Scale Hadoop Data Migration at Facebook

Users share billions of pieces of content daily on Facebook, and it’s the data infrastructure team's job to analyze that data so we can present it to those users and their friends in the quickest and most relevant manner. This requires a lot of infrastructure and supporting data, so much so that we need to move that data periodically to ever larger data centers. Just last month, the data infrastructure team ...

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Microsoft Research Releases Another Hadoop Alternative for Azure

Today Microsoft Research announced the availability of a free technology preview of Project Daytona MapReduce Runtime for Windows Azure. Using a set of tools for working with big data based on Google's MapReduce paper, it provides an alternative to Apache Hadoop. Daytona was created by the eXtreme Computing Group at Microsoft Research. It's designed to help scientists take advantage of Azure for working wit ...

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It’s The API, Stupid! (Part 3)

Last week was definitely a busy one in the MapReduce world! At the annual Hadoop Summit, Yahoo! officially announced the spinoff of HortonWorks (possibly the worst kept secret in the Hadoop community), and Cloudera and MapR both announced new distributions. With even more fragmentation coming to the Hadoop community, what better time to wrap up this series on the state of MapReduce. In my previous two posts ...

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Informatica Adds Support for ‘big Data,’ Hadoop

Informatica is joining the growing ranks of vendors moving to support Hadoop, the open-source framework for large-scale or "big data" processing, the company announced Monday. The 9.1 version of Informatica's platform features a connector to the Hadoop file system (HDFS), allowing customers to move data in and out of Hadoop clusters. While the Hadoop project has its roots in Web companies, having been led b ...

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Why MapR Is Right to Give Back to Apache Hadoop

Big data startup MapR is now an official corporate contributor to the Apache Hadoop project, a somewhat interesting turn of affairs given its corporate mission to lure users away from Apache’s Hadoop Distributed File System. Although this might seem like an odd partnership — even more so now after EMC announced MapR as the storage foundation for its Apache Hadoop alternative — it demonstrates the type of co ...

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BIG DATA CLOUD RECOMMENDS – The Evolving Role of the Enterprise Data Warehouse in the Era of Big Data Analytics

The Evolving Role of the Enterprise Data Warehouse in the Era of Big Data Analytics A white paper by Dr. Ralph Kimball The enterprise data warehouse (EDW) community has entered a new realm of meeting new and growing business requirements in the era of “Big Data.” A few of the common challenges include: extreme integration, semi- and un-structured data sources, petabytes of behavioral and image data accessed ...

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Hadoop Orchestration

Most data processing tasks with Hadoop require multiple Hadoop jobs with dependencies between them. The dependency arises out of the need for one job to use the output for another job. The dependency between Hadoop jobs can be expressed as a directed acyclic graph (DAG), where each node represents a Hadoop job. DAG is useful for modelling relationship between entities that have partial ordering. The depende ...

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