Where does Hadoop fit into an effective data strategy?

.@philsimon on the convergence between tools such as Hadoop and strategy.

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SAS Grid Manager for Hadoop nicely tied into YARN (Part 2)

In Part 1 of this series, Cheryl Doninger described how SAS Grid Manager can extend your investment in the Hadoop infrastructure. In this post, we’ll take a look at how Cloudera Manager helps Hadoop administrators meet competing service level agreements (SLAs). Cloudera Manager lets Hadoop admins set up queues to […]

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SAS Grid Manager for Hadoop nicely tied into YARN (Part 1)

If you'd like to extend your investment in the Hadoop infrastructure, SAS Grid Manager for Hadoop can help by enabling you to colocate SAS Grid jobs on your Hadoop data nodes. It works because SAS Grid Manager for Hadoop – which is Cloudera certified – is integrated with the native […]

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Self-service data preparation transforms data professionals into data rock stars

When my band first started and was in need of a sound system, we bought a pair of cheap yet indestructible Peavey speakers, some Radio Shack microphones and a power mixer. The result? We sounded awful and often split our ear drums from high-pitched feedback and raw, untrained vocals. It took us years […]

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Beyond the boundaries of structured data: Part two

How many times have you gone onto a website, put a few things in a shopping cart, and then exited the Internet? I do it all the time. Sometimes when I log on to that site during my next visit, those same items are still in my cart – ready for purchase. I find […]

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Will Hadoop replace the data warehouse?

Twenty-five years ago (when I was 12 years old), we realized that data, across the corporation, was not integrated. Nor did our data let us predict the future by looking at the past. So we started creating these stores of historical data soon to be called “data warehouse.” Here are […]

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Using big data techniques to increase database performance

Many people perceive big data management technologies as a “cure-all” for their analytics needs. But I would be surprised if any organization that has invested in developing a conventional data warehouse – even on a small scale – would completely rip that data warehouse out and immediately replace it with an NoSQL […]

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Fields and dreams of data warehousing

“Field of dreams warehouse”– a historic phrase I used in the early days of data warehouse development. It describes the frenzy of activity that took place to create enterprise data infrastructure, before the business rationale for the data use was even understood. Those were the early days. In some ways […]

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Managing big data, Part 1: Technical questions

With Big Data, there are far more technical questions than answers.






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Big "quality" data

Data quality issues don’t go away just because you have more data. Big data is sometimes considered exempt from the requirement to be integrated, cleansed and standardized. Unfortunately, chances are that the more data you have, the worse its quality will become. tags: big data, data management, data quality, hadoop

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