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Don't get carried away by Hadoop's 'gee whiz' factor

Enterprises should take business-centric view when deploying technology, Forrester cautions

October 11, 2011 05:24 PM ET

Computerworld - Companies should take a pragmatic approach to implementing Hadoop for their "big data" requirements, a new report released Tuesday by analyst firm Forrester Research urges.

The guidance is based on the experiences of some early adopters of Hadoop, including Yahoo, AOL, Mozilla and Klout. It cautions companies against getting carried away by the hype surrounding the technology and advocates a staged Hadoop deployment driven purely by business goals.

Avoid Hadoop "science projects" that lack business value, the report noted. "Be careful not to mistake Hadoop's technological gee whiz factor with a genuine business case that delivers real business value."

Hadoop is an open source technology designed to help companies manage and process extremely large volumes of data. Much of Hadoop's growing popularity lies in its ability to break up large data sets into smaller data blocks that are then distributed across a cluster of commodity hardware for faster processing.

Early adopters have been using Hadoop to store and analyze petabytes of unstructured data that other enterprise data warehouse technologies have not been able to handle as easily. The fact that it is an open source technology with growing vendor support has greatly contributed to its growing allure within enterprises.

"Hadoop is the Linux of enterprise data warehouses," said James Kobielus, a Forrester analyst and author of the report. "It is being adopted and forked and tweaked and optimized," in much the same way that Linux was in the early days, he said.

Hadoop holds significant promise for enterprises, especially in cloud-based environments Kobielus said. "It was architected from the get go to be more than a data warehouse. It was architected from the start to handle huge volumes of complex, unstructured content and not just structured, relational data like conventional relational database technologies are, he said.

Even so, the technology is still a work in progress, he said. Hadoop's relative newness, its immaturity, lack of standards, relative dearth of commercial offerings and skills availability, all pose big challenges for enterprises, he said.

The Forrester report outlines a set of best practices that Kobielus said companies can use to guide their Hadoop deployments.

One recommendation is for companies to align their Hadoop initiatives with a clear big data business strategy, Kobielus said. IT managers need to identify specific business situations where Hadoop's capabilities can deliver clear benefits. Yahoo's business case for using Hadoop for instance, has always been to support analytics on very large data sets for ad placement purposes, Kobielus said.

Companies need to have similar specific goals when implementing Hadoop. In most cases, it is best to start with projects that have near-term benefits and easily tangible impact. Before deploying Hadoop, it is also best to see if other enterprise data warehouse technologies can handle the requirements.



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