How Hadoop makes business analytics more intelligent

While big data analysis is used in many different industries to various effect, its use for business analytics in particular can represent problems. The first is right there in the name – business analytics is an enterprise-based initiative first and foremost, desired explicitly to turn more data into higher profits. In other sectors, like healthcare and urban development, for example, analytics users are more apt to share critical data and even insights so that they can inform medical breakthroughs or more sustainable city planning strategies. Apache Hadoop is already in use by many organizations in these sectors, and their continued contributions to both big data utilization and Hadoop programs themselves create an environment of constant evolution. This ecosystem fosters a high degree of innovation.

In business analytics, however, data sharing is a much murkier case. It's understandable that businesses are reluctant to share data with each other, as giving free information to the competition doesn't seem to be a good strategy for sustained business growth. As far as the continued development of analytics strategies are concerned, however, this reticence could prove costly, according to KM World contributor David Weinberger.

"The 'more' is not just the distributing of research but also the networking of it," he wrote. "It's great that a 'data native' now has the skills and tools to take control of the analytics process. But the real power comes when research and researchers are able to use one another's work, and to elaborate on that work in public. That's how you get a data commons that not only aggregates data but that enables researchers to bang their models together to discover weaknesses and to create sparks."

Apache Hadoop and the evolving business analytics paradigm
Weinberger argued that collaboration between businesses needs to become a more prominent component of business models. Organizations don't need to divulge the recipe to their secret sauce to their competitor, but sequestering data analytics strategies can end up creating limitations in the long run. A lack of collaborative drive can have unintended internal effects as well, according to business intelligence analyst and Information Age contributor Tom Pringle. In these environments, business users may be less likely to be trained in the full scope of analytics uses and strategies. Business intelligence and data mining should prioritize a self-service environment and universal access among an organization's end users. The Apache Hadoop platform has continued to develop with these business users in mind, and the way that the Hadoop HDFS is structured can make select data sharing easier and promotes collaborative user engagement.

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