Big data and Hadoop: it’s about the community
What Apache Hadoop offers its business users isn't just an enterprise outpost in the vast landscape of big data – it presents the opportunity to form a community. From the start, Hadoop has been a community-driven entity, a collaborative platform for innovators to develop and articulate new strategies in a supportive environment. Optimized Hadoop is a reciprocal relationship between data and analysts, who continuously build on an array of researched observations to produce a panoply of actionable practices. As more organizations target stronger collaborative initiatives with service partners and build relationships with employees and consumers, a synergetic business ethos will continue to be an asset, spurring further growth. Apache Hadoop is geared toward these forward-thinking businesses, and its adoption, like its optimal use, can be a collaborative effort.
Building colonies with Hadoop architecture
Using Hadoop datanodes as the cornerstones of big data analysis strategies ensures that information-driven insights will be structured. The data itself doesn't have to be – having structured and unstructured information from which to draw insights can provide a wide scope of perception – but it's useful to have a framework in place so that insights don't end up being amorphous. ClickZ contributor Andrew Edwards highlighted the rationale for analytics adoption by marketing professionals and wrote that it makes their initiatives more open.
"Marketers aren't typically wired for data," Edwards wrote. "Measurement has landed on them and they have embraced it; and some of the most agile and forward-thinking have made big wins with data-driven decision-making."
Every business will have employees in areas that aren't traditionally big data-based, so it behooves them to promote a community of Apache Hadoop users. That way, data mining isn't a task for a few sequestered employees. Instead, it encourages users to converge their analysis and fosters conversation.
Use Hadoop tutorials to make big data evolve, not go in circles
Wired contributor Chris Taylor recently argued that big data might be in Gartner's 'trough of disillusionment' for many of its business users, if they go aimlessly in circles with their data instead of using it to scale to new heights. He wrote that many companies that are experimenting with big data are not seeing the results they had hoped for. One of the ways to bridge the gap between trials and success is to go all in. By employing Hadoop tutorials to inform employees about the many application options, organizations can create a community of reliable, skilled users that understand how to strategize data for optimal insight.
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