Big data and Hadoop applications empower consumers

Big data analytics has quickly gone from a niche service utilized by only the most heavily resourced corporations to an application widely deployed by organizations spanning numerous industries. Much of that growth can be attributed to both the evident benefits provided by the technology and the emergence of the open source Apache Hadoop platform. This advancement has allowed many companies to create their own customized analytics projects without the need for costly infrastructure changes. Adoption rates of big data and Hadoop applications have soared in recent years, with more enterprises looking to leverage these tools to gain greater insight into various aspects of their sectors, including consumer trends and potential market shifts looming on the horizon.

XL Marketing CEO David Steinberg argued in a recent Wired post that access to these insights would result in greater levels of efficiency and productivity across the board, as businesses will launch fewer products that engender apathetic levels of consumer interest. With multitudinous sources of information to glean consumer insights, companies can ensure that their products are tailored to meet the demands of their customer base.

“The paradigm has shifted much more heavily in favor of consumers telling companies what they want, not the other way around,” Steinberg wrote. “Armed with this knowledge, companies have a much clearer picture of who could be a potential customer and can therefore focus their time and energy to reaching those prospective customers and not trying to figure out who they are thereby making businesses far more productive in customer acquisition. This cycle continues in perpetuity so that brands are constantly gathering research, processing that research, and taking action on the findings.”

Optimizing big data storage
A primary benefit of the collecting consumer insights is the ability to gain useful information in real time and then quickly modify services or products to meet changes in public opinion. The proliferation of social media networks has greatly assisted this pursuit, as powerful analytics processes can comb through numerous websites, gathering useful and actionable information.

According to Enterprise Storage Forum, getting the most out of real-time social media updates will require a storage solution that provides low-latency access to massive quantities of information. Hadoop clusters can accommodate those needs, as they provide substantial data storage capacity and accessibility. In addition, the Hadoop platform produces copies of processed data and distributes them across the node architecture. This means that if one were to fail, users could continue their analytics projects with their backup data without facing potentially costly downtime.

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