Pain Point of Hadoop

Hadoop is everywhere. For better or worse, it has become synonymous with big data. In just a few years it has gone from a fringe technology to the de facto standard. If you want to learn what data scientists and designers are thinking about Big Data, there’s probably no much better place than at the O’Reilly Strata conference, where the big thinkers tend to congregate. The outcomes of a survey performed by Dimensional Research and sponsored by RainStor are informing, revealing simply how difficult working with Hadoop can be, even for professionals in the field.

Roughly 88 % of individuals checked at the conference say they are experiencing challenges with Hadoop, a few of the leading reasons consist of; lack of real-time response and needs manual coding which results in longer time to manufacturing. “Individuals are delighted about Hadoop but even the smartest individuals in this field are still figuring it out,” says Diane Hagglund, a senior research analyst with Dimensional Study. Check out how Ford is explore Hadoop. Substantial training in order to roll-out Hadoop contributes to the expense of deployment and finding and hiring people with the ideal abilities poses an even higher difficulty. Companies are not yet seeing quick arise from their Big Data jobs, and more notably some still struggle with exactly what the business wants and the problems they are trying to address. Business users need to focus on a clear meaning of the trouble, up front, which will take the technology requirements as opposed to simply buying a Hadoop cluster, tossing some technical resources at it to see what’s possible. Attending the GigaOM Structure: Data conference in New york city this previous week, we heard very comparable comments. The majority of attendees are definitely dealing with Hadoop however a real ROI from a business viewpoint has yet to be realized much less a full understanding of how the Hadoop environment will co-exist together with other enterprise data management and analytics platforms. It often feels as though data scientists have to figure out what’s possible with Hadoop-based technologies before totally including business user and investing more heavily.

When it concerns data volumes, however, most business are not yet discussing petabyte-scale– a minimum of not yet. Less than half of Hadoop projects in production handle more than 500 TB of data, according to the study. “This confirms that lots of are still in the pilot phase, and at that point, it’s to be anticipated that you would handle a lower data volume,” says Hagglund.

On a favorable note, the fact that 24 % of participants reported having a project with Hadoop in production is an excellent sign in the still nascent “market” of Hadoop-based environments, Hagglund states. Business are selecting Hadoop because of the belief that open source is a lot more cost effective. Majority of participant’s state that the main factor for using Hadoop is for low cost scale, followed by better evaluation of wider data sets and unique performance.

Hadoop is still a young technology– it’s clear that lots of organizations need even more resources, competence, solutions and tools to relieve the execution difficulties. Each week we see brand-new market entrants, which are accelerating the rate of Hadoop adoption. In fact, different verticals are including their own unique set of devices that satisfy demands such as integrated security and regulatory compliance capabilities. I think the stage of Hadoop-experimentation is drawing to a close, now we’re going into a phase of fast adoption and even a little beyond the early adopter phase, because companies are producing finest practices, looking for standardization and ease-of-use so that users can successfully obtain understandings at a quicker speed.
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