Six Details Your Big Data Provider Won't Tell You

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Technology and Needs Change Rapidly

There is a wide range of Big Data technologies, and innovation in this sector is happening fast. There's Hadoop and Hive and Spark and YARN and on and on — who knows what new, must-have technology will emerge next year. When you started your Big Data initiative, batch analytics may have been adequate, but you may discover later that you need more real-time capabilities. Moreover, once organizations start diving into their data, they may find different use cases that drive more value. With an on-premises Big Data system, new software technologies can require integration with existing systems, fine-tuning to get stable and working correctly, as well as new expertise to install and maintain it.

In a report released in January, Capgemini reported that, while 60 percent of executives believed Big Data will disrupt their industry within the next three years, only 13 percent of organizations in the survey have achieved full-scale production of their Big Data implementations. Moreover, the research found that only 27 percent of respondents described their Big Data initiatives as successful.

This is not a surprise to Ashish Thusoo, CEO and founder of the Big Data-as-a-service company Qubole. As one of the original creators of Facebook's data infrastructure and authors of Apache Hive, he's intimately familiar with the challenges of working with Hadoop, Spark, Hive, Presto and other related technologies. Building out an on-premises Big Data infrastructure takes significant time, investment and technical expertise and brings with it a lot of risk to boot. That's why Thusoo believes Big Data belongs in the cloud.

For organizations currently considering their own Big Data deployments, here are six things Big Data software providers won't tell you about on-premises solutions.

 

Related Topics : Vulnerabilities and Patches, Resellers, Broadcom, Broadband Services, Supercomputing

 
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