Six Details Your Big Data Provider Won't Tell You

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It May Take Years to Realize Value

Building and maintaining Big Data infrastructure is hard work. It takes specialized expertise, investments in hardware and software, and a team of consultants to deploy – not to mention trainings on how to use it. And only once the system is installed and teams are trained can organizations start to dig into their data. It's not uncommon for organizations to only start seeing a return on investment as much as 24 months after the project was initiated.

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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