Building a Sustainable Analytics Infrastructure for Your Big Data Efforts

A recent survey of Fortune 1000 executives showed that 37% of their companies invested over $100 million in Big Data over the past five years. Less than half of the respondents reported that their Big Data efforts were “highly successful.”

Why aren’t these companies seeing ROI on Big Data? One major reason for the discrepancy could be that many companies are bogged down in a never-ending cycle of teardown and rebuild of their analytics infrastructure.

Data analysts work hard to build data infrastructures that are robust, supportive and scalable for businesses. But it seems they’re constantly rebuilding analytics infrastructure every time they need to make an update to their implementation. This cycle costs companies a lot of time and money, and increases organizational complexity debt.

Breaking the cycle and implementing a sustainable analytics infrastructure will ultimately increase organizational efficiency and foster data analysis.

Sustainable data implementations allow companies to gain valuable insights from Big Data over longer time periods, helping them make informed business decisions without all the restructuring run-around.

Jason Thompson, co-founder of 33 Sticks, agrees. Recently, he stated:

“Companies and analysts alike need to get out of their comfort zone of building analytics implementations. At some point in time, you actually need to start making informed business decisions from the data you collect.”

Jason Thompson is an experienced digital analyst and entrepreneur whose primary focus is on encouraging organizations to think differently about their delivery of information, data insights and recommendations. He will be presenting “Zen and the Art of Sustainable Implementations” at the 2017 Analytics Summit on November 9th.

To learn more about building sustainable data infrastructures, register for the Analytics Summit to gain access to Jason Thompson’s insights. Thompson and 24 other prominent speakers will cover best practices, trends, technologies and key concerns for data-driven organizations.

Jason Thompson

Jason Thompson 


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