Author Archive

Brahma Tangella

Brahma Tangella

Sr. Manager, Service Strategy, Dell IT

Framing the Data Science Proof of Concept

Whether companies refer to results, outcomes, ROI, or case studies, Big Data and data science are finally moving beyond the hype and proving to deliver dividends over time. Several new Big Data technologies and predictive tools have been launched to meet the growing demand within business and technology groups to harness the constant growth of both structured and unstructured data within and outside of the enterprise. But such technologies and tools won’t be effective unless you define the problem to be addressed.

Most data science initiatives start with a proof of concept (PoC) or in some cases with a proof of value (PoV) if the foundational concept is clearly established. Developing a pipeline of PoC’s can be extremely helpful through working sessions with data scientists, business subject matter experts (SME’s), data experts, and leaders. Following this, prioritize PoCs by stack-ranking each of them based on business value and ease of implementation which factors in availability of data, granularity, and quality.


Why a Data Lake? Keeping Up with the Digital Universe

With the digital universe expected to swell to 44 zettabytes of data by 2020, today’s enterprises need a central data repository that can process increasing volumes of all types of data faster to let business users make better, real-time decisions. In short they need a stronger backbone; they need the data lake!

Not only do traditional databases constrain real-time and shared data analytics due to their siloed nature, they also lack the technology to accommodate the skyrocketing level and types of data being created at an increasing rate. After all, according to IDC research, the growing number of smart devices that analyze everything from home heating systems to consumer information will mean that within four years there will be some 7 billion connected people using an estimated 30 billion devices.


The Journey Toward a Predictive Enterprise

The 2014 EMC Digital Universe Study, with research and analysis by IDC, predicts that by 2020 the digital universe will contain nearly as many digital bits as there are stars in the universe.

According to the study, digital growth “is doubling in size every two years and by 2020, the digital universe—the data we create and copy annually—will reach 44 zettabytes, or 44 trillion gigabytes.”

As companies brace for this data tsunami, they are challenged to identify the next business opportunity, improve risk management, customer engagement and sustainability. They will need to become “predictive enterprises” which leverage their data to define their future focus and how to get there. Sifting massive amounts of data to find relevant insights for business will be a continuous process, constantly evolving and adapting to business climate. IT departments need to have a robust framework to manage their organizations’ ambitions and goals.


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