Seven Ways to Make Big Data an Actionable Opportunity Conventional wisdom holds that in order to really derive the benefits of investing in Big Data, organizations need to hire data scientists that typically command salaries above $100,000. That kind of investment could normally put Big Data investments out of the reach of many organizations. But […]
Seven Ways to Make Big Data an Actionable Opportunity
Conventional wisdom holds that in order to really derive the benefits of investing in Big Data, organizations need to hire data scientists that typically command salaries above $100,000.
That kind of investment could normally put Big Data investments out of the reach of many organizations. But as Big Data analytics continues to become more sophisticated, it’s clear that the dependency on data scientists is going to be sharply reduced.
Case in point is the Teradata Aster Discovery Platform, which provides a core processing engine on top of which multiple analytics engines can be deployed that allow users to automatically discover patterns in data using either Teradata Aster SQL, Teradata Aster SQL-MapReduce, or the newly developed Teradata Aster SQL-GR engine for graph analysis.
According to Manan Goel, senior director of product marketing for Teradata Aster, the Teradata Aster Discovery Platform helps fill the Big Data skills gap in multiple ways. Rather than having to build multiple stacks of systems with different file systems and data stores to process different types of analytics applications, Teradata is making it possible for organizations to leverage a single platform built on top of the Teradata Aster Seamless Network Analytic Processing (SNAP) Framework. This reduces the need to hire IT administrators to manage separate Big Data platforms.
More significantly, the Teradata Aster Discovery Platform makes it easier for analysts to access Big Data applications without the direct intervention of a data scientist. While Teradata Aster Discovery Platform doesn’t totally eliminate the need for a data scientist, it can reduce that dependency to the point where it makes more sense to contract the services of a data scientist for specific projects rather than having to hire one as a full-time employee.
The problem with hiring data scientists in today’s IT environment is that most of them wind up spending most of their time on low-level IT plumbing tasks that are required to set up Big Data applications. The Teradata Aster Discovery Platform is designed to automate much of the building and processing associated with creating Big Data analytics applications under a unified data management architecture. That not only makes Big Data more accessible to the organization, it also substantially reduces the cost of the Big Data investment.
Michael Vizard is a seasoned IT journalist, with nearly 30 years of experience writing and editing about enterprise IT issues. He is a contributor to publications including Programmableweb, IT Business Edge, CIOinsight and UBM Tech. He formerly was editorial director for Ziff-Davis Enterprise, where he launched the company’s custom content division, and has also served as editor in chief for CRN and InfoWorld. He also has held editorial positions at PC Week, Computerworld and Digital Review.
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