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Maximizing the Value of Big Data

Bill Jacobs, Director, Product Marketing, Revolution Analytics

The 2013 McKinsey report “Game changers: Five opportunities for US growth and renewal” suggests that effective use of Big Data could drive $325 billion incremental annual GDP in retail and manufacturing by 2020, while cutting $285 billion in costs across the government and health care sectors.1 Similar studies suggest that Big Data can have game-changing effects across a broad variety of industries.

Worldwide, over two million statisticians, data scientists, and business analysts have turned to the open source R language to accelerate development of statistics, predictive analytics, and machine-learning applications.The R language, together with a vast array of freely available statistical and analytical algorithms, has become the fastest growing predictive-analytics and machine-learning software choice.

Companies using Teradata Databases continue to amass ever-larger data assets. When they consider using R to analyze these data assets, they often discover the limitations of the open source R language. Open source R, while popular and powerful, falls short of the data-scale, ease-of-use, and production-integration needs that arise when analyzing Big Data.

Revolution Analytics provides an R-based analytics solution that scales to meet Big Data analytics requirements. Our RRE product provides a commercially supported R platform for computational scale, ease of development, and ease of integration.

Revolution R Enterprise 7 (RRE 7) brings these capabilities to Teradata users. By running Big Data analysis“in-database,” RRE 7 provides Teradata users with data scale, computational scale, and computational efficiency unmatched in the industry.