Big Data Analytics

Posted: 21/07/2013 in Web Tech

Big Data Analytics

Between now and 2020, the sheer volume of digital information is predicted to increase to 35 trillion gigabytes – much of it coming from new sources including blogs, social media, internet search, and sensor networks.

Teradata can help you manage this onslaught with big data analytics for structured big data within an integrated relational database– and now Teradata’s Aster Data Analytic Platform can help you deal with the emerging big data that typically has unknown relationships, includes non-relational data types. Together, these two powerful technologies provide greater insight than ever for smarter, faster, decisions.

Teradata’s Aster Data Analytic Platform powers next-generation big data analytic applications with a massively parallel processing (MPP) analytics engine that stores and processes big data analytics together with data. As a result, it delivers breakthrough performance and scalability to give you a competitive edge in these critical areas:

  • Enable new analytics: Big data analytics framework with pattern and graph analysis that are hard to define and execute in SQL enable valuable new applications – including digital marketing optimization, fraud detection and prevention, and social network and relationship analysis.
  • Accelerate analytics development: Unique analytics architecture combined with pre-built library of analytic modules, visual development environment, and local testing capability simplify and streamline analytic development. Supports a variety of languages are supported – including C, C++, C#, Java, Python, Perl, and R – to simplify development and embedding of rich analytics in the MPP data store.
  • High-performance and elastic scalability: Patented high parallelism and massive scalability for complex analytics that enable iterative, on-the-fly data exploration and analysis to rapidly uncover new and changing patterns in data.
  • Cost-effective big data analytics: Uses commodity hardware to provide lower cost to scale than alternative approaches.

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