Продвинутая аналитика Oracle для Больших Данных4 апреля 2012
"For example, traditional data such as quarterly sales figures tell the story of who is buying a product,” says William Hardie, vice president, Oracle Database product marketing. “But by analyzing comments on social media such as Twitter and Facebook, and tracking activities on their own Website, companies can also do sentiment analysis to discover who isn’t pulling the purchase trigger, and why. This is not possible to do with transactional data alone.”
In an integrated advanced analytics framework, companies can use Hadoop to analyze and summarize big data, extract relevant summaries, and move that information to their Oracle data warehouse. Doing so offers several advantages, says Hardie. “It provides customers with an environment that continues to utilize their investment in skill and resources, and certainly provides better security. Most importantly, enterprises can run powerful analytics within the database itself, using tools such as Oracle Advanced Analytics.”
Comprising Oracle R Enterprise and Oracle Data Mining, Oracle Advanced Analytics extends the database into a comprehensive platform for real-time analytic applications that deliver insight into key business subjects, such as churn prediction, product recommendations, and fraud alerting.
In-database analytics provides several key benefits.
Performance — With analytical operations performed in the database, Oracle R Enterprise delivers enterprise-class performance for users of the R statistical programming language, delivering performance up to 100 times faster.
Scalability — Customers can easily scale analytics as the data volume increases by bringing the algorithms into the database. Users are no longer constrained by the memory requirements of a laptop, so the scale of data that can be analyzed increases by orders of magnitude.
Security — Oracle Advanced Analytics provides controlled and auditable access to production data in Oracle Database 11g, accelerating data analyst productivity while maintaining data security. Moreover, users avoid the physical security risks inherent in extracting and downloading data to a mobile device.