(52b) Big Data

Today the term big data draws a lot of attention, but behind the hype there's a simple story. For decades, companies have been making business decisions based on transactional data stored in relational databases. Beyond that critical data, however, is a potential treasure trove of non-traditional, less structured data: weblogs, social media, email, sensors, and photographs that can be mined for useful information. Decreases in the cost of both storage and compute power have made it feasible to collect this data - which would have been thrown away only a few years ago. As a result, more and more companies are looking to include non-traditional yet potentially very valuable data with their traditional enterprise data in their business intelligence analysis.

To derive real business value from big data, you need the right tools to capture and organize a wide variety of data types from different sources, and to be able to easily analyze it within the context of all your enterprise data. Oracle offers the broadest and most integrated portfolio of products to help you acquire and organize these diverse data types and analyze them alongside your existing data to find new insights and capitalize on hidden relationships.

SQL is the natural language for querying data, but data increasingly lives in many places: HDFS, HBase, relational databases, and NoSQL stores. As the options for data management explode, developers, applications, and tools begin to demand SQL everywhere.

In this session, we’ll present a SQL-based strategy for integrating Hadoop, NoSQL technologies, and relational databases. Our approach illustrates how to get the best out of each platform, and enables integration with no changes to existing applications. Along the way, we’ll dive deep into the architecture of Big Data SQL, which can access all of these platforms in a single query through query franchising