SAS^® and Hadoop

In this time of massive data production and proliferation, it is easy to become overwhelmed. While the increased volume, velocity and variety of big data may be new to us all, managing large amounts of data with complex analytical processes is not new to SAS. Over the years, SAS has extended advanced analytics capabilities to a variety of database and storage vendors, including Hadoop.

SAS' support for Hadoop is centered on a singular goal: helping you know more – faster – so you can make better decisions. Beyond accessing this tidal wave of data, SAS products and services create seamless and transparent access to more Hadoop capabilities such as the Pig and Hive languages and the MapReduce framework. SAS provides the framework for a richer visual and interactive Hadoop experience, making it easier to gain insights and discover trends. It is all part of a larger SAS strategy to manage the entire analytics life cycle, from data preparation and data exploration, to modeling and deployment.

How SAS^® Can Help

With Hadoop and SAS you can:

• Easily access and use big data stored in Hadoop. SAS/ACCESS® software provides seamless and transparent data access to Hadoop (via HiveQL). Users can access Hive tables as if they were native SAS data sets, and then apply text mining and predictive analytics to data stored in Hadoop to gain and share new insights.
• Maximize Hadoop's distributed processing capability. SAS helps execute Hadoop functionality with Base SAS by enabling MapReduce programming, scripting support and the execution of HDFS commands from within the SAS environment. This complements the capability provided by SAS/ACCESS by extending support for Pig, MapReduce and HDFS commands.
• Effectively manage Hadoop using SAS Information Management. SAS Data Management Advanced can help users quickly get value from data residing in Hadoop with existing familiar SAS technology. It provides an intuitive, graphic interface to move data from and to Hadoop. With SAS metadata, data lineage and security, customers can continue to integrate their data management and analytic investments with Hadoop.
• Quickly visualize your data stored in Hadoop, discover new patterns and publish reports. SAS Visual Analytics is an in-memory solution for exploring data very quickly. It enables you to identify opportunities for further analysis and convey visual results via Web reports or mobile devices.
• Leverage Hadoop for big data analytics. SAS High-Performance Analytics Server is an in-memory solution that allows you to develop analytical models using all data, not just a subset, to produce more accurate and timely insights. You can run frequent modeling iterations and use sophisticated analytics to get answers to questions you never thought of or had time to ask.

How SAS^® Is Different

• Comprehensive analytic support for Hadoop. SAS/ACCESS not only retrieves big data stored in Hadoop's distributed file system (HDFS), it also allows you to incorporate and use other Hadoop capabilities such as the Pig and Hive languages and the MapReduce framework.
• Flexible architecture. Because SAS is focused on analytics, we offer a flexible approach to hardware or database vendors by working with users to deploy the correct mix of technologies including the ability to deploy Hadoop with other data warehouse technologies.
• Complete lifecycle support. SAS supports the entire analytics life cycle, from data preparation and exploration, model development, and production deployment and monitoring. This approach provides seamless closed-loop management for the entire data to decision cycle.