BIG DATA. SAS Tools
暫譯: 大數據：SAS 工具

People and organizations have attempted to tackle the problem to analyze massive volumes of data from many different angles. SAS uses multicore technologies to deliver increased processing capabilities through high-performance, in-database and in-memory analytics resulting in greater insights more quickly from big data and streaming data. Important foundational updates allow you to deploy SAS in the manner that best suits your needs. The angle that is currently leading the pack in terms of popularity for massive data analysis is an open source project called Hadoop. Hadoop is also shipped as part of SAS tools. SAS incorporated Hadoop into their applications (SAS Base, SAS Data Integration, Sas Enterpris Guide, SAS Enterprise Miner, …). Same SAS aplications works in-memory on Hadoop (In-memory Statistics, SAS Visual Analytics and SAS Visual Statistics). SAS support for big data implementations, including Hadoop, centers on a singular goal – helping you know more, faster, so you can make better decisions. Regardless of how you use the technology, every project should go through an iterative and continuous improvement cycle. And that includes data preparation and management, data visualization and exploration, model development, model deployment and monitoring. Also throught SAS and Hadoop is possible work in all steps of Analytical Process: Identify/formulate Problem, Data Preparation, Data Exploration, Transform and select, Buil Model, Validate model, Deploy Model and Evaluate/Monitor Results. This book presents the work possibilities that SAS offers in the modern sector of big data. The most important tools of SAS are presented for processing and analyzing large volumes of data in an orderly manner. In turn, these tools allow also extract the knowledge contained in the data.