SAS Hadoop

SAS (Statistical Analysis System) is a well-known software suite used for advanced analytics, business intelligence, and data management. SAS offers several products and solutions that integrate with Hadoop to enable big data analytics and data processing. Here are some key aspects of SAS integration with Hadoop:

1. SAS Data Connector for Hadoop: SAS provides a data connector for Hadoop that allows you to access and process data stored in Hadoop Distributed File System (HDFS) and Hadoop ecosystem components like Hive and HBase. This connector enables you to read, write, and analyze large volumes of data without having to move it out of Hadoop.

2. SAS Viya: SAS Viya is a cloud-native, open analytics platform that seamlessly integrates with Hadoop and other data sources. It offers a wide range of analytics capabilities, including machine learning, deep learning, and text analytics, and allows you to leverage Hadoop’s distributed processing power for large-scale data analytics.

3. SAS In-Database Processing: SAS provides in-database processing capabilities for Hadoop. This means that SAS analytics can be pushed down to the Hadoop cluster, where data is processed in parallel. This reduces data movement and speeds up analytics.

4. SAS Data Integration: SAS Data Integration tools enable you to extract, transform, and load (ETL) data from Hadoop and other sources into SAS for analytics. This is particularly useful for data preparation and data quality tasks.

5. SAS Visual Analytics: SAS Visual Analytics is a data visualization and exploration tool that can connect to Hadoop data sources. It allows users to create interactive dashboards and reports based on Hadoop data.

6. SAS Event Stream Processing for Hadoop: This solution enables real-time analytics on streaming data from Hadoop and other sources. It can be used for applications such as fraud detection, IoT analytics, and real-time monitoring.

7. SAS Grid Manager for Hadoop: SAS Grid Manager can be integrated with Hadoop clusters to provide workload management, resource optimization, and parallel processing capabilities. This ensures efficient utilization of Hadoop resources for SAS analytics.

8. SAS Analytics for IoT: SAS offers analytics solutions for the Internet of Things (IoT), which can integrate with Hadoop for processing and analyzing data from IoT devices and sensors.

9. SAS Hadoop Data Connector for Teradata: This connector allows data to be moved seamlessly between Hadoop and Teradata systems, enabling data sharing and analytics across both platforms.

10. SAS Education and Training: SAS provides training and certification programs to help individuals and organizations build expertise in using SAS analytics with Hadoop and big data technologies.