Load your data into or out of Hadoop and data lakes. Prep it so it's ready for reports, visualizations or advanced analytics – all inside the data lakes. And do it all yourself, quickly and easily.
Intuitive user interface
Makes it easy to access, transform and manage data stored in Hadoop or data lakes with a web-based interface that reduces training requirements.
Purpose-built to load data to/from Hadoop
Built from the ground up to manage big data on Hadoop or in data lakes; not repurposed from existing IT-focused tools.
Chaining and scheduling directives
Lets you group multiple directives to run simultaneously or one after the other. Schedule and automate directives using the exposed Public API.
Collaboration and security
Enables you to share and secure directives. Call them from SAS Data Integration Studio, uniting technical and nontechnical user activities.
Big data quality and profiling
Includes built-in directives – casing, gender and pattern analysis, field extraction, match-merge and cluster-survive. Profiling runs in-parallel on the Hadoop cluster for better performance.
In-memory analytics server
Lets you load data in memory to prepare it for high-performance reporting, visualization or analytics.
In-cluster code and data quality execution
Executes analytics and data quality processing within Hadoop for fast, budget-friendly results. Minimizes data movement for increased scalability, governance and performance.
Big data integration
Imports data from CSV, SAS/ACCESS® libraries, cloud sources, relational databases and other delimited files into Hadoop. Runs HiveQL and Impala SQL.
Take control of your data – and free up IT – with self-service data preparation.
Manage data – no special skills needed.
Perform data integration, data quality and data preparation tasks yourself, without having to write code or ask for specialized help. SAS Data Loader for Hadoop bridges the skills gap, giving all users access to their data regardless of technical ability.
Boost scalability and performance.
Business users find it easy to use. Data scientists and SAS coders like its speed, efficiency and agility. A code accelerator harnesses the power of Hadoop, and data quality functions run in memory on Spark for better performance. And by minimizing data movement, you increase your data's security.
Ensure big data quality.
Take control of the data within data lake environments. SAS Data Loader for Hadoop allows you to profile data to understand its overall quality. Then you can standardize, parse, match and perform other core data quality functions, resulting in quality data for business needs inside of the data lakes.
Speed data management processes with Spark.
Data quality functions run in memory in Apache Spark for improved performance. Matching and best record creation enables master data management for big data. In addition, you can read and write to Spark data sets as needed.
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