Get your data right where you want it by loading it into – or out of – Hadoop so it’s ready and available for reports, visualizations or advanced analytics. Sound easy? It is. Because you can do it all yourself. SAS Data Loader for Hadoop empowers you to manage your own data without writing code.
Manage data without specialized skills.
No need to outsource anything. You know what you need from your data, and you can do it yourself. SAS Data Loader for Hadoop makes it easy for business users or data scientists to perform big data integration, data quality and data preparation tasks without writing complex MapReduce code or asking for outside help.
Improve scalability and performance.
While business users appreciate the solution for its ease of use, data scientists and SAS coders like how it improves speed, efficiency and agility. A code accelerator makes it possible to run code in parallel on the Hadoop cluster for faster performance. Plus, you can improve data quality and implement data profiling without moving your data.
Free up IT for more technical tasks.
When the data scientists on your team are weighed down with basic data management duties, their advanced skills go underused – and business takes a hit. SAS Data Loader for Hadoop frees up IT to focus on making your systems better, faster and more powerful.
Derive more value from your big data.
It’s easy to load data from relational data sources or SAS data sets to and from Hadoop – and put your big data to work. There are endless opportunities for advanced analytics and other technologies that have the potential to transform your organization.
SAS data expert Matt Magne explains how SAS Data Loader for Hadoop tackles the Hadoop skills shortage and empowers you to prepare, integrate and cleanse big data.
- Intuitive user interface. Easily access, transform and manage data stored in Hadoop with one web-based interface that reduces training requirements.
- Purpose-built to load data to and from Hadoop. Built from the ground up to manage big data on Hadoop; not repurposed from existing IT-focused tools.
- Big data quality and profiling. With directives that include casing, gender analysis, pattern analysis and field extraction – plus profiling that runs in-parallel on the Hadoop cluster for better performance – data will be accurate and ready for action.
- Big data integration. Import data from CSV and other delimited files into Hadoop. Plus, you can run HiveQL commands and delete rows on Hadoop tables.
- In-memory analytics server. Load data in memory to prepare it for high-performance reporting, visualization or analytics.
- In-cluster code and data quality execution. Execute analytics and data quality processing within Hadoop for fast, budget-friendly results. Minimize data movement for increased scalability, governance and performance.
- Improved security. SAS Data Loader for Hadoop supports Active Directory and Lightweight Directory Access Protocol for user authorization.