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.
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.
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.
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.
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.
This TDWI report accelerates users’ understanding of new products, technologies and best practices that have emerged around Hadoop. It will also help readers connect available options to use cases, with a focus on mainstream enterprise uses, while respecting proven IT practices and delivering maximum business value.
Discover why data quality and data governance are so important to large-scale analytics. Learn how to balance governance with usability so you can come up with a strategic plan for managing big data.
This paper focuses on the integration of Hadoop-centric big data approaches with user-focused business analytics capabilities. Users see accessible business analytics tools that produce results, without the need for IT staff to craft queries in programming languages.
Learn how SAS Data Loader for Hadoop enables business users – along with data scientists and IT – to access, profile, transform and cleanse Hadoop data. The best part is, it requires minimal training and no need for coding.
An Investigation into the Evolution and Deployment of Hadoop
Want to get even more value from your Hadoop implementation? Learn about the SAS portfolio of solutions that enable you to bring the full power of business analytics to Hadoop.
A vendor profile from The Bloor Group that refers to the full report: Making Sense of Hadoop and its Ecosystem.
Written by the International Institute for Analytics, this paper presents a broad view of Hadoop in the marketplace, including how it is being adopted and used by global organizations. It then offers a set of recommendations that organizations can use to succeed with Hadoop.
Discover why Heavy Reading recommends using advanced analytics from proven vendors to obtain real-time intelligence from all your big data.
Discover why the latest evolution of data integration delivers more value from big data.
This TDWI Best Practices Report discusses the latest data preparation processes, self-service options and how to effectively integrate data prep with analytics and BI solutions.r More Productive Users
Read interviews with two Hadoop customers and two Hadoop implementors, plus Hadoop adoption survey results and tips for big data management - all in one convenient ebook package.
Find out how organizations are addressing their most pressing data quality issues, discover the top 10 priorities for data quality solutions, and learn the best ways to engage and empower business users to improve data quality.
This paper examines how a non-geek yet technically savvy business professional can understand how to use Hadoop - and how it will impact enterprise data environments for years to come. The paper serves as a playbook that demonstrates six common “plays” that illustrate how Apache Hadoop can support and extend the enterprise data warehouse (EDW) ecosystem.
SAS, Hortonworks and Intel can help you embrace technologies and processes to anticipate a wide range of customer needs, providing the foundation for next-generation customer experiences.
Leveraging a big-picture approach to Hadoop opens up a world of
This paper focuses on eight considerations when it comes to applying big data analytics to extract value from Hadoop. Readers will learn about the importance of in-memory analytics, how to optimize the data preparation processes and the skill sets needed to derive benefits from Hadoop.
Ease your transition to Hadoop by following these tried-and-true best practices from SAS customers.
Let the SAS Analytics Life Cycle guide you through the iterative process of going from raw data to predictive modeling to automated decisions, faster. This paper tells you how.
Check out these products related to SAS Data Loader for Hadoop, built on the powerful SAS® Platform.
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