Self-service interface
Intuitive, point-and-click interface generates code automatically so nontechnical users can profile, cleanse, blend and move data without specialized skills or training.
SAS® DATA PREPARATION
Quickly prepare data for analytics – without coding, using specialized skills or relying on IT.
Self-service data preparation from SAS – on SAS® Viya® – helps you access, profile, cleanse and transform data from an intuitive interface. Get the job done without an IT or data specialist.
Access data from multiple sources
Access data from flat files, relational data sources, social media, SAS data sets, Hadoop, Teradata, CSV or text files, or any source defined by licensed SAS/ACCESS® software.
Ability to code
Technical users who prefer to code can access the SAS Data Quality routines from SAS code or from third-party coding languages (e.g., Python).
Built-in data quality and integration
Market-validated data quality and data integration are prebuilt into visual interfaces for more consistency.
In-memory, fast processing of data
A combination of advanced analytics, data visualization and data preparation capabilities helps you quickly prepare data for analysis. Bulk data movement, including parallel read/write for some sources, speeds performance.
Integration into analytics pipeline
Automatically integrates prepared data into the analytics pipeline, creating a seamless data discovery and data preparation user experience.
Get the business insights you need – on your own. Act quickly. Make decisions confidently. Work more efficiently.
Be more productive by working autonomously.
No need for specialized skills. No coding or SQL required. Our visual interface makes data preparation easy by removing technical barriers and enabling you to blend and shape data on your own – where it then gets integrated as part of your reporting and analytics pipeline. IT is freed up to focus on more strategic work, while you get the insights you need to investigate data at will.
Prepare data faster so you're ready for action.
Minimize the time you spend preparing data so you can spend more time analyzing it. Prebuilt transformations and data cleansing functions run in memory to increase processing speed. Advanced analytics, data visualization and data preparation capabilities are seamlessly combined. The result? You have more time to explore data, get answers and react to situations in near-real time.
Reuse data preparation tasks for more efficiency.
Duplicated work wastes valuable time. SAS Data Preparation helps you share automatically generated code with IT so it can be scheduled to run during every source data update. You can also save data preparation plans to be used by others. Shared work leads to more productivity – and everyone benefits.
Collaborate with other team members.
Working with multiple members of your team on the same project has never been easier. With SAS Data Preparation you can share jobs as centrally managed assets. Project activity feeds can be set to notify teams and individuals of changes and updates. You can share and reuse tasks and existing plans, post updates and work together to boost productivity and generate more value from your data.
This solution runs on SAS® Viya®, which has the breadth and depth to conquer any analytics challenge, from experimental to mission critical. SAS Viya extends the SAS Platform to enable everyone – data scientists, business analysts, developers and executives alike – to collaborate and realize innovative results faster, with flexible licensing and pricing options to accommodate your current and future needs.
Explore More on SAS® Data Preparation & Beyond
-
Article
The five D's of data preparationFrom discovering which data is best to use, to delivering it in the right format to users, learn why these 5 D’s are essential to data preparation.
-
White Paper
5 Data Management for Analytics Best Practices“Unpolluted” data is core to a successful business – particularly one that relies on analytics to survive. But preparing data for analytics is full of challenges. By some reports, most data scientists spend 50 to 80 percent of their model development time on data preparation tasks. SAS adheres to five data management best practices that help you access, cleanse, transform and shape your raw data for any analytic purpose. With a trusted data quality foundation and analytics-ready data, you can gain deeper insights, embed that knowledge into models, share new discoveries and automate decision-making processes to build a data-driven business.
-
Article
Data lake and data warehouse – know the differenceData lake – is it just marketing hype or a new name for a data warehouse? Find out what a data lake is, how it works and when you might need one.
-
Article
Data management backgrounderFrom data integration to data quality and data preparation, find out what these terms mean and why they’re so important for your analytics projects.
-
White Paper
Data Preparation – Refining Raw Data into ValueBARC conducted an independent survey among 695 BI professionals from a range of industries that offers a global overview about current thinking on data preparation. More than 75% of respondents consider data preparation to be important.
The study demonstrates the benefits, timeliness and relevance of data preparation for analytics. It shows you how and by whom data preparation is being driven and how the balancing act between governance and flexibility can be achieved by specifying the requirements for data preparation.
Learn how data preparation is used today, which challenges you need to overcome, and in which organizational framework this takes place. Finally, BARC gives recommendations how you can be effective in creating value from data in your company.
-
White Paper
Data Preparation Challenges Facing Every EnterpriseTime spent cleaning data is eating away at the time available for analysis. What steps can your enterprise take to get analytics back on track?
Read this e-book to learn how to reverse those numbers, improving efficiency for both business users and IT by letting analysts quickly prepare data for analytics.
-
White Paper
Data Preparation Challenges Facing Every EnterpriseTime spent cleaning data is eating away at the time available for analysis. What steps can your enterprise take to get analytics back on track?
Read this e-book to learn how to reverse those numbers, improving efficiency for both business users and IT by letting analysts quickly prepare data for analytics.
-
White Paper
Data Preparation – Refining Raw Data into ValueBARC conducted an independent survey among 695 BI professionals from a range of industries that offers a global overview about current thinking on data preparation. More than 75% of respondents consider data preparation to be important.
The study demonstrates the benefits, timeliness and relevance of data preparation for analytics. It shows you how and by whom data preparation is being driven and how the balancing act between governance and flexibility can be achieved by specifying the requirements for data preparation.
Learn how data preparation is used today, which challenges you need to overcome, and in which organizational framework this takes place. Finally, BARC gives recommendations how you can be effective in creating value from data in your company.
-
White Paper
5 Data Management for Analytics Best Practices“Unpolluted” data is core to a successful business – particularly one that relies on analytics to survive. But preparing data for analytics is full of challenges. By some reports, most data scientists spend 50 to 80 percent of their model development time on data preparation tasks. SAS adheres to five data management best practices that help you access, cleanse, transform and shape your raw data for any analytic purpose. With a trusted data quality foundation and analytics-ready data, you can gain deeper insights, embed that knowledge into models, share new discoveries and automate decision-making processes to build a data-driven business.
-
Article
5 ways to become data-drivenSuccessful data-driven businesses foster collaborative, goal-oriented cultures, have leaders who believe in data and are governance-oriented. Read more in this summary of TDWI research that uncovers best practices for becoming data-driven.
-
Article
Data lake and data warehouse – know the differenceData lake – is it just marketing hype or a new name for a data warehouse? Find out what a data lake is, how it works and when you might need one.
-
Article
Data management backgrounderFrom data integration to data quality and data preparation, find out what these terms mean and why they’re so important for your analytics projects.
-
Article
The five D's of data preparationFrom discovering which data is best to use, to delivering it in the right format to users, learn why these 5 D’s are essential to data preparation.
Related Products
Check out these products related to SAS Data Preparation, all based on the powerful SAS® Platform.
-
SAS/ACCESS® SoftwareRead, write and update data regardless of its native database or platform.
-
SAS® Data QualityImprove the value of your data – and maintain that excellence – for better data-driven decisions.
-
SAS® Visual AnalyticsVisually explore all data, discover new patterns and publish reports to the web and mobile devices.
-
SAS® Viya®Conquer your analytics challenges, from experimental to mission critical. SAS Viya extends the SAS Platform to enable everyone – data scientists, business analysts, developers and executives alike – to collaborate and realize innovative results faster.
