SAS® DATA PREPARATION
Quickly prepare data for analytics using machine learning and AI suggestions – without coding, needing 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.
Self-service interface
Generates code automatically from an intuitive, point-and-click interface so nontechnical users can profile, cleanse, blend and move data without specialized skills or training.
Access data from multiple sources
Accesses data from flat files, relational data sources, social media, SAS data sets, Hadoop, data lakes, the cloud, Teradata, CSV or text files, or any source defined by licensed SAS/ACCESS® software.
Ability to code
Enables technical users who prefer to code to access SAS Data Quality routines from SAS code or third-party coding languages (e.g., Python).
Built-in data quality & integration
Includes prebuilt transformations and data cleansing functions to assist data scientists and business users in the exploration, refinement and transformation of data analytical readiness.
In-memory, fast processing of data
Combines advanced analytics, data visualization and data preparation capabilities to help you prepare data quickly for analysis. Speeds performance with bulk data movement, including parallel read/write for some sources.
Integration into analytics pipeline
Integrates prepared data into the analytics pipeline automatically, creating a seamless data discovery and data preparation user experience.
Machine learning & AI suggestions
Scans data and makes intelligent transformation suggestions using machine learning and AI. You can accept suggestions and complete transformations at the click of a button, no advanced or complex coding required.
Cloud data exchange
Securely copies data from on-site repositories to a cloud-based SAS Viya instance running in a private or public cloud for use in SAS Viya applications and sending data back to on-site locations. Preprocess data locally, reducing the amount of data that needs to be moved to remote locations.
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, wrangle and shape data on your own – where it is then integrated as part of your reporting and analytics pipeline. This frees IT to focus on more strategic work, while you get insights needed 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
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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.
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White Paper
Thirsting for Insight? Quench It With 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.
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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.
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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.
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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.
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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.
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White Paper
Data EvolutionMost organizations have spent the last decade acquiring data integration tools from different sources to manage, govern and utilize data. This generally means they now possess a nonintegrated toolbox of technologies. Organizations need a solution that enables employees to focus on better managing data instead of integrating disparate technologies. A comprehensive data management platform would address all aspects of data integration, data quality and master data management, be underpinned by adapters and a federation capability, and share technical and business metadata. Ultimately, a single user interface should surface all of the data management capabilities. This white paper describes the evolution of data integration tools and the benefits that can be achieved with a comprehensive data management platform.
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White Paper
Best Practices in SAS® Data Management for Big DataThis paper discusses capabilities and techniques for optimizing SAS Data Management products for big data. It demonstrates how SAS supports Apache Hadoop technologies, including details on the various languages available in the platform and how to use them with SAS. An overview of SAS Data Management integration with the SAS® LASR™ platform is also provided. Practical tips and techniques are presented, including case studies that illustrate how to best use the SAS Data Management feature set with big data.
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White Paper
Transforming Health Care and Life Sciences Organizations With AnalyticsHealth care and life sciences organizations are proving that with a little ingenuity, data and analytics can be working much harder to improve lives and health, while improving the health of the organization as well. At the May 2014 SAS Health Analytics Executive Conference, industry leaders from Kaiser Permanente, WellPoint and Janssen Pharmaceuticals discussed how their organizations are being transformed with analytics – how they got started, what worked, and how analytics expertise is developed and structured.
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White Paper
Data Integration Déjà Vu: Big Data Reinvigorates DIData integration (DI) may be an old technology, but it is far from extinct. Today, rather than being done on a batch basis with internal data, DI has evolved to a point where it needs to be implicit in everyday business operations. Big data – of many types, and from vast sources like the Internet of Things – joins with the rapid growth of emerging technologies to extend beyond the reach of traditional data management software. To stay relevant, data integration needs to work with both indigenous and exogenous sources while operating at different latencies, from real time to streaming. This paper examines how data integration has gotten to this point, how it’s continuing to evolve and how SAS can help organizations keep their approach to DI current.
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White Paper
Aggravation or Aggregation: Risk Data and ComplianceTo improve the resolvability of banks and enhance their risk IT capabilities, the Basel Committee on Banking Supervision established a set of principles for effective risk data aggregation and risk reporting. The BCBS 239 principles set a challenging agenda for banks in terms of improving their IT infrastructure. SAS surveyed 27 major financial institutions worldwide to explore the initiatives undertaken to comply with BCBS 239, including compliance initiatives, risk data solutions, risk data aggregation, the current state of process automation, and current progress and the future outlook of compliance projects.
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White Paper
Modernizing Data Integration to Accommodate New Big Data and New Business RequirementsData integration modernization can take many forms, depending on the current state of your infrastructure and what kinds of new data or platforms you must embrace. This TDWI Checklist Report offers recommendations for the seven most pressing DI modernization tasks. It covers many of the new vendor product types, functionality, and user best practices that can contribute to data integration modernization, plus the business case and technology strengths of each.
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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.
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Interview
How does one of the largest cities in the world use data for social good? From data privacy to data quality, what are the challenges in using data for social good, and how does one large organization in New York City address them? Hear from a research scientist at the Center for Innovation through Data Intelligence about the data they have, the questions they ask of it, and the data they’d like to see in the future.
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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.
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Article
Key questions to kick off your data analytics projectsThere’s no single blueprint for starting a data analytics project. Technology expert Phil Simon suggests considering these ten questions as a preliminary guide.
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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.
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Article
Five steps that can save your data analytics – and help you save faceThere’s nothing more awkward than watching analysts struggle to defend their results. Even if you think your process is rock-solid, things can go awry – unless you keep these milestones in mind.
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Article
Big data integration: Go beyond 'just add data'Every business-focused technology requires users to "just add data." This article by Matt Magne explores why that's much easier than it sounds, especially in a big data age.
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White Paper
Tips for successful data integration modernizationOrganizations today have to capture, process and move all types of new and big data. Get some tips for data integration modernization from TDWI.
Related Products
Check out these products related to SAS Data Preparation, all based on the powerful SAS® Platform.
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SAS/ACCESS® SoftwareRead, write and update data regardless of its native database or platform.
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SAS® Data QualityImprove the value of your data – and maintain that excellence – for better data-driven decisions.
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SAS® Visual AnalyticsVisually explore all data, discover new patterns and publish reports to the web and mobile devices.
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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.
