Self-service data preparation
SAS Data Preparation
Quickly prepare data for analytics using machine learning and AI suggestions – without coding, needing specialized skills or relying on IT.
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.
Free Trial
Try the latest SAS Viya capabilities.
Get a free, 14-day trial of SAS Viya, which includes SAS Data Preparation, as well as capabilities for the entire analytics life cycle.
Key Features
With self-service data preparation from SAS, you can access, profile, cleanse and transform data using an intuitive interface. Get the job done without an IT or data specialist.
Data access, preparation & quality
Access, profile, cleanse and transform data using an intuitive interface that provides self-service data preparation capabilities with embedded AI.
Custom chatbot creation
Create and deploy custom, natural language chatbots via an intuitive, low-code visual interface for chatbot-enabled insights and conversational user experiences.
Data visualization
Visually explore data and create and share smart visualizations and interactive reports through a single, self-service interface. Augmented analytics and advanced capabilities accelerate insights and help you uncover stories hidden in your data.
Access data from multiple sources
Access 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
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
Prebuilt transformations and data cleansing functions assist data scientists and business users in the exploration, refinement and transformation of data analytical readiness.
Fast, in-memory processing of data
Quickly prepare data for analysis with combined advanced analytics, data visualization and data preparation capabilities. Speed performance with bulk data movement, including parallel read/write for some sources.
Integration into analytics pipeline
Automatically integrate prepared data into the analytics pipeline, creating a seamless data discovery and data preparation user experience.
Machine learning & AI suggestions
Machine learning and AI capabilities scan data and make intelligent transformation suggestions. Accept suggestions and complete transformations at the click of a button –no advanced or complex coding required.
Cloud native
SAS Viya's architecture is compact, cloud native and fast. Whether you prefer to use the SAS Cloud or a public or private cloud provider, you'll be able to make the most of your cloud investment.
Explore More on SAS Data Preparation and Beyond
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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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Customer Story
Jakarta Smart City uses IoT analytics to better serve residentsJakarta and SAS team up to create an award-winning approach to public services and disaster management.
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Customer Story
Improving loss ratios and profitabilityTriad Analytic Solutions helps insurers benefit from advanced 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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Customer Story
Combating financial crime and terrorism financing with real-time sanctions screeningOrange Bank stays ahead of emerging risks and changing regulations with a cloud-based sanctions-screening solution from SAS and Neterium.
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Article
What big data has brought to the privacy discussionHow does big data impact your privacy? There are ways to balance privacy and security in an increasingly transparent and dangerous world.
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Article
How to improve data prep for analytics: TDWI shares best practicesGetting good results from your data means doing a good job of preparing the data for analytics. Find out what TDWI says it takes to get there.
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Article
Public health infrastructure desperately needs modernizationPublic health agencies must flex to longitudinal health crises and acute emergencies – from natural disasters like hurricanes to events like a pandemic. To be prepared, public health infrastructure must be modernized to support connectivity, real-time data exchanges, analytics and visualization.
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Customer Story
A data-driven approach to whole person careRiverside County relies on data integration and analytics from SAS to improve the health and well-being of vulnerable Californians.
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Analyst Report
Gartner Top Strategic Technology Trends for 2023: AI Trust, Risk and Security ManagementLearn why IT leaders must adopt an AI TRiSM to protect their organizations and improve their business outcomes from AI models.
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Analyst Report
Gartner positions SAS as a Leader in the Magic Quadrant for Data Quality SolutionsGartner positions SAS as a Leader in the Magic Quadrant for Data Quality Solutions.
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Customer Story
Transforming the consumer banking experience through advanced analyticsCIMB Singapore uses SAS Viya to enhance business operations and keep pace with changing customer needs.
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Customer Story
Identifying potential trouble spotsFlorida DOC turns to SAS Analytics to help improve citizen safety.
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Article
Components of an information management strategyBefore starting a data management strategy for your business, you need to understand each component. Data expert David Loshin breaks them down.
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E-Book
Data Preparation Challenges Facing Every EnterpriseData preparation
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E-Book
Data Privacy: Are You Concerned?Report based on a 2018 survey of 525 US consumers regarding their views on data privacy in light of recent data scandals and the implementation of the General Data Protection Regulation in the EU. It's purpose is to better understand their opinions on data privacy and how it affects their behaviors and trust toward companies.
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Customer Story
Building a culture of analytics empowers university to lead as an educational enterpriseFrom enrollment to graduation, the University of Texas at Arlington uses SAS Analytics for Education on Amazon Web Services to aid in analysis supporting student success and campus strategic decision making.
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Article
The “problem-solver” approach to data preparationNoted technology author David Loshin explains why it's important to know what the problems are before getting data ready for analytics.
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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 these 10 questions as a guide.
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Article
Big data privacy: Four ways your data governance strategy affects security, privacy and trustWith IT and business strategies converging, something that’s a little late to the party is the concept of big data privacy.
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Article
Data governance: The case for self-validationLearn why you should redefine data governance policies to empower customers to be accountable for keeping their personal data accurate, consistent and up-to-date.
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Customer Story
Advanced analytics fuels virtual banking with data-driven decisionsAirstar Bank relies on SAS for risk-based customer due diligence, money laundering detection and comprehensive credit risk management.
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Article
Data integration: It ain't what it used to beOnce limited in scope, data integration now supports analytics and data-driven operational processes like real-time insurance claims processing and IoT apps.
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Customer Story
Knowing the who, informs the whatThe New Zealand Ministry of Health established the Virtual Data Registry to more accurately identify diabetes sufferers and citizens likely to contract diabetes. They'll use the database to inform policy and spending decisions that will ensure better care for those patients.
Related Offerings
Check out these products and solutions related to SAS Data Preparation.
- SAS/ACCESS®Get seamless, transparent read, write and update access to data, regardless of source or platform.
- SAS® Information GovernanceEasily find data and analytic assets, while simultaneously protecting and evaluating their fitness for use.
- SAS® Visual AnalyticsDiscover and explore relationships in data, and share insights.