Features List

Data

Import data from a variety of sources: databases, Hadoop, Excel spreadsheets, social media, etc.
Drag an Excel file, CSV or SAS data set onto your workspace and quickly start building reports or dashboards.
Use standard data quality functions like change case; convert, rename, remove and split columns; and create calculated columns and transformations using custom code.
Prep data using append, join, filter and transpose functions.
Reuse, schedule and monitor jobs.
View lineage with network diagrams.
Quickly view descriptive statistics on measures to help you see the characteristics of your data.
Manage data connections (ability to on-prem, cloud or file data sources) and authorization of data sets.

Data catalog

Provides automated discovery agents that crawl data sources to discover data so you'll know what data is available.

Data preparation

Includes a self-service interface to built-in data quality and data integration tools. Provides a view of what data preparation is needed.

Automatic content classification & discovery of privacy data

Provides field content identification and classification using SAS Quality Knowledge Base.

Information discovery

Helps users locate and get quick access to hard-to-find data, reports, models and other analytic assets.

Flexible search capabilities

Enables data consumers to search using free text or faceted search and apply filters on search results to refine their queries. Also allows users to use elastic search to find data assets.

One-click access to SAS Viya applications

Lets users go directly from selected data in the Information Catalog to the next application – e.g., to build an analytical pipeline or create a report.

Data lineage

Provides an end-to-end lineage – from data flow to data, report, model and decision. This includes process jobs, such as data preparation plans, while viewing additional details, properties and other related objects for each lineage asset.

Tagging

Tags can be assigned to data assets to provide collaboration across the organization or with other data users. Tag keywords can be used to search and discover data assets. Tags are governed according to who can create or assign, read or delete tags.

Metadata exchange & governance

A SAS Viya connector to Egeria enables users to read new catalog objects into Egeria and establish relationships between them. Metadata can then be shared among users and different tools, providing visibility and context around data to improve use, reuse and trust.

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.

SAS Viya in-memory engine

CAS (SAS Cloud Analytic Services) performs processing in memory and distributes processing across nodes in a cluster.
User requests (expressed in a procedural language) are translated into actions with the parameters needed to process in a distributed environment. The result set and messages are passed back to the procedure for further action by the user.
Data is managed in blocks and can be loaded in memory and on demand.
If tables exceed memory capacity, the server caches the blocks on disk. Data and intermediate results are held in memory as long as required, across jobs and users.
Includes highly efficient node-to-node communication. An algorithm determines the optimal number of nodes for a given job.
Communication layer supports fault tolerance and lets you remove or add nodes from a server while it is running. All components can be replicated for high availability.
Support for legacy SAS code and direct interoperability with SAS 9.4M5 clients.
Supports multitenancy deployment, allowing for a shared software stack to support isolated tenants in a secure manner.

SAS Information Governance Features List