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Average Ratings 0 Ratings

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ease
features
design
support

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Description

SAS Enterprise Guide provides users with a streamlined way to harness the analytical capabilities of SAS via a user-friendly point-and-click interface designed for Windows. This tool enables users to independently conduct analyses by merging a vast selection of analytical options with SAS software's robust features, all within an intuitive graphical interface. Consequently, business analysts can generate their own insights and disseminate reports, allowing IT departments to concentrate on more strategic initiatives. Furthermore, SAS Enterprise Guide seamlessly integrates with SAS Viya, enabling teams to utilize their existing workflows while executing SAS programs in the cloud without the need for recoding, thus leveraging the advantages of a modern, cloud-based environment that offers increased efficiency, scalability, and enhanced analytical capabilities. Additionally, it assists users in quickly accessing data for their analyses, scheduling projects, sharing outcomes, and embedding outputs for recurring use, which includes leveraging advanced analytics and various other functionalities provided by SAS. This combination of features not only enhances productivity but also fosters a more collaborative approach to data analysis within organizations.

Description

SAS Studio offers a programming environment accessible through web browsers, making it simpler and quicker to write and engage with SAS code from any location. This platform is designed to enhance teamwork by facilitating the creation of effective data pipelines, promoting effortless collaboration, minimizing the need for extensive coding, and allowing for open-source integration. It interfaces with prominent cloud data services like AWS Redshift and S3, Google BigQuery and Cloud Storage, and Azure Data Lake Storage, in addition to various relational and non-relational databases such as Oracle, Snowflake, Teradata, SingleStore, and MongoDB. Furthermore, SAS Studio is compatible with multiple file formats, including Excel, text, Parquet, and ORC. Users have the flexibility to work with a no-code, low-code, or traditional coding approach, enabling them to construct comprehensive data pipelines through drag-and-drop operations, create Python and SAS code within SAS Studio or other IDEs, and integrate these components into SAS Studio workflows for secure and centralized data access. Additionally, SAS Studio accommodates both ELT and ETL methodologies, ensuring versatility in data handling. This adaptability makes SAS Studio a valuable tool for data professionals aiming to streamline their analytics processes.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon EMR
Amazon Redshift
Apache Parquet
Azure Data Lake
Azure HDInsight
Azure Synapse Analytics
Cloud Dataprep
Cloudera Data Platform
Databricks
Google Cloud Storage
Greenplum
IBM Db2
Microsoft Excel
MongoDB
MongoDB Atlas
Oracle Database
Python
SAS Viya
SingleStore
Teradata VantageCloud

Integrations

Amazon EMR
Amazon Redshift
Apache Parquet
Azure Data Lake
Azure HDInsight
Azure Synapse Analytics
Cloud Dataprep
Cloudera Data Platform
Databricks
Google Cloud Storage
Greenplum
IBM Db2
Microsoft Excel
MongoDB
MongoDB Atlas
Oracle Database
Python
SAS Viya
SingleStore
Teradata VantageCloud

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

SAS

Founded

1976

Country

United States

Website

www.sas.com/en_us/software/enterprise-guide.html

Vendor Details

Company Name

SAS

Founded

1976

Country

United States

Website

www.sas.com/en_us/software/studio.html

Product Features

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Product Features

Alternatives

Alternatives