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Description
Dataform provides a platform for data analysts and engineers to create and manage scalable data transformation pipelines in BigQuery using solely SQL from a single, integrated interface. The open-source core language allows teams to outline table structures, manage dependencies, include column descriptions, and establish data quality checks within a collective code repository, all while adhering to best practices in software development, such as version control, various environments, testing protocols, and comprehensive documentation. A fully managed, serverless orchestration layer seamlessly oversees workflow dependencies, monitors data lineage, and executes SQL pipelines either on demand or on a schedule through tools like Cloud Composer, Workflows, BigQuery Studio, or external services. Within the browser-based development interface, users can receive immediate error notifications, visualize their dependency graphs, link their projects to GitHub or GitLab for version control and code reviews, and initiate high-quality production pipelines in just minutes without exiting BigQuery Studio. This efficiency not only accelerates the development process but also enhances collaboration among team members.
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
No
API Access
Has API
Yes
Integrations
Google Cloud BigQuery
Yes
Amazon EMR
No
Amazon Redshift
No
Amazon S3
No
Apache Parquet
No
Azure Data Lake
No
Azure HDInsight
No
Azure Synapse Analytics
No
Cloud Dataprep
No
Cloudera Data Platform
No
Integrations
Google Cloud BigQuery
Yes
Amazon EMR
Yes
Amazon Redshift
Yes
Amazon S3
Yes
Apache Parquet
Yes
Azure Data Lake
Yes
Azure HDInsight
Yes
Azure Synapse Analytics
Yes
Cloud Dataprep
Yes
Cloudera Data Platform
Yes
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Founded
1998
Country
United States
Website
cloud.google.com/dataform
Vendor Details
Company Name
SAS
Founded
1976
Country
United States
Website
www.sas.com/en_us/software/studio.html