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What is Wolfram Data Science Platform?

The Wolfram Data Science Platform enables users to engage with both structured and unstructured data, regardless of whether it is static or streaming in real-time. By harnessing the power of WDF and the linguistic framework utilized in Wolfram|Alpha, individuals can convert unstructured data into structured forms through automated methods or guided assistance that aids in disambiguation and restructuring. This platform utilizes sophisticated database connection technologies to seamlessly integrate information from various databases into its dynamic symbolic representation. With the ability to natively understand hundreds of data formats, the Wolfram Data Science Platform promotes conversion across a wide array of data types. It supports numerous formats, including images, text, networks, geometry, sounds, and GIS data, among others. By employing the innovative symbolic data representation that is a hallmark of the Wolfram Language, the platform can efficiently handle both SQL-type and NoSQL data structures. Furthermore, the Wolfram Data Science Platform automatically produces a detailed interactive report, implementing algorithms that identify and visualize essential features of the dataset, thus enhancing the intuitiveness and informativeness of data analysis. This versatile and feature-rich environment not only enables users to extract deeper insights but also fosters a more collaborative approach to data exploration and decision-making.

What is Unity Catalog?

Databricks' Unity Catalog emerges as the only all-encompassing and transparent governance framework designed specifically for data and artificial intelligence within the Databricks Data Intelligence Platform. This cutting-edge offering allows organizations to seamlessly oversee both structured and unstructured data across multiple formats, along with machine learning models, notebooks, dashboards, and files on any cloud or platform. Data scientists, analysts, and engineers can securely explore, access, and collaborate on trustworthy data and AI resources in various environments, leveraging AI capabilities to boost productivity and unlock the full advantages of the lakehouse architecture. By implementing this unified and open governance approach, organizations can enhance interoperability and accelerate their data and AI initiatives, while also simplifying the process of meeting regulatory requirements. Moreover, users can swiftly locate and classify both structured and unstructured data, including machine learning models, notebooks, dashboards, and files across all cloud platforms, thereby ensuring a more efficient governance experience. This holistic strategy not only streamlines data management but also promotes a collaborative atmosphere among teams, ultimately driving innovation and enhancing decision-making processes.

Media

Media

Integrations Supported

AWS Glue
Apache Spark
Azure Synapse Analytics
ChatGPT Plus
DataNimbus
DuckDB
GO+
Google Cloud BigQuery
Google Cloud Platform
LanceDB
LangChain
MLflow
Microsoft Fabric
MySQL
PuppyGraph
Snowflake
StarRocks
Starburst Enterprise
Trino
Unstructured

Integrations Supported

AWS Glue
Apache Spark
Azure Synapse Analytics
ChatGPT Plus
DataNimbus
DuckDB
GO+
Google Cloud BigQuery
Google Cloud Platform
LanceDB
LangChain
MLflow
Microsoft Fabric
MySQL
PuppyGraph
Snowflake
StarRocks
Starburst Enterprise
Trino
Unstructured

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Wolfram

Date Founded

1987

Company Location

United States

Company Website

www.wolfram.com/data-science-platform/

Company Facts

Organization Name

Databricks

Date Founded

2013

Company Location

United States

Company Website

www.databricks.com/product/unity-catalog

Categories and Features

Data Science

Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports

Categories and Features

Data Governance

Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management

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