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What is SAS Data Science Programming?

Develop and oversee large-scale decision-making processes driven by data, whether in real-time or batch formats. The SAS Data Science Programming approach is tailored for data scientists who prefer a comprehensive programmatic style, enabling them to engage with SAS's analytical tools throughout the full analytics life cycle, which includes stages like data preparation, exploration, and deployment. Identify and illustrate crucial patterns in datasets, which facilitates the generation and sharing of interactive reports and dashboards. Furthermore, utilize self-service analytics to quickly assess potential outcomes, empowering organizations to make well-informed, data-driven choices. Work with your data to create or adjust predictive analytical models using the SAS® Viya® platform. This collaborative framework encourages data scientists, statisticians, and analysts to unite in refining their models iteratively across different segments, ultimately bolstering decision-making grounded in dependable insights. Address complex analytical problems through an intuitive visual interface that adeptly manages all facets of the analytics life cycle, ensuring users can navigate challenges with both ease and accuracy. By adopting this methodology, organizations can significantly improve their strategic decision-making capabilities and drive better overall performance in their operations. Emphasizing collaboration and innovation within analytics will lead to more agile responses to rapidly changing market conditions.

What is IBM Cloud Pak for Data?

A significant challenge in enhancing AI-fueled decision-making is the insufficient use of available data. IBM Cloud Pak® for Data offers an integrated platform featuring a data fabric that facilitates easy connection and access to disparate data, regardless of whether it is stored on-premises or in multiple cloud settings, all without the need to move the data. It optimizes data accessibility by automatically detecting and categorizing data to deliver useful knowledge assets to users, while also enforcing automated policies to ensure secure data utilization. To accelerate insight generation, this platform includes a state-of-the-art cloud data warehouse that integrates seamlessly with current systems. Additionally, it enforces universal data privacy and usage policies across all data sets, ensuring ongoing compliance. By utilizing a high-performance cloud data warehouse, businesses can achieve insights more swiftly. The platform also provides data scientists, developers, and analysts with an all-encompassing interface to build, deploy, and manage dependable AI models across various cloud infrastructures. Furthermore, you can enhance your analytical capabilities with Netezza, which is a powerful data warehouse optimized for performance and efficiency. This holistic strategy not only expedites decision-making processes but also encourages innovation across diverse industries, ultimately leading to more effective solutions and improved outcomes.

Media

Media

Integrations Supported

Microsoft 365
Microsoft Excel
Microsoft Outlook
Microsoft PowerPoint
Microsoft Word
SAS Visual Statistics
SAS Viya

Integrations Supported

Datamatics Trade Finance
IBM Control Desk
IBM Db2 Big SQL
IBM Db2 Event Store
IBM InfoSphere Information Governance Catalog
IBM Netezza Performance Server
IBM Storage Software Suite
IBM WebSphere Commerce

API Availability

Has API

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

$699 per month

Supported Platforms

SaaS

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

SAS

Company Location

United States

Company Website

support.sas.com/en/software/data-science-programming.html

Company Facts

Organization Name

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/products/cloud-pak-for-data

Categories and Features

Data Science

Not specified

Categories and Features

AI Governance

Not specified

Big Data

Not specified

Data Fabric

Not specified

Data Integration

Not specified

Data Science

Not specified

Data Virtualization

Not specified

Machine Learning

Not specified

Predictive Analytics

Not specified

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