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SAS® on Mainframe

Our team navigates the unique landscape of SAS® integration on Mainframe systems, merging the robust reliability of mainframe computing with the analytical strength of SAS®. This powerful combination forms a platform for enterprise-scale analytics, ensuring unparalleled performance, security, and efficiency. Analytium can optimise SAS® on Mainframe, providing a seamless and reliable platform for advanced analytics.

Data Security

Data Security

SAS® on Mainframe offers unparalleled data security and robust performance for analytics workflows in large enterprises.
Volume Capacity

Volume Capacity

It enables high-volume data processing, allowing for critical analysis of sizable datasets within industries such as finance and healthcare.
Stable and Reliable

Stable and Reliable

The integration of SAS® with mainframe systems ensures stable and reliable analytical processing, leading to enhanced operational efficiency.

3 Reasons to Care

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1
Predictive Insights

Cog

AI-driven analytics transforms raw data into predictive insights, automating and enhancing decision-making across the business. 

2
Operational Efficiencies

Cog

By leveraging AI, companies can personalise customer experiences and optimise operations, leading to increased customer loyalty and operational efficiencies.

3
Innovation

Cog

AI serves as the backbone for innovation, helping businesses adapt to emerging market conditions and staying ahead of the competition. 

SAS on Mainframe

Technology Overview

SAS® on Mainframe binds the reliability and security of mainframe computing with the analytical skill of SAS®, forming a powerful platform for enterprise-scale analytics.

FAQ

Discover how our focus on deep Data & Analytics technology expertise delivers solutions that are designed to deliver on the outcomes you expect.

How do mainframes enhance SAS®'s analytical capabilities?
Mainframes provide the processing power and security necessary for executing complex analytics on large datasets.
What are the advantages of running SAS® on a mainframe environment?
Improved processing speeds, data security, and system stability are among the key benefits.
Is it cost-effective to use SAS® on Mainframes?
Yes, when dealing with massive volumes of transactions and data processing, efficiency and reliability can lead to cost savings.

Featured Case Studies

Growth Marketing vs. Performance Marketing: Key Differences

If you’ve searched for marketing strategies or follow #MarketingTwitter, there’s no doubt you’ve seen the terms “growth marketing” and “performance marketing” before. If you have, ...
Harmen Porter
Harmen Porter

4 Signs You Need to Create More Long From Content (And How To Do It)

Many marketers improve the performance of their website pages using a method called content optimization. With content optimization, you can identify and adjust messaging over a ...
Chris Baker
Chris Baker

Using HubSpot With WordPress Websites: HubSpot vs. WordPress vs. Both

Many marketers improve the performance of their website pages using a method called content optimization. With content optimization, you can identify and adjust messaging over a ...
Shirline Dungey
Shirline Dungey

Growth Marketing vs. Performance Marketing: Key Differences

If you’ve searched for marketing strategies or follow #MarketingTwitter, there’s no doubt you’ve seen the terms “growth marketing” and “performance marketing” before. If you have, ...
Harmen Porter
Harmen Porter

4 Signs You Need to Create More Long From Content (And How To Do It)

Many marketers improve the performance of their website pages using a method called content optimization. With content optimization, you can identify and adjust messaging over a ...
Chris Baker
Chris Baker

Using HubSpot With WordPress Websites: HubSpot vs. WordPress vs. Both

Many marketers improve the performance of their website pages using a method called content optimization. With content optimization, you can identify and adjust messaging over a ...
Shirline Dungey
Shirline Dungey

Featured Use Cases

Real-time Transaction Processing for Banking
Real-time Transaction Processing for Banking

Context: A bank aims to improve its transaction processing system to handle high volumes efficiently while ensuring data security and compliance.

Practical Application: Implement SAS on Mainframe to leverage its high processing power and robust security features. This will enable real-time analytics on transaction data, facilitating fraud detection and risk management, thus enhancing customer trust and regulatory compliance.

Large-scale Data Management for Insurance
Large-scale Data Management for Insurance

Context: An insurance company needs to process and analyse vast amounts of data from various sources to improve risk assessment and policy pricing.

Practical Application: Use SAS® on Mainframe for efficient data management and analytics. This setup can handle large datasets with ease, allowing for sophisticated analysis like predictive modelling for risk assessment, leading to more accurate policy pricing and better financial performance.

Customer Data Analytics for Retail
Customer Data Analytics for Retail

Context: A retail chain wants to optimize its marketing strategies by gaining deeper insights into customer behaviour and preferences.

Practical Application: Deploy SAS® on Mainframe to analyse extensive customer data collected through various channels. This powerful combination enables detailed segmentation and predictive analytics, helping tailor marketing efforts to individual preferences and boosting sales effectiveness.

Let's Get in Touch

Whatever the size of your business, or the scope of your project, we're available to answer any questions you may have.