SAS Voices

Data Management

Blend, cleanse and prepare data for analytics, reporting, or data modernization efforts.

Data Management | Innovation | Predictions

Vrushali SawantNovember 22, 2023 0

3 industries set to benefit from ethical synthetic data generation in 2024

In 2024, we will witness the proliferation of synthetic data across industries. In 2023, companies experimented with foundational models, and this trend will continue. Organizations see it as an emerging force to reshape industries and change lives. However, the ethical implications can't be overlooked. Let’s explore some industries I think

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Banking | Health Care | Life Sciences

Data Management

Margaret CrevarNovember 8, 2023 2

Using IBM mainframes and SAS for mission critical operations

What makes mainframes relevant today? Why are they still in use more than 50 years after their inception? Watch the video below and then come back to read about some specific use cases of SAS® technology in use on IBM mainframe computers. Mainframes have had many uses Throughout this half-century

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Cloud | Data Management

Marty TomasiNovember 7, 2023 0

Building trust in the cloud: Are you a champion for security?

When it comes to my data in the cloud, I want my service providers to keep security in mind. Few things worry me more than knowing my private information is not secure, or is being shared with untrusted collaborators. That’s why the recent announcement from SAS, our partner Microsoft, and

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Analytics | Data Management

Gavin DayAugust 15, 2023 0

Data management: The foundation for resilient organizations

Today, a business disruption can stem from just about any type of event — a once-in-a-lifetime pandemic, economic pressures, critical skillset shortages or changes in market or investor evaluation criteria. Only resilient companies can ride out the turbulence and quickly bounce back. But with the ongoing pace of change, making

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Advanced Analytics | Analytics | Cloud | Data Management

blue waves symbolizing a statistical computing environment

Brittany ShriverMay 22, 2023 0

5 tips for choosing a statistical computing environment

When you think about life-saving technology, does a statistical computing environment come to mind? Statistical computing environments (SCE) are critical in accelerating scientific discoveries by enabling researchers to manage, process and analyze data efficiently and compliantly, maintaining the utmost regulatory integrity. As life sciences research generates increasingly large and diverse

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Life Sciences

Analytics | Data Management | Fraud & Security Intelligence

Alex KwiatkowskiMay 15, 2023 0

Could these tips help prevent the next bank failure?

The reverberations of SVB’s collapse continue to be felt in the banking industry. Markets remain jittery and the negative news headlines keep coming. First Republic Bank had its credit rating downgraded into junk territory by S&P Global, causing its share price to plummet by 47 percent before rallying. On the

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Banking

Data Management

Reggie TownsendApril 27, 2023 0

Data quality: The foundation for trustworthy AI

I see the term resilience in a lot of business literature these days. Intuitively, it makes sense. After a pandemic, global supply chain disruptions and resulting economic fragility, executives understandably consider adaptability, durability and how best to operate with a strength of character – all attributes that define resilience. Many

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Artificial Intelligence | Data Management | Innovation

Olivia OjedaMarch 8, 2023 0

How women are revolutionizing fashion with AI

Women are trailblazing new ideas across industries, countries and cultures every day. This International Women’s Day, take a minute to read some innovative SAS Hackathon highlights for this upcoming year and from the past. You'll also learn about some incredible women and see what amazing innovations lie ahead. AI

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Analytics | Data Management

Liz McIntoshMarch 7, 2023 0

Metadata: 5 reasons why you should understand its analytical value

Analytics can get you answers from data. With an ever-increasing volume of data and new regulatory pressures, you need to know more than knowing where and how it is used. It's critical to comprehend the data: Is it relevant? Does it contain sensitive or private information? Can we detect bias?

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Analytics | Data Management