Tag: data culture and literacy

Advanced Analytics | Artificial Intelligence | Innovation
Alex Coop 0
Making sense of the AI hype with Katie King

Katie King has interviewed subjects from many walks of business life for her books: academics, venture capitalists, executives from high-profile brands and telecommunications companies. Among them, one that made a lasting impression was an artist: Ai-Da. King interviewed the artificial intelligence-powered humanoid robot artist for her 2022 book AI Strategy

Analytics
Alexis Mallis 0
How SAS® users are benefiting from the career versatility of data analytics

More than spreadsheets and formulas, data analytics combines technology, creativity and strategic thinking to help diverse industries make innovative discoveries and leave an impact where it matters most. Even historically, non-technical industries like agriculture, for instance, are tapping into data management and visualization to predict and reduce their carbon footprint

Advanced Analytics
Rochelle Fisher 0
From classroom to competition: Building applied analytics skills with the Curiosity Cup

The ability to analyze and derive insights from vast amounts of information is invaluable. As industries increasingly rely on data-driven decision-making, there is a growing demand for professionals with expertise in applied analytics. To bridge this skills gap, academic institutions seek innovative ways to provide students with hands-on experience. Integrating

Analytics | Students & Educators
Lilia Rodriguez 0
Honoring educators who are learning, teaching and using SAS in innovative ways

This summer, SAS Academic Programs recognized four faculty members from across the country for their excellence in teaching data analytics. Awardees of the SAS Distinguished Award and the Emerging Educator Award received plaques at the SAS Summer Educator Conference, where they participated in a panel discussion about their experience teaching

Analytics | Artificial Intelligence
Reggie Townsend 0
Striking the balance: Navigating the pitfalls of AI technocentrism

Embracing AI is wonderful. From a practical business perspective, though, there are limits. This issue is broader than AI. However, I’ll constrain the conversation to that for now, given the attention AI is getting these days. Yes, some processes are undoubtedly good candidates for automation, but avoiding “technocentrism” is critical to

Advanced Analytics | Analytics | Cloud | Data Management
Kayt Leonard 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

Analytics | Artificial Intelligence
Bryan Harris 0
From data-driven to AI-driven: Scaling human productivity and decision making

Given the headlines each week, it is clear that global disruption and economic volatility are not slowing down. At the same time, information overload is far exceeding human capacity. Despite these pressures, business goals remain the same: improve revenue, increase margins, operate more efficiently and meet customer expectations. So, how do

Analytics
Cheryl Cass 0
How UNC Wilmington data science students are using SAS to drive business results for Lightcast

Students in the master's program in data science at the University of North Carolina Wilmington (UNCW) drove real-world results using SAS® Viya® for the labor market analytics company Lightcast. The project gave students practical analytical tools to solve a business challenge – invaluable career preparation. At the same time, Lightcast gained business insights

Analytics
Kayla Woitkowski 0
6 reasons why hiring early-career talent may be a strategy to explore

Determining the “right” talent strategy for an organization isn’t easy. Diverse projects and priorities demand various levels of knowledge, skills and experiences to achieve the end goal. Talent planning requires assessing current employees and unearthing the gaps to identify what’s needed to meet business demands. Specific and extensive knowledge and