It’s easy to get overwhelmed by an onslaught of customer data. With so many data points, organizations need to find and effectively utilize the insights that help them better serve their customers. AI has only increased the stakes, creating more pressure to develop delightful customer experiences, build operational efficiencies and
In today’s world of financial services, a well-crafted decisioning system is paramount, whether you're dealing with credit risk, fraud prevention, financial compliance, or any other critical aspect. Occasionally, financial services organizations decide whether to buy a risk decisioning system or build one using in-house resources. This quandary demands careful consideration
The relationship between trust and accountability is taking center stage in the global conversations around AI. Accountability and trust are two sides of the same coin. In a relationship – whether romantic, platonic or business, we trust each other to be honest and considerate. Trust is fueled by actions that showcase
When tech experts want to hear directly from thought leaders in the industry, they turn to theCUBE for professionally produced interviews from wherever the global enterprise tech community is gathering. During SAS Explore in Las Vegas, theCUBE stopped by the Innovation Hub to interview a few SAS leaders and get their take
This year, Las Vegas played host to SAS Explore, an incredible gathering of developers, data scientists, engineers, programmers and more. In true Las Vegas fashion, the opening session brought all the glitz, immersing attendees in everything SAS offers. With a particular focus on SAS enthusiasts and users, day one featured exciting
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
In a world where technology is a cornerstone of society, opportunities in the tech sector should be within reach for all. Yet, for many people, education, resources and access barriers stand in the way. According to research by McKinsey, Black people make up 12 percent of the US workforce but only
SAS Model Manager and the sasctl packages aim to create a seamless ModelOps and MLOps process for Python and R models. Python and R models are not second-class citizens within SAS Model Manager. SAS, Python, and R models can be easily managed using our no-code/low-code interface. This is an interface that can be extended to support a variety of use cases.
Life insurance is hard to sell. People don’t like talking about it because it draws attention to a topic no one wants to consider for themselves. Death. Life insurers have earned a reputation for laborious and intrusive processes to secure the coverage that everyone needs. So, over the years, they
SAS' Phuong Ngo demonstrates an automated shift-left CI/CD security workflow.
Entries are in. Now it’s your turn to cast your vote for the best in each category.
SAS expert Leonid Batkhan presents the %embed macro function as a way to embed both “foreign” and SAS native code from a file into a SAS program, preventing clutter in your code.
As AI rapidly advances over the next several years, I’ve been fortunate to have an active role in helping to guide a responsible path forward when it comes to technology’s impact on our daily lives. Currently, this role includes serving as Vice President for the SAS Data Ethics Practice, as an
SAS Explore 2023 is open for your ideas and submissions! Bring your content ideas to the conference -- your experience and expertise is needed!
Who is responsible for ensuring that new AI technologies are fair and ethical? Does that responsibility land on AI developers? On innovators? On CEOs? Or is the responsibility more widespread? At SAS, we believe that it is everyone’s duty to innovate responsibly with AI. We believe that adhering to trustworthy
In her first blog post, SAS' Mu He shows you how to train a convolutional neural network that can accurately detect patients with COVID-19 using the transfer learning technique.
Generative AI (GenAI) is a category of AI that can create new content, including video, audio, images and text. GenAI has the potential to change the way we approach content creation. It’s gotten much attention lately. Take ChatGPT for example. The AI chatbot has captivated the public’s imagination with clever
SAS' Mary Carter details challenges and benefits of accelerating the delivery of SAS software.
Responsible innovation is critical because technology does not exist in a vacuum. It affects us all in unexpected ways. We know analytics has an undeniable impact on society. For example, analytics can help hospitals manage their inventories for essential items like wheelchairs and bladder scanners, help sports teams curate a
SAS is inclusive as a community, as a company, and as a technology. I'll wear the message loud and proud -- and you can too.
In my blog series regarding SAS REST APIs (you can read all of my posts on this topic here) I outlined how to integrate SAS analytical capabilities into applications. I detailed how to construct REST calls, build body parameters and interpret the responses. I've not yet covered authentication for the
Between DevOps, DataOps, MLOps and ModelOps, there are different "Ops" based on different environments. "Ops" generally is the shortened version of Operations. Check out some of the different ones in our current technological world. How many do you know? Learning about DevOps DevOps or Developer Operations refers to applying agile
DataOps increases the productivity of AI practitioners by automating data analytics pipelines and speeding up the process of moving from ideas to innovations. DataOps best practices make raw data polished and useful for building AI models. Models need to work on the data that is introduced, as well as on
Data science teams are no longer comprised of tiny groups of Ph.D. holders exploring cutting-edge projects. Organizations that wish to stay competitive in their marketplaces today need effective data science teams. A strategy to effectively apply advanced analytics and data science to drive better products, services and decisions has many
Anuja Nagpal and Yonglin Zhu of SAS R&D reveal how, MLPA – without any code and within a given timeframe – finds an effective pipeline for a data set after applying data preprocessing, feature engineering and modeling with hyperparameter tuning.
It is difficult – one might even say impossible – to talk about partners without mentioning innovation. The two go hand in hand, which is why we regularly honor our partners who demonstrate outstanding innovation in our Excellence in Innovation Award. This year’s winner and finalists innovated across industries and
보통 분석모델 관리 프로세스는 모델개발, 모델등록, 배포, 모니터링 및 재학습으로 구성됩니다. 이번 글에서는 SAS Model Manager (MM)가 제공하는 API를 통해 분석모델 관리 프로세스가 어떻게 진행되는지 살펴보겠습니다. SAS MM은 모델 컬렉션의 생성 및 관리를 간소화하는 제품입니다. 이 웹 기반 인터페이스를 사용하면 모델 관리 프로세스를 손쉽게 자동화하고, 사용자가 모델링 프로세스의 각 단계별로 진행
Get educated about cryptocurrency to inform your decisions in this evolving space.
From rising operating costs to wage inflation, business leaders are facing challenges on an unprecedented scale. For small and medium-sized enterprises (SMEs) in particular, this is driving the need for more in-depth data gathering, understanding and insight generation to inform smarter decision making and identify cost-saving opportunities. Some might remember
Billy Dickerson of SAS R&D chronicles three key challenges and lessons learned in SAS' journey to continuous integration (CI) and continuous delivery (CD).
