Generative adversarial networks (GANs) offer a promising solution by creating synthetic data that mimics real datasets, allowing developers to build models without exposing sensitive customer information.
Synthetic data has become a valuable resource in data science and machine learning. Superior quality, reliable synthetic data facilitates analysis and iteration at scale while mitigating privacy concerns associated with real data and can fill gaps where real data is scarce. Note, however, that “good” synthetic data is not defined
In today's digital age, marketing technology (MarTech) plays a crucial role in how businesses engage with their customers. However, the success of truly contextual customer engagement hinges on one fundamental principle: trust. Building and maintaining customer trust is essential for long-term business success, as it fosters loyalty and contributes to
The world of data and AI is evolving at breakneck speed, with 2025 shaping into a year of breakthroughs and significant challenges. From AI model hallucinations to the role of synthetic data in innovation, industry leaders are grappling with complex issues that will shape the future of technology. I recently
Every year, as Data Privacy Week sharpens the focus on protecting personal information, I’m reminded of a customer event a major North American bank hosted at SAS world headquarters. The bank’s chief data officer led a roundtable discussion on generative AI (GenAI) with a group of esteemed data and AI experts. The
What happens if an employee unknowingly enters sensitive information into a public large language model (LLM)? Could that information then be leaked to other users of the same LLM? For example, if you ask ChatGPT or Claude to read and summarize a confidential contract, a patient record or a customer
Synthetic data has emerged as a powerful tool for overcoming the limitations of real-world data. The future holds great promise for accelerated innovation. With synthetic data, companies can now generate financial transactions, medical records or customer behavior patterns that maintain statistical relevance like real data. This emerging technology can help
As data decays, it becomes less useful. See how synthetic data for insurance can help.
The search to maximize our own productivity is never-ending. We all want to be more efficient in our work and carve out more time with loved ones. As you assess data and AI technology to automate processes and maximize efficiency, you may wonder if it’s truly possible for you or
Data scarcity, privacy and bias are just a few reasons why synthetic data is becoming increasingly important. In this Q&A, Brett Wujek, Senior Manager of Product Strategy at SAS, explains why synthetic data will redefine data management and speed up the production of AI and machine learning models while cutting
Stop bias in its tracks – learn about the value of synthetic data for insurance.
생성형 AI는 우리의 업무 환경과 사회를 변화시키고 있습니다. 사람과 기술이 상호작용할 새로운 방법을 제시하며 상상을 능가하는 속도로 영향을 끼치고 있죠. 최근 실시한 조사 결과는 생성형 AI에 대한 흥미로운 시각을 제시하고 있는데요, 기업 의사결정자들이 체감하는 생성형 AI의 해결 과제와 기회를 동시에 확인하실 수 있습니다. 대다수의 응답자는 GenAI를 통해 직원 만족도가 향상되었고(82%),
The ancients’ practice of publicizing set-in-stone personal records would run anathema to modern data privacy laws. These days, in lieu of using contemporary personally identifiable records, I anonymized a 4,000-year-old tax record from ancient Babylon to describe three principles for effective data anonymization at scale: Embracing rare attributes: values and
Well, there's another plot twist in the Google third-party cookie deprecation saga. After years of banter and shifting deadlines, Google has decided to abandon its plans to phase out third-party cookies from Chrome. What does this mean for marketers? Even though third-party cookies aren't being removed, Google is planning to
Digital banking, big tech and data privacy are all contributing to a shift in the Scandinavian banking scene, according to Tom Palving, Center of Excellence Lead for Digital Communication and Sales Loyalty at Jyske Bank. As a result, says Palving, traditional banks are facing a number of challenges, including: Customers
Adopting analytics and AI in the public sector is changing how governments make decisions. Technology improves the efficiency and transparency of work processes, positively impacting service delivery to increasingly demanding citizens. However, many government organizations still need help fully embracing a data-driven culture. The Covid-19 pandemic is one of the
I saw a fascinating Reddit thread titled: "What would you do if your son told you he’s dating an AI?" Here's the post verbatim: "My son (20M) just told my wife and I that he’s been in a relationship with a replika for the past few months. He claims that it’s
As organizations embrace AI, they often handle large volumes of data that power AI systems. Handling data appropriately includes implementing adequate privacy policies and security measures to protect it. Doing so prevents accidental exposure and ensures ethical data use. AI technology often uses sensitive data for creating, training and utilizing models.
Humanity collectively creates 2.5 quintillion bytes of data daily, presenting incredible opportunities for organizations—especially those who collect it in the cloud. Cloud-based data offers excellent insights for organizations, including a meaningful look at customer needs and operational improvements. However, these benefits come with risks, especially regarding security. According to IBM
Mental health and data sharing. Seeing those phrases in a single sentence gives even the most seasoned professionals pause. This is legitimately sensitive data. And there are often specialized confidentiality and privacy laws due to the stigma and discrimination against those with mental health disorders. All the same, many agencies are starting to ask
An estimated 44% of people in jail and 37% of those in prison have a mental health condition. When I worked at the San Bernardino County Department of Behavioral Health, the Sheriff and Probation Departments were close partners with us. My Research & Evaluation team worked with their data teams to evaluate
New and more prescriptive privacy and other data-related regulations are elevating data governance to a strategic asset for organizations in all sectors. Data governance can no longer remain confined to a back-end IT operation. As the data-rich financial services sector is now moving fast towards more profound digitization of financial
In the US, we often notice that what starts in California will eventually spread to the rest of the country. Whether it's related to fashion, culture or legal issues, if it starts in the golden state there's a good chance it will spread east in the US. On June 28, 2018, California Governor
Surprise! The data team does more than you think to implement certain legislative actions.
The European General Data Protection Regulation (GDPR) came into force in May 2018, and there is a debate about potential convergence between Moroccan data protection law (09-08) and the GDPR standard. This means that there is a good chance that the control and verification mechanisms set up by the National
David Loshin reminds us that data protection compliance applies to different individuals in different contexts – and not just GDPR and CCPA.
There's a chasm in today's business world between "can" and "should." Let's hope that gap closes soon.
Brush up on the latest news around data privacy. Todd Wright shares his top 10 picks.
Jim Harris discusses a key role of the data engineer – protecting sensitive personal data.
Todd Wright shares results of a SAS survey about consumers' data privacy concerns.
