Leaders need to trust data within the organization to make sound business decisions. So, many turn to master data management (MDM), a solution to get and keep uniform and accurate data that increases business value. Yet, according to Gartner, 75% of all MDM programs across organizations fail to meet business objectives. Moreover, this trend has worsened since 2015, […]
Are Data Marketplaces the Future of AI?
AI is hungry for data. But while the algorithms get smarter, the supply chain that feeds them – called data marketplaces – is quietly reshaping how we build AI models. In the past, acquiring the right datasets was an arduous process marked by silos, proprietary agreements, and endless data wrangling. Now, with the rise of digital platforms […]
Insurance for AI Liabilities: An Evolving Landscape
Most businesses expect that artificial intelligence (AI) will save money and promote efficiency as it continues to be adopted and implemented across various industries. But what these companies may not expect – and AI cannot predict – are the myriad ways that AI will result in new and increasing potential for liability. From addiction-forming or defamatory chatbots to automated hiring tools with discriminatory impact, AI-driven technologies […]
Book of the Month: “The Data Hero Playbook”
For July’s Book of the Month, we’re challenging our perspective on data leadership with “The Data Hero Playbook” by Malcolm Hawker. The subtitle is “Developing Your Career and Data SUPERPOWERS,” which gives a sense of the journey the reader is about to engage in. The book ultimately challenges a lot of long-held beliefs and practices in […]
Mind the Gap: The Many Faces of ChatGPT in the Mirror
One of the most significant areas of data ethics concern is bias in generative AI models. Concerns about algorithmic bias are not new. Associative model (i.e., neural network) bias is not new. Even the ceding of consequential decisions to these models is not new. Just a few examples: AI is used to screen resumes and evaluate […]
Why and How to Enhance DevOps with AIOps
AIOps, the practice of enhancing IT and DevOps with help from artificial intelligence and machine learning, is not an especially new idea. It has been nearly a decade since Gartner coined the term in 2016. Yet, the growing sophistication of AI technology is making AIOps much more powerful. Gone are the days when AIOps was mostly a […]
Deploying AI Models in Clinical Workflows: Challenges and Best Practices
The global healthcare AI market is projected to grow from $32.34 billion in 2024 to $431 billion by 2032. It is evident that artificial intelligence (AI) is transforming the healthcare sector, one workflow at a time. Even so, hospitals and clinics struggle to successfully integrate the technology into their workflows, as real-world deployment is fraught […]
Data Warehouse vs. Data Lakehouse
The phrase “data warehouse vs. data lakehouse” offers an exciting topic for ongoing debate in the global data management world. While businesses have relied on traditional data warehouses for storing structured and semi-structured data for years, the more recent technological solution of the data lakehouse is growing in importance because of its unique ability to provide structure to raw data. […]
The Importance of Women in Data Management
Despite the increasing participation of women in data management (DM) roles, women still confront gender-related challenges throughout their careers. One significant challenge is the persistent gender bias prevalent within the industry. According to the study USA Diversity in Data Report 2022-2023, only 26% of DM and analytics positions are held by women. Women often face stereotypes […]
Turning Data into Insights: A Smarter Playbook for Mid-Size Businesses
In today’s hyper-competitive economy, data is a critical asset that drives innovation, strategic decision-making, and competitive advantage. However, for many mid-sized organizations, turning raw data into actionable business intelligence (BI) is challenging. The rapid pace of technological advancements, coupled with increasingly complex data environments, presents significant hurdles, particularly for those with limited resources to build […]