Welcome to the latest edition of Mind the Gap, a monthly column exploring practical approaches for improving data understanding and data utilization (and whatever else seems interesting enough to share). Last month, we explored the rise of the data product. This month, we’ll look at data quality vs. data fitness. Everybody likes a pithy definition. Marketers describe […]
How to Design a Dynamic Data Archival System for Maximum Results
Today’s business landscape continues to become more data-driven. The fact is that the quality of enterprise data defines modern organizations. Business growth stems from proficient data management and analysis. For organizations to thrive, it’s critical for an efficient data archival solution to be in place to satisfy customer demands and attain company goals. Because of […]
Leveraging Data to Unlock Hidden Growth with Data Mesh, Data Fabric, and Knowledge Graphs
Among business leaders today there is a persistent fear of missing out on something transformative. They know they are sitting on a goldmine of data; they know this data could conceivably be turned to profitable ends. What they struggle to do is leverage this data. And the more time they waste, the worse the problem gets because […]
Understanding the Potential Failures of a Data Governance Program
Implementing a successful data governance program is essential for any organization that wants to manage its data effectively. However, these programs can sometimes fail, often due to issues related to key business drivers. In the pursuit of effective data management, many organizations overlook the practical realities and challenges that can significantly impact their success. While […]
Data Privacy Compliance Is an Opportunity, Not a Burden
The consumer privacy landscape is constantly evolving. Potential regulations like the American Data Privacy and Protection Act (ADPPA), which resemble current laws set forth by the General Data Protection Regulation (GDPR), are keeping marketers on their toes. Meanwhile, other major trends dictating how and when marketers interface with consumer data are on the horizon (such […]
How to Ask Great Questions with a Data Science Lens
When it comes to solving business problems, data scientists understand how crucial it is to formulate the right business question. While it’s easy to get sidetracked by intriguing data trails, the most effective questions are those that align closely with organizational priorities, provide actionable insights, and guide strategic decisions. Here are the key principles for crafting high-impact […]
Cloud Computing and Business Strategy: How to Align for Maximum Impact
Today’s modern business landscape is fiercely competitive, and companies are wielding cloud computing as a strategic weapon to gain an edge. Cloud computing has revolutionized how businesses operate, offering on-demand access to a vast pool of IT resources – storage, servers, databases, networking, and software – all securely delivered over the internet. Imagine ditching expensive […]
Taking the Chill Out of Selecting the Appropriate Iceberg Data Catalog
Over the past few years, the industry has increasingly recognized the need to adopt a data lakehouse architecture because of the inherent benefits. This approach improves data infrastructure costs and reduces time-to-insight by consolidating more data workloads into a single source of truth on the organization’s data lake. This is made possible by data lakehouse table […]
From Complexity to Clarity: GenAI Decodes Clinical Trial Data
As AI matures and becomes more integrated into clinical trial operations, generative AI (GenAI) technology is ushering in a new era for clinical research and drug development, redefining the clinical trial landscape and offering a quantum leap in efficiency and precision. This innovative technology streamlines every phase, transforming traditionally time-consuming processes into swift, automated workflows. […]
Generative AI and Data: Using Knowledge Graphs and RAG Together
Generative AI has huge potential, but it also faces problems. If generative AI creates information that is not factually accurate in response to a user request – resulting in so-called hallucinations – it can have a big impact on users. Relying on large language model (LLM) training data on its own is not enough to prevent […]