You never know what’s going to happen when you click on a LinkedIn job posting button. I’m always on the lookout for interesting and impactful projects, and one in particular caught my attention: “Far North Enterprises, a global fabrication and distribution establishment, is looking to modernize a very old data environment.” I clicked the button […]
5 Data Management Tool and Technology Trends to Watch in 2025
The market surrounding data management tools and technologies is quite mature. After all, the typical business has been making extensive use of data to help streamline its operations and decision-making for years, and many companies have long had data management tools in place. But that doesn’t mean that little is happening in the world of […]
Technical and Strategic Best Practices for Building Robust Data Platforms
In the AI era, organizations are eager to harness innovation and create value through high-quality, relevant data. Gartner, however, projects that 80% of data governance initiatives will fail by 2027. This statistic underscores the urgent need for robust data platforms and governance frameworks. A successful data strategy outlines best practices and establishes a clear vision for data architecture, […]
Chatbot Quality Control: Why Data Hygiene Is a Necessity
The rush is on to deploy chatbots. Chatbots rely on data to power their outputs; however, companies that prioritize data quantity over quality risk creating systems that produce unreliable, inappropriate, and simply incorrect responses. Success in this field depends on rigorous data standards and ongoing quality control rather than simply accumulating more training data. When […]
The Impact of Advanced Data Lineage on Governance
In today’s data-driven business landscape, data quality – the availability of usable and business-ready information – remains a significant and worsening challenge for many organizations. To mitigate these effects, businesses need swift resolution of data issues with transparent and trustworthy information. However, in our fast-paced digital environment, complex data architectures with more system variables make it difficult to understand the problems. […]
AI Data Governance Spotlights Privacy and Quality
The emergence of artificial intelligence (AI) brings data governance into sharp focus because grounding large language models (LLMs) with secure, trusted data is the only way to ensure accurate responses. So, what exactly is AI data governance? Let’s define “AI data governance” as the process of managing the data product lifecycle within AI systems. To keep it […]
It’s Essential – Verifying the Results of Data Transformations (Part 1)
Today’s data pipelines use transformations to convert raw data into meaningful insights. Yet, ensuring the accuracy and reliability of these transformations is no small feat – tools and methods to test the variety of data and transformation can be daunting. Transformations generally involve changing raw data that has been cleansed and validated for use by […]
Common Data Integrity Issues (and How to Overcome Them)
To say data has “integrity” means that it can be trusted and relied upon and is ultimately useful. Data integrity also conveys a sense of unity and completeness. The greatest challenges to ensuring that data has integrity are any characteristics or events that detract from the data’s usefulness, trustworthiness, and reliability, as well as anything […]
Innovating with Data Mesh and Data Governance
Large organizations want to create a flexible environment to innovate and respond quickly based on new data insights. But at the same time, these businesses want some structure for good Data Quality, data fit for consumption, simplifying and speeding up data access. Using a data mesh, which is a decentralized data architecture (collecting, integrating, and analyzing […]
Navigating the Sea of Data Mapping Solutions
This is the third and final blog post in my “Charting a Course Through the Data Mapping Maze.” If you’ve been following the previous posts, thanks for joining me on this journey. Part one defined data mapping and outlined key components and why it’s essential. Part two explored how data mapping works, the common techniques used, […]