The Coming Wave of Autonomous Data Quality (ADQ)
For a long time, data quality has been built on a simple idea: rules. If a value is missing, flag it. If a number is out of range, reject it. If a record doesn’t match what we expect, fail the pipeline. This approach made sense when data systems were smaller, slower, and far more predictable. […]
Building Strong Workplace Relationships
We dedicate a large share of our lives to our jobs. That is a lot of time to spend with people who are initially total strangers. While it’s easy to view coworkers simply as “the people who help get the job done,” the reality is that the quality of your professional relationships is often the […]
Why Compliance Can’t Fix Broken AI Products
AI risk is increasingly viewed as a compliance issue. Organizations respond with policies, review boards, checklists, and governance frameworks, assuming that stricter controls will make intelligent systems safe. This approach is reassuring but fundamentally flawed because product design creates safety, not compliance. By the time compliance enters the picture, most of the meaningful risk has […]
Modern Excel PivotTables: Accelerating Enterprise-Grade Data Analysis
Excel PivotTables have quietly gotten a lot more “modern” in the last year—especially for analysts who live in Microsoft 365. One big upgrade is the smarter, easier Recommended PivotTables experience. Microsoft replaced the older dialog with a redesigned panel that makes it simpler to preview options and adjust your data range before inserting a […]
The Role of QA in Data Analytics Projects
In data-driven organizations, analytics outputs directly influence business decisions. While tools and dashboards enable insights, Quality Assurance (QA) ensures those insights are accurate, complete, and trustworthy. Unlike traditional application testing, QA in analytics focuses on validating data integrity, not just system behavior. 🔍 How Analytics QA Is Different Traditional testing answers: Does the application […]