John Kerski's Blog

Automated Testing for Broken Visuals with Microsoft Playwright and Azure DevOps In my previous article, I explained how to run...

Automated Testing for Broken Visuals with Microsoft Playwright Figure 1 This image plagues my dreams, a grey box of death...

Multiple Value Parameters in Paginated Reports Paginated Reports offer us the ability to generate near pixel-perfect exports of our reports...

I need better equipment… that was the first line of my first blog post back in July of 2021. My...

Weaving DataOps into Microsoft Fabric – Logging Test Results to OneLake In my last article, I reviewed how to automate testing...

Microsoft Most Valuable Professional (MVP) I’m honored to receive a Microsoft Most Valuable Professional (MVP) award this year. When I...

Weaving DataOps into Microsoft Fabric – Invoke-DQVTesting and Orchestration In my last article, I discussed how to automate testing on your...

Weaving DataOps into Microsoft Fabric – Invoke-DQVTesting If you are building tests in Power BI and automating those tests in Azure...

Weaving DataOps into Microsoft Fabric - Automating DAX Query View Testing Pattern with Azure DevOps In my last article, I...

Weaving DataOps into Microsoft Fabric - DAX Query View Testing Pattern The last three months of Power BI Desktop releases...

Part 35 – Commenting Power Query with Azure OpenAI Leveraging Artificial Intelligence (AI) to reduce cycle times. Over the past...

Revisiting Fabric: DataOps Principles in the Newest Microsoft Analytics Solution When Microsoft unveiled the Public Preview of Fabric in May,...

Bringing “Quality is Paramount” for Gen1 Dataflows Continuing from Part 33, where I introduced the polling method for implementing version...

Make It Reproducible… for Gen1 Dataflows While I look forward to all the new capabilities Gen2 dataflows offer, it may...

The Data Journey: Don’t Assume What Worked Last Week Will Work Today Microsoft technologies and application programming interfaces (APIs) are...

DataOps Principle #14 - Analytics is manufacturing Exciting developments are underway for Microsoft users, with the recent announcements of Power...

DataOps 101 on YouTube Over the past year during meetups and conferences, I have had the opportunity to introduce the...

Quality is Paramount and the Cell-Level Error Cell-Level errors (like the one in Figure 1) are things of nightmares to...

How DataOps is woven into the Microsoft Fabric Last week, there was a wave of awesome news that has come...

DataOps Principle #8 - Reflect As promised from Part 27, I said I would offer tips on pulling SharePoint verison...

DataOps Principle #8 - Reflect As I stated in Part 26 of this ever-growing series (a real journey), my colleagues,...

DataOps Principle #16 - Monitor Quality and Performance For many of us we live in an E3/G3 world.  So, what...

DataOps Principle #18 – Improve Cycle Times Late in September 2022, I had the chance to meet with Mathias Thierbach,...

DataOps Principle #16 - Monitor Quality and Performance Over the past year I’ve been leveraging Application Insights on my blog...

DataOps Principle #14: Analytics is Manufacturing “Let’s switch gears” We’ll take a break from talking about dataflows and turn attention...

DataOps Principle #10: Orchestration In my last two entries I explained a way to integrate Power BI dataflows into source...

DataOps Principle #15: Quality is Paramount In my last entry I explained how to update a dataflow in the Power...

DataOps Principle #4: It’s a team sport Despite the negativity and seedy underbelly that comes with social media, it does...

Bringing DataOps to Power BI on YouTube Earlier this year I began a project to put part of this blog...

Distractions, DataOps, and Documentation If you have read Part 1 of this series, you probably know that I like to...

DataOps Principle #1: Continually satisfy your customer It’s complicated… that’s how I would sum up my relationship with SharePoint. On...

DataOps Principle #9: Analytics is code (cont., cont.) I love Regular Expressions… but I’ve been told I may lean on...

DataOps Principle #9: Analytics is code (cont.) And now we address Challenge #2… In Part 14 I identified the challenge...

DataOps Principle #9: Analytics is code Now how did that get there?… A client asked me about a new column...

DataOps Principle #17: Reuse “Don’t lose it, reuse it!”… is a catchphrase from a popular show that my little one...

DataOps Principle #7: Reduce heroism “You saved the day!”… one of our clients told my teammate. We had attended a...

DataOps Principle #14: Analytics is Manufacturing (cont.) “Time is money”… Continuing our work from Part 10 we have the data...

DataOps Principle #14: Analytics is Manufacturing “Patience is a virtue”… I am not a patient person. Red lights at traffic...

DataOps Principle #8: Reflect (cont.) “What gets measured gets done”… I’ve seen that message numerous times over my career and,...

DataOps Principle #8: Reflect I’m on a ship with no compass… that’s how I felt about our testing. Our team...

DataOps Principle #3: Embrace Change Change is constant… and the Power BI team at Microsoft has taken this idea and...

DataOps Principle #13: Simplicity We lacked consistency… a senior developer tells me this after he reviewed some of the Power...

DataOps Principle #10: Orchestrate Let’s Orchestrate… If you have read Part 3 and Part 4 of this series, you’ve probably...

DataOps Principle #15: Quality is Paramount Yep, I did it to myself… I thought I had fixed an issue in...

DataOps Principle #11 – Make it reproducible I am panicked… it has been a long week at work and a...

DataOps Principle #16 - Monitor for Quality and Performance Now before I talk about this principle, I would like to...

I need better equipment… I tell myself while trying to jog off the extra pounds I gained in 2020. The...