The 6 Dimensions of Data Quality - Completness
Missing data can look perfectly normal. How completeness failures distort analysis and the decisions that follow.
Read the essayData. Thinking. Better decisions.
The data is only half the story.
I’m Tal Mizrachi. I write about the questions, judgment, and occasional wrong turns that make data work worth doing.
Data scientist · Educator & mentor · Creator of XP Lab
From the notebook
Fresh thinking
Practicing Data Analysis Is Broken Too (Not Just Hiring)
Most analyst practice trains execution on clean toy problems instead of judgment under ambiguity.
Read the essay
AI Broke Your Hiring Signals (You Just Haven’t Noticed Yet)
LLMs made polished take-homes and portfolios easier to fake, which breaks many old hiring signals.
Read the essaySame data. Different questions.
For people who think with data.
01
Data professionals
Frame the problem, question the assumptions, and turn an analysis into a decision you can defend.
02
Data educators
Teach the thinking behind the tools. Make room for ambiguity, mistakes, and curiosity.
03
Data managers
Recognize analytical ability, develop your people, and ask better questions of the work.
A good place to start
Questions worth sitting with.
A few essays on what happens before the query, behind the dashboard, and after the confident answer.
010203
Start by Not Touching the Data
Good analysis often starts by clarifying the question and the business context before touching the dataset.
Why Hiring Data Analysts Is Still Broken (And We Pretend It’s Not)
Many analyst hiring processes still reward presentation polish and credential proxies over analytical judgment.
The 6 Dimensions of Data Quality - Completness
Missing data can look perfectly normal. How completeness failures distort analysis and the decisions that follow.
From ideas to actual practice
Better thinking takes real practice.
I built XP Lab around the ideas I write about here: open-ended problems, imperfect data, and feedback on how you think. A place for analysts, educators, and teams to practice the actual work.
Meet XP Lab →Follow your curiosity
Find your thread.
The person behind the pixels
Hi, I’m Tal.
Data scientist, educator, and mentor. I try to make analytical methods and data science accessible, useful, and fun. Curiosity welcome. Dad jokes included.
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