You're a Data Analyst. How Can You Be Sure You Have Quality Data?
Start with QUESTIONS not DATA. Put your data down. Ask yourself and stakeholders: What questions do we need to answer?
You're a data analyst. How can you be sure you have quality data? Start with QUESTIONS, not DATA. Put your data down. Ask yourself and your stakeholders: What questions do we need to answer?
Reflecting on the questions you have might lead you in surprising data directions.
For example, to find *new* ideas, you might need expansive, messy, serendipitous data sources.
Or, you might find you don't have the right data. Get it now. Clean it later.
Or, you may have the data you need. But wait: don't dive in yet. Forge your questions into a thesis: what are you trying to prove, disprove, or distill from data?
Take your time. This problem formulation stage is just as important as correcting flaws in data.
With your questions and thesis in tow, you're ready for data quality. GO!
LinkedIn recently named me a “Top Voice in Data Analytics.” They ask me to answer questions like this in less than 750 characters, and I love the challenge of writing rapid-fire, quick-hitting answers.
Here are the other answers to this question on LinkedIn.
a database buried in the dirt --ar 16:9