Cracking the Data BA Code — A Cheatsheet

Analysts looking over charts, trying to make sense
What Stories Does the Data Tell? Image credits- <a href=’'>Business statistics vector created by freepik —</a>
Cheat Sheet Image credits- <a href=’'>Paper icon vector created by —</a>
  1. What is the purpose of collecting or analysing this data? What are the business questions this data will help us answer?
  2. What is the source of the data? How will they send data? What is the frequency of the data? What is the expected quality of the data-at-source?
  3. Is the single source of data enough to be useful? Do we need to “blend” data in from other sources or get it from some third-party sources?
  4. Is it a go-forward ingestion or do we need to ingest history?
  5. What transformations does this data need to go through? What cleansing or validation would need to be in place?
  6. What are any applicable compliance or regulatory requirements around this data? How would we honour those requirements, when we receive requests to delete the data?
  7. How frequently and with what concurrency will the data be accessed, once we ingest it?
  8. What partitioning would we need to consider? What sort of queries are the most expected, to help guide the partitioning strategy?
  9. What should the strategies around managing governance, auditing?




Product analyst. Agile enthusiast. ThoughtWorker. Wrote a book. Behind 9 products gone live!

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Abhishek Mishra

Abhishek Mishra

Product analyst. Agile enthusiast. ThoughtWorker. Wrote a book. Behind 9 products gone live!

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