Learn the work behind Data, AI & Forward Deployed Engineering
Practical explanations, career decisions and reproducible workflows. Read the reasoning, inspect the evidence and follow the next skill into a real programme.
Use AI to propose data checks and verify them independently
Use AI-generated data checks as proposals. Validate each rule against the business contract, a known-good fixture and deliberately broken examples before adopting it. A check that rejects valid business records can damag
Use an LLM to explain a chart without inventing causality
Give an LLM the chart's verified data table, metric definition and comparison rules before asking for commentary. Require it to separate observations, hypotheses and unanswered questions. A chart can show an increase wit
Use context managers to close files reliably
Use a with statement to give an open file a clear lifetime. The file is closed when control leaves the block, including when an exception propagates. That makes resource cleanup predictable and keeps ownership visible to
Use DIVIDE to make undefined business ratios explicit
A ratio is meaningful only when its numerator and denominator represent the intended population and the denominator supports division. DAX DIVIDE provides defined handling for zero or blank denominators, but you still ne
Use Docker Compose for an app and database
Compose can make a multi-service development environment repeatable, but start order alone does not mean the database is ready.
Use fixtures to isolate test data from production data
A reliable test owns its inputs. Reading a live spreadsheet or production database makes results unstable and can expose or alter real records.
Use Git to review changes to an analysis script
Review an analysis change at two levels: what the code changed and what the reported result changed. A one-character diff can alter the reporting population, while a large refactor can leave every business result unchang
Use structured tables to prevent broken spreadsheet ranges
A fixed formula such as SUM(K2:K8) describes seven specific worksheet cells. If new records arrive outside that range, the formula can keep returning a plausible but incomplete total. An Excel table gives the dataset a n
Use synthetic data when demonstrating AI analysis
Use original synthetic data to demonstrate an analytical workflow without exposing real customer records. Design the data to exercise the business rules and failure cases you want to teach, and label it clearly. A fictio
Use type hints to document an integration boundary
Type hints let callers and tools see the intended contract, but Python annotations alone do not validate untrusted JSON. Use them with explicit runtime parsing.
Validate a pandas pipeline against a tiny golden dataset
A golden dataset is a small input with independently specified expected results. Use it to test the complete transformation at its business grain, including unusual records that expose plausible mistakes.
Validate an analyst SQL query with five independent checks
A SQL query is not validated merely because it runs or matches yesterday's dashboard. It needs evidence that the intended population, grain and calculation were preserved. Useful checks should fail for different reasons,
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