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Practical explanations, career decisions and reproducible workflows. Read the reasoning, inspect the evidence and follow the next skill into a real programme.
Build an RFM segmentation table with SQL
RFM describes customers using recency, frequency and monetary value. Recency measures time since the latest qualifying purchase; frequency counts qualifying purchases within a defined observation window; monetary value s
Build contract tests for an external tool integration
An integration can compile while the provider changes a field, error or timeout behaviour. Contract tests protect the application-facing adapter independently from model output.
Calculate customer cohorts in pandas and reconcile with SQL
Assign each customer to a defined starting cohort, count distinct active customers by activity period and divide by the original cohort size. Reconcile the intermediate customer-month table before comparing percentages a
Calculate customer repeat rate without double-counting visits
Repeat-customer rate needs a definition of both customer and repeat occasion. In an order-line table, two rows can belong to one order. Counting rows as visits or purchases can therefore classify a one-order customer as
CALCULATE explained through a changing filter context
CALCULATE evaluates an expression after modifying its filter context. The important question is which filters it adds, replaces or preserves. A measure can be syntactically valid while answering a different question from
Calculate return rates with the right denominator
“Return rate” is not a complete metric definition. It may mean the share of orders with a return, the share of units returned, or the value refunded as a share of eligible order value. Those measures use different numera
Calculate rolling averages without hiding missing dates
A three-row moving average is a three-day moving average only when the input has exactly one row for every relevant day. If the table contains only days with purchases, a row-based frame skips inactive dates and changes
Calculate sample size from a meaningful business effect
Choose a meaningful effect before calculating sample size. For a conversion experiment, specify the baseline probability, absolute difference, allocation ratio, significance level, desired power and unit of randomization
Calculate weighted average order value in SQL
Overall average order value is eligible order value divided by eligible order count. If you start from regional averages, weight each region by its number of eligible orders. A simple average of regional averages gives a
Calculate weighted margin instead of averaging percentages
Overall margin rate is total eligible margin divided by total eligible net value under the defined measure. Averaging category margin percentages equally gives each category the same influence regardless of its size, whi
Calibrate a grader before using it as a deployment gate
A grader score is another model output until it is compared with a trusted label. Agreement alone is insufficient when one error type matters more: a grader that misses unsafe failures can look accurate on a mostly passi
Calibrate an LLM judge against human-labelled cases
An LLM judge can scale evaluation, but it is another model with biases and failure modes. Compare it against a clear rubric and human-reviewed cases before using it in a release gate.
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