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Understand what engineering metrics measure, how teams collect them, and what the numbers can tell you about the work behind a release.
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191 termsActionable metric
Actionable metric can trigger a specific decision by a clear owner.
Engineering analyticsAggregate inference error
Aggregate inference error is an analytical risk or quality concern that can make an engineering analysis appear more certain, comparable, or causal than it is.
Engineering analyticsAggregate reversal
Aggregate reversal is an analytical risk or quality concern that can make an engineering analysis appear more certain, comparable, or causal than it is.
Engineering analyticsAggregation bias
Aggregation bias is an analytical risk or quality concern that can make an engineering analysis appear more certain, comparable, or causal than it is.
Engineering analyticsAggregation function
Aggregation function determines how observations become a summary.
Engineering analyticsAlert threshold
Alert threshold sets the boundary for notification or response.
Engineering analyticsAttribution bias
Attribution bias is an analytical risk or quality concern that can make an engineering analysis appear more certain, comparable, or causal than it is.
Engineering analyticsAutomatic instrumentation
Automatic instrumentation adds telemetry through libraries or agents.
Engineering analyticsAvailability bias
Availability bias is an analytical risk or quality concern that can make an engineering analysis appear more certain, comparable, or causal than it is.
Engineering analyticsBackfill
Backfill loads or recomputes historical records after a repair.
Engineering analyticsBaseline regression
Baseline regression is an analytical risk or quality concern that can make an engineering analysis appear more certain, comparable, or causal than it is.
Engineering analyticsBenchmark baseline
Benchmark baseline is an analytical concept for using reference values to understand engineering performance, variation, or capability.
Engineering analyticsBenchmark cohort
Benchmark cohort is an analytical concept for using reference values to understand engineering performance, variation, or capability.
Engineering analyticsBenchmark comparability
Benchmark comparability is an analytical concept for using reference values to understand engineering performance, variation, or capability.
Engineering analyticsBenchmark confidence
Benchmark confidence is an analytical concept for using reference values to understand engineering performance, variation, or capability.
Engineering analyticsBenchmark distribution
Benchmark distribution is an analytical concept for using reference values to understand engineering performance, variation, or capability.
Engineering analyticsBenchmark drift
Benchmark drift is an analytical concept for using reference values to understand engineering performance, variation, or capability.
Engineering analyticsBenchmark gaming
Benchmark gaming is an analytical concept for using reference values to understand engineering performance, variation, or capability.
Engineering analyticsBenchmark interpretation
Benchmark interpretation is an analytical concept for using reference values to understand engineering performance, variation, or capability.
Engineering analyticsBenchmark normalization
Benchmark normalization is an analytical concept for using reference values to understand engineering performance, variation, or capability.
Engineering analyticsBenchmark percentile
Benchmark percentile is an analytical concept for using reference values to understand engineering performance, variation, or capability.
Engineering analyticsBenchmark quality
Benchmark quality is an analytical concept for using reference values to understand engineering performance, variation, or capability.
Engineering analyticsBenchmark range
Benchmark range is an analytical concept for using reference values to understand engineering performance, variation, or capability.
Engineering analyticsBenchmark sample size
Benchmark sample size is an analytical concept for using reference values to understand engineering performance, variation, or capability.
Engineering analyticsBenchmark target
Benchmark target is an analytical concept for using reference values to understand engineering performance, variation, or capability.
Engineering analyticsCherry-picking
Cherry-picking is an analytical risk or quality concern that can make an engineering analysis appear more certain, comparable, or causal than it is.
Engineering analyticsCohort attrition
Cohort attrition is an analytical concept for separating engineering observations into populations whose differences may matter to a decision.
Engineering analyticsCohort comparison
Cohort comparison is an analytical concept for separating engineering observations into populations whose differences may matter to a decision.
Engineering analyticsCohort definition
Cohort definition is an analytical concept for separating engineering observations into populations whose differences may matter to a decision.
Engineering analyticsCohort maturation
Cohort maturation is an analytical concept for separating engineering observations into populations whose differences may matter to a decision.
Engineering analyticsCohort retention
Cohort retention is an analytical concept for separating engineering observations into populations whose differences may matter to a decision.
Engineering analyticsCohort survivorship
Cohort survivorship is an analytical concept for separating engineering observations into populations whose differences may matter to a decision.
Engineering analyticsCohort window
Cohort window is an analytical concept for separating engineering observations into populations whose differences may matter to a decision.
Engineering analyticsComparison Group
Comparison Group is an analytical concept for separating engineering observations into populations whose differences may matter to a decision.
Engineering analyticsCompleteness rate
Completeness rate measures the present share of an expected data population.
Engineering analyticsConfirmation bias
Confirmation bias is an analytical risk or quality concern that can make an engineering analysis appear more certain, comparable, or causal than it is.
Engineering analyticsCorrelation and causation
Correlation and causation is an analytical risk or quality concern that can make an engineering analysis appear more certain, comparable, or causal than it is.
Engineering analyticsCorrelation ID
Correlation ID associates related records across systems.
Engineering analyticsCount metric
Count metric records how many defined events or entities occur.
Engineering analyticsCumulative metric
Cumulative metric shows a running total across time or population.
Engineering analyticsDashboard
Dashboard curates measures, context, and navigation for a decision.
Engineering analyticsDashboard hygiene
Dashboard hygiene keeps metric views accurate, current, and understandable.
Engineering analyticsData accuracy
Data accuracy asks whether records reflect the real event or value.
Engineering analyticsData availability
Data availability measures whether an expected data asset can be accessed and used.
Engineering analyticsData catalog
Data catalog inventories assets with owners, schemas, lineage, freshness, and access.
Engineering analyticsData collector
Data collector receives, processes, and forwards observations.
Engineering analyticsData consistency
Data consistency keeps related fields and records compatible across sources.
Engineering analyticsData contract
Data contract agrees schema, meaning, quality, ownership, and change handling.
Engineering analyticsData contract testing
Data contract testing how to test a data contract before it breaks analytics.
Engineering analyticsData dictionary
Data dictionary documents field meanings, types, units, and allowed values.
Engineering analytics