query-design

작성자: microsoft

DAX 데이터 가져오기와 TypeScript 프레젠테이션을 분리합니다. 집계, 총 행, FORMAT() 등에 DAX, TypeScript, Vega-Lite 중 무엇을 사용할지 안내합니다.

npx skills add https://github.com/microsoft/fabric-apps-analytic-templates --skill query-design

Query Design — Separation of Data and Presentation

DAX computes and fetches data. TypeScript shapes it for display. VegaVisual and DataGrid render it.

Aggregate in DAX to the visual's grain — never fetch lower-grain rows to roll up client-side. When a visual layout changes, only the TypeScript or spec layer should change — not the DAX query.

Responsibility Matrix

ConcernOwner
Semantic measures (SUM, DISTINCTCOUNT, etc.)DAX
Filters and slicersDAX or TypeScript (see Filter Strategy)
Grouping grain (SUMMARIZECOLUMNS)DAX
Time intelligence (YTD, YoY)DAX
TopN / payload reductionDAX
Deterministic row ordering (ORDER BY)DAX (for debugging — not presentation sort)
Partitioning a flagged result tableTypeScript
Coordinating separate query resultsTypeScript (one hook call per result table)
Server-provided grand totals (preferred, supports all aggregation types)DAX + TypeScript row partitioning
DataGrid-computed grand totalsDataGrid (alternative only for additive sum values or a count of fetched leaf rows)
Filling dimension gapsTypeScript (stitch dimension list into sparse results)
Reshaping (pivot, unpivot)TypeScript
Column display namescolumnMetadata in factory file
Number/date formattingcolumnMetadata.format / Vega-Lite spec
User-facing sort orderTypeScript / Vega-Lite sort / DataGrid sort
Decorative labels, iconsDataGrid cellRenderer or Vega-Lite condition
Axis titles, legends, color encodingVega-Lite spec

Rules

Must

  • Aggregate in DAX to the visual's grain — never fetch lower-grain rows just to roll them up to that grain in TypeScript
  • One EVALUATE per .dax file; use ROLLUPADDISSUBTOTAL when DataGrid body and grand-total grains share one result table
  • ORDER BY in DAX for stable, diffable results — not presentation sort
  • Same filters/measures across related split-grain queries to prevent drift

Prefer

  • SUMMARIZECOLUMNS for grouped aggregation — it also drops BLANK-measure rows, keeping payloads small
  • DAX's natural column names ('Table'[Column], [Measure]) mapped via columnMetadata.displayName
  • Raw typed values from DAX — format via columnMetadata.format or Vega-Lite, never FORMAT()
  • Model-defined format strings (from INFO.VIEW.MEASURES()) over invented ones
  • Multiple lightweight queries for independently shaped datasets; one flagged rollup query for a DataGrid body and grand total
  • User-facing sort in TypeScript / Vega-Lite / DataGrid — never re-query for sort

Avoid

  • SELECTCOLUMNS solely for renaming — use columnMetadata.displayName instead
  • UNION to mix body and total grains — use ROLLUPADDISSUBTOTAL and partition its flagged rows
  • FORMAT() in DAX — converts to text, breaks sorting and charting
  • Converting BLANK to 0 / "" / "N/A" in DAX — causes result-set explosion
  • CONCATENATEX, UNICHAR, emoji prefixes — decorative text belongs in cellRenderer or Vega-Lite
  • Fetching all members of high-cardinality dimensions just to fill gaps

Decision Flowchart

Need to add something to the query result?
  |-- Calculation / aggregation / filter?
  |     -> DAX (measures, CALCULATE, SUMMARIZECOLUMNS)
  |-- Interactive filter the user controls?
  |     -> Low-cardinality: widen grain, filter in TypeScript or Vega-Lite transform
  |     -> High-cardinality: push filter to DAX, re-query
  |-- Adding a DataGrid grand total?
  |     -> DAX rollup query: split body and total rows with toRollupDataTables
  |        and always pass the returned grandTotalTable via grandTotals.data
  |     -> DataGrid-computed sum/count: pass grandTotals without data and set defaultAggregation
  |-- Merging datasets or adding other synthetic rows?
  |     -> Charts: pass multiple DataTables to VegaVisual, layer in spec
  |     -> Grids: append rows in TypeScript, style via cellRenderer
  |-- Renaming a column for display?
  |     -> columnMetadata in the factory file (displayName)
  |-- Formatting, labeling, or encoding?
  |     -> Vega-Lite spec or DataGrid cellRenderer
  |-- Decorating values (icons, status badges, null placeholders)?
  |     -> DataGrid cellRenderer or Vega-Lite condition encoding
  |-- Not sure?
        -> Does it change what the data *means* (filter, measure, grain)? -> DAX
           Does it change only how data is *rendered* (labels, icons, layout)? -> TypeScript / Vega-Lite spec / DataGrid cellRenderer
           Still unclear? -> Read the relevant reference above

Interactivity

Reports coordinate multiple visuals: a selection in one changes what the others show. Two distinct behaviors, with different data work behind them:

  • Cross-filtering — a selection in one visual constrains the data shown in another, removing or narrowing the non-matching rows from the target's view. The target shows less. Applying that constraint is a cost/cardinality tradeoff — widen the grain and filter client-side, or push the filter into DAX and re-query. See Filter strategy.
  • Cross-highlighting — a selection in one visual emphasizes the matching subset within another while the full context stays visible. The target keeps its baseline (dimmed) and draws the selected subset bright on top. The subset is a separate aggregation aligned to the baseline's grouping, measures, and row set — not a client-side filter of the baseline. See Highlight queries.

Both consume the predicate-based selection events the visual components emit (onInteraction). The components render only the DataTables they are handed; this skill produces those tables. For how a spec binds and layers multiple datasets, see the visuals skill's multi-data input reference.

Reference Materials

Read these when working on a specific topic:

  • Anti-patterns and corrections — Open when reviewing a query that uses UNION for totals, FORMAT(), SELECTCOLUMNS for renaming, CONCATENATEX/emoji decoration, BLANK-to-0 conversion, or GENERATE/CROSSJOIN for gap-filling.
  • Multi-grain patterns — Open when a single visualization needs data at multiple grains (e.g., bars + reference line, region detail + total row, monthly trend + YTD), to choose between one flagged rollup result and separate queries while keeping related factories, hooks, and DataTables aligned.
  • Filter strategy — Open when adding a user-controlled filter or implementing cross-filtering, and deciding whether to widen the grain (filter client-side) or push the filter into DAX (re-query on each change).
  • Highlight queries — Open when writing the "selected subset" overlay query for a cross-highlight visual: an aligned CALCULATETABLE / TREATAS query whose rows match the baseline.
  • Format strings — Open when picking a columnMetadata.format value, when a measure has a dynamic format string, or when formatting needs to flow into a Vega-Lite axis.

Integration with Sibling Skills

  • schema-discovery — Schema exploration; discover tables, columns, and relationships before writing queries.
  • dax-authoring — DAX syntax, query patterns, and testing workflow. Apply this skill's principles when deciding what DAX should compute.
  • visuals — Vega-Lite specs and DataGrid configuration. Push formatting and labels into specs, not DAX.

microsoft의 다른 스킬

oss-growth
microsoft
OSS 성장 해커 페르소나
agent-framework-azure-ai-py
microsoft
Microsoft Agent Framework Python SDK(agent-framework-azure-ai)를 사용하여 Azure AI Foundry 에이전트를 구축합니다. AzureAIAgentsProvider로 지속적 에이전트를 만들 때, 호스팅 도구(코드 인터프리터, 파일 검색, 웹 검색)를 사용할 때, MCP 서버를 통합할 때, 대화 스레드를 관리할 때, 또는 스트리밍 응답을 구현할 때 사용합니다. 함수 도구, 구조화된 출력, 다중 도구 에이전트를 다룹니다.
development
airunway-aks-setup
microsoft
Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: "setup AI Runway", "onboard AKS cluster", "install AI Runway", "airunway setup", "deploy model to AKS", "GPU inference on AKS", "KAITO setup on AKS", "run LLM on AKS", "vLLM on AKS", "set up model serving on AKS", "AI Runway controller".
devops
appinsights-instrumentation
microsoft
Azure Application Insights로 웹앱을 계측하기 위한 지침입니다. 원격 분석 패턴, SDK 설정, 구성 참조를 제공합니다. WHEN: 앱 계측 방법, App Insights SDK, 원격 분석 패턴, App Insights란 무엇인가, Application Insights 지침, 계측 예시, APM 모범 사례.
devops
applicationinsights-web-ts
microsoft
브라우저/웹 앱을 Application Insights JavaScript SDK(@microsoft/applicationinsights-web)로 계측합니다. Real User Monitoring(RUM) — 페이지 뷰, 클릭, AJAX/fetch 종속성, 예외, 사용자 지정 이벤트, 백엔드 OpenTelemetry 트레이스와 상관관계가 있는 브라우저 측 GenAI 에이전트 트레이스에 사용합니다. SDK Loader Script 및 npm 설정, 프레임워크 확장(React, React Native, Angular), Click Analytics, 텔레메트리 이니셜라이저, 브라우저에서 생성된 에이전트/도구/모델 스팬에 대한 OTel GenAI 의미론적 규칙을 다룹니다.
devops
azure-ai-anomalydetector-java
microsoft
Azure AI Anomaly Detector SDK for Java로 이상 탐지 애플리케이션을 구축하세요. 단변량/다변량 이상 탐지, 시계열 분석 또는 AI 기반 모니터링을 구현할 때 사용하세요.
development
azure-ai-language-conversations-py
microsoft
azure-ai-language-conversations Python SDK를 사용하여 대화형 언어 이해(CLU)를 구현합니다. ConversationAnalysisClient로 대화 의도와 엔터티를 분석하거나, NLP 기능을 구축하거나, 애플리케이션에 언어 이해를 통합할 때 사용합니다.
development
azure-ai-ml-py
microsoft
Azure Machine Learning SDK v2 for Python. ML 작업 영역, 작업, 모델, 데이터 세트, 컴퓨팅 및 파이프라인에 사용합니다. 트리거: "azure-ai-ml", "MLClient", "workspace", "model registry", "training jobs", "datasets".
development