Use when Power Query queries need explicit load contracts for source object keys, columns, types, culture, refresh mode, gateway, privacy, folding, reconciliation, and failure handling.
원문 언어: 영어
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이 저장소의 skills
SkillsMP는 rweisssieker-xp/PowerBi-Codex-Plugin에서 259개의 skill을 수집했습니다. skill을 열어 소스와 세부 정보를 확인하세요.
rweisssieker-xp/PowerBi-Codex-Plugin수집된 skill 259개 중 40개를 표시합니다.
Use when Power Query queries need explicit load contracts for source object keys, columns, types, culture, refresh mode, gateway, privacy, folding, reconciliation, and failure handling.
원문 언어: 영어
Use when building Power BI process digital twins for bottlenecks, what-if scenarios, capacity, delivery delay, cash impact, inventory, escalations, and process improvement simulation.
원문 언어: 영어
Use when generating reusable Power BI process packs such as O2C, P2P, R2R, Plan2Produce, Dock2Stock, Complaint2CAPA, Maintain2Operate, or Control2Evidence.
원문 언어: 영어
Use when regulated BI artifacts need audit evidence for KPI changes, source lineage, tests, approvals, AI recommendations, human confirmation, SOX, GxP, ISO, GDPR, or similar controls.
원문 언어: 영어
Use when consolidating duplicate Power BI reports, finding retirement candidates, identifying target semantic models, and planning migration away from report sprawl.
원문 언어: 영어
Use when a Power BI report should be reviewed like a senior report designer for visual choice, information density, hierarchy, drilldowns, actionability, accessibility, and mobile usability.
원문 언어: 영어
Use when Power BI refresh failures need automated diagnosis and fix planning for credentials, gateway, schema drift, API pagination, timeout, privacy levels, type conversion, or missing files/sheets.
원문 언어: 영어
Use when two Power BI semantic model versions must be compared for breaking changes in TMDL, measures, columns, relationships, RLS/OLS, display metadata, or report impact.
원문 언어: 영어
Use when creating or selecting reusable Power BI semantic model patterns such as O2C, P2P, R2R, inventory snapshot, SCD, bridge table, role-playing date, or calculation group patterns.
원문 언어: 영어
Use when source-system objects, tables, APIs, joins, status logic, document flow, delta mechanisms, and common data quality issues must be identified for Power BI modeling.
원문 언어: 영어
Use when Power BI tenant assets must be analyzed for duplicate reports, stale usage, orphaned owners, refresh failures, risky sharing, expensive models, or consolidation candidates.
원문 언어: 영어
Use when selecting Power BI data-source connectors and comparing Import, DirectQuery, Direct Lake, incremental refresh, gateway, SSO, folding, privacy, and refresh limitations.
원문 언어: 영어
Use when a Power BI solution must generate native Power Query connector patterns for any Power BI-supported source, including Excel, files, databases, Fabric, Azure, Power Platform, SaaS, OData, REST, ODBC/OLE DB, semantic models, and custom connectors.
원문 언어: 영어
Use when Power BI work needs Power Query M designs or code for APIs, SAP OData, SQL, files, pagination, incremental refresh, schema drift, error handling, typing, and folding.
원문 언어: 영어
Use when interviewing a Process Owner or Process Manager to turn process goals, pain points, decisions, KPIs, sources, owners, targets, and exceptions into a Power BI build scope.
원문 언어: 영어
Use when a Power BI solution needs metadata discovery for SAP, Salesforce, Dynamics/Dataverse, Power BI/Fabric, SQL databases, OData feeds, REST APIs, files, warehouses, lakehouses, or semantic models before designing reports.
원문 언어: 영어
Use when Power BI usage telemetry should drive AI recommendations for report training, redesign, consolidation, retirement, communication, or role-based enablement.
원문 언어: 영어
Use when Power BI issues need AI-generated remediation plans for refresh failures, DAX bugs, model defects, RLS gaps, performance problems, source drift, or documentation failures.
원문 언어: 영어
Use when Power BI decisions, KPI definitions, model patterns, source mappings, incidents, fixes, and best practices must be retained across projects and reused safely.
원문 언어: 영어
Use when Power BI must prepare boardroom or executive meetings with KPIs, variance, root causes, risks, scenarios, decisions, actions, and evidence-backed narratives.
원문 언어: 영어
Use when AI should estimate financial or operational impact of KPI changes, process actions, data-quality issues, policy changes, capacity shifts, or scenario decisions.
원문 언어: 영어
Use when Power BI models, process chains, roles, or source metadata should generate role-specific management questions for executives, process owners, analysts, and operators.
원문 언어: 영어
Use when Power BI or Fabric capacity needs AI recommendations for model splitting, aggregations, Direct Lake, Import, refresh windows, query reduction, and cost optimization.
원문 언어: 영어
Use when Power BI users suspect a business driver and need AI-assisted causal plausibility checks instead of simple correlation claims.
원문 언어: 영어
Use when Power BI reports, semantic models, AI outputs, sharing, exports, RLS, labels, PII, SOX, GDPR, audit evidence, or governance policies need AI-assisted compliance review.
원문 언어: 영어
Use when Power BI standards should learn from report reviews, tickets, UAT defects, KPI conflicts, user feedback, usage telemetry, quality gates, and delivery retrospectives.
원문 언어: 영어
Use when Power BI needs AI mapping of dependencies across O2C, P2P, production, quality, finance, service, supply chain, HR, ESG, and maintenance processes.
원문 언어: 영어
Use when BI, IT, data owners, and business teams need AI-assisted negotiation of fields, keys, quality thresholds, freshness, ownership, and blocking rules for Power BI data contracts.
원문 언어: 영어
Use when Power BI data product owners need AI support for SLA, quality, roadmap, usage, incidents, certification, stakeholder feedback, and escalation management.
원문 언어: 영어
Use when data stewards need AI prioritization of data quality issues, owner assignment, correction backlog, root-cause grouping, SLA tracking, and retest plans.
원문 언어: 영어
Use when Power BI KPIs, reports, close packages, monthly reviews, board packs, or process cockpits need AI-generated management narratives grounded in evidence.
원문 언어: 영어
Use when complex DAX measures need explanations for business users, developers, auditors, data owners, or certification evidence.
원문 언어: 영어
Use when decisions made from Power BI reports, AI narratives, scenarios, or KPI alerts need later audit for traceability, effectiveness, evidence, and learning.
원문 언어: 영어
Use when Power BI should learn internal benchmarks by plant, region, product, customer, supplier, process, team, or time period from historical enterprise data.
원문 언어: 영어
Use when Power BI exceptions, KPI breaches, anomalies, overdue items, or process bottlenecks should become prioritized business actions with owner, due date, impact, and retest condition.
원문 언어: 영어
Use when Power BI tasks should be scored for whether AI/plugin automation, self-service, CoE, IT, or senior expert work is the right execution path.
원문 언어: 영어
Use when Power BI forecasts or plan variances need AI explanations by mix, volume, price, capacity, supply, demand, seasonality, backlog, and data quality.
원문 언어: 영어
Use when Power BI reports, measures, semantic models, RLS, sources, labels, ownership, or KPI definitions may have drifted away from approved standards.
원문 언어: 영어
Use when AI-generated Power BI insights, anomalies, exceptions, or narratives need ranking by business impact, confidence, urgency, actionability, and owner readiness.
원문 언어: 영어
Use when Power BI needs AI-assisted KPI discovery from process data, source metadata, report portfolios, event logs, operational exceptions, or business questions.
원문 언어: 영어