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SkillsMP hat 259 Skills aus rweisssieker-xp/PowerBi-Codex-Plugin gesammelt. Öffne einen Skill, um Quelle und Details zu prüfen.
rweisssieker-xp/PowerBi-Codex-PluginEs werden 40 von 259 gesammelten Skills angezeigt.
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.
Quellsprache: Englisch
Use when building Power BI process digital twins for bottlenecks, what-if scenarios, capacity, delivery delay, cash impact, inventory, escalations, and process improvement simulation.
Quellsprache: Englisch
Use when generating reusable Power BI process packs such as O2C, P2P, R2R, Plan2Produce, Dock2Stock, Complaint2CAPA, Maintain2Operate, or Control2Evidence.
Quellsprache: Englisch
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.
Quellsprache: Englisch
Use when consolidating duplicate Power BI reports, finding retirement candidates, identifying target semantic models, and planning migration away from report sprawl.
Quellsprache: Englisch
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.
Quellsprache: Englisch
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.
Quellsprache: Englisch
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.
Quellsprache: Englisch
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.
Quellsprache: Englisch
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.
Quellsprache: Englisch
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.
Quellsprache: Englisch
Use when selecting Power BI data-source connectors and comparing Import, DirectQuery, Direct Lake, incremental refresh, gateway, SSO, folding, privacy, and refresh limitations.
Quellsprache: Englisch
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.
Quellsprache: Englisch
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.
Quellsprache: Englisch
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.
Quellsprache: Englisch
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.
Quellsprache: Englisch
Use when Power BI usage telemetry should drive AI recommendations for report training, redesign, consolidation, retirement, communication, or role-based enablement.
Quellsprache: Englisch
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.
Quellsprache: Englisch
Use when Power BI decisions, KPI definitions, model patterns, source mappings, incidents, fixes, and best practices must be retained across projects and reused safely.
Quellsprache: Englisch
Use when Power BI must prepare boardroom or executive meetings with KPIs, variance, root causes, risks, scenarios, decisions, actions, and evidence-backed narratives.
Quellsprache: Englisch
Use when AI should estimate financial or operational impact of KPI changes, process actions, data-quality issues, policy changes, capacity shifts, or scenario decisions.
Quellsprache: Englisch
Use when Power BI models, process chains, roles, or source metadata should generate role-specific management questions for executives, process owners, analysts, and operators.
Quellsprache: Englisch
Use when Power BI or Fabric capacity needs AI recommendations for model splitting, aggregations, Direct Lake, Import, refresh windows, query reduction, and cost optimization.
Quellsprache: Englisch
Use when Power BI users suspect a business driver and need AI-assisted causal plausibility checks instead of simple correlation claims.
Quellsprache: Englisch
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.
Quellsprache: Englisch
Use when Power BI standards should learn from report reviews, tickets, UAT defects, KPI conflicts, user feedback, usage telemetry, quality gates, and delivery retrospectives.
Quellsprache: Englisch
Use when Power BI needs AI mapping of dependencies across O2C, P2P, production, quality, finance, service, supply chain, HR, ESG, and maintenance processes.
Quellsprache: Englisch
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.
Quellsprache: Englisch
Use when Power BI data product owners need AI support for SLA, quality, roadmap, usage, incidents, certification, stakeholder feedback, and escalation management.
Quellsprache: Englisch
Use when data stewards need AI prioritization of data quality issues, owner assignment, correction backlog, root-cause grouping, SLA tracking, and retest plans.
Quellsprache: Englisch
Use when Power BI KPIs, reports, close packages, monthly reviews, board packs, or process cockpits need AI-generated management narratives grounded in evidence.
Quellsprache: Englisch
Use when complex DAX measures need explanations for business users, developers, auditors, data owners, or certification evidence.
Quellsprache: Englisch
Use when decisions made from Power BI reports, AI narratives, scenarios, or KPI alerts need later audit for traceability, effectiveness, evidence, and learning.
Quellsprache: Englisch
Use when Power BI should learn internal benchmarks by plant, region, product, customer, supplier, process, team, or time period from historical enterprise data.
Quellsprache: Englisch
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.
Quellsprache: Englisch
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.
Quellsprache: Englisch
Use when Power BI forecasts or plan variances need AI explanations by mix, volume, price, capacity, supply, demand, seasonality, backlog, and data quality.
Quellsprache: Englisch
Use when Power BI reports, measures, semantic models, RLS, sources, labels, ownership, or KPI definitions may have drifted away from approved standards.
Quellsprache: Englisch
Use when AI-generated Power BI insights, anomalies, exceptions, or narratives need ranking by business impact, confidence, urgency, actionability, and owner readiness.
Quellsprache: Englisch
Use when Power BI needs AI-assisted KPI discovery from process data, source metadata, report portfolios, event logs, operational exceptions, or business questions.
Quellsprache: Englisch