Execute KQL queries and analyze data in Azure Data Explorer for log analytics, telemetry, and time series insights. Execute KQL queries against massive datasets with sub-second performance, including filtering, aggregation, time series analysis, and cross-table joins Discover and explore cluster resources, databases, and table schemas to understand your data model before querying Supports five core query patterns: basic retrieval, aggregation analysis, time series analytics, join-based correlation, and schema discovery Built-in fallback to Azure CLI commands when MCP tools timeout or encounter connection errors
Identify cost savings across Azure subscriptions through resource analysis, utilization metrics, and actionable optimization recommendations. Discovers orphaned resources (unattached disks, unused NICs, idle gateways) and over-provisioned services using Azure Quick Review Queries actual costs from Azure Cost Management API and utilization data from Azure Monitor to support rightsizing recommendations Generates prioritized optimization reports with estimated savings, implementation commands, and Azure Portal links for each resource Includes specialized Redis cost optimization analysis with subscription filtering and pre-built report templates Requires Cost Management Reader, Monitoring Reader, and Reader roles; validates prerequisites before analysis begins
Unified Azure cost management: query historical costs, forecast future spending, and optimize to reduce waste. WHEN: \"Azure costs\", \"Azure spending\",…
Query metrics, logs, and traces across Azure Monitor, Application Insights, and Log Analytics. Access metrics, KQL log queries, and distributed tracing through MCP tools or Azure CLI commands Supports Application Insights for APM and performance analysis, Log Analytics for custom KQL queries, and Azure Monitor for infrastructure metrics Includes common KQL query patterns for errors, request performance, and resource usage monitoring Workbooks integration for building interactive observability dashboards and reports
Create, edit, and analyze Excel spreadsheets with formulas, formatting, and error-free calculations. Supports reading, creating, and modifying .xlsx, .xlsm, .csv, and .tsv files using pandas for data analysis and openpyxl for formulas and formatting Automatically recalculates all formulas and scans for Excel errors (#REF!, #DIV/0!, #VALUE!, #N/A, #NAME?) using LibreOffice integration Enforces industry-standard color coding and number formatting for financial models (blue for inputs, black for formulas, green for internal links, red for external links) Includes comprehensive documentation requirements for hardcoded values and assumption-based formula construction to maintain dynamic, updateable spreadsheets
Semantic modeling assistant for building optimized Power BI data models with DAX, relationships, and best practices. Connects to active Power BI models (Desktop or Fabric) to analyze current structure before providing guidance on star schemas, relationships, measures, and naming conventions Covers core modeling tasks: creating DAX measures, configuring table relationships and cardinality, implementing row-level security (RLS), and optimizing performance Includes model quality assessment against best practices, with checklists for documentation, hidden fields, cross-filter direction, and calculation groups Provides targeted recommendations via reference guides for star schema design, relationship configuration, DAX patterns, and performance tuning
Comprehensive Power BI design consultation framework covering chart selection, layout strategy, accessibility, and interactive patterns. Provides structured requirements gathering for business context, data analysis, and technical constraints before recommending visualizations Includes detailed chart selection methodology organized by data relationships (comparison, trend, composition, distribution) with specific recommendations for each category Offers audience-specific design patterns for executive dashboards, analytical reports, and operational dashboards with distinct layout and interaction approaches Covers color strategy with semantic mapping, accessibility compliance (4.5:1 contrast, colorblind-friendly palettes), typography hierarchy, and mobile-responsive design considerations Includes design review checklists, user testing protocols, and implementation guidelines with phased development approach and quality assurance criteria
Comprehensive DAX formula analysis and optimization with performance, readability, and best-practice guidance. Analyzes formulas across four dimensions: performance bottlenecks, readability clarity, best-practice compliance, and maintainability challenges Provides step-by-step optimization strategy including variable usage opportunities, function replacements, and context optimization techniques Delivers refactored formulas with improved structure, error handling via DIVIDE and BLANK preservation, and inline documentation Covers common patterns like variable caching for expensive calculations, proper iterator function usage, and defensive programming for edge cases
Comprehensive Power BI data model design review framework for evaluating architecture, relationships, and optimization. Covers schema architecture, relationship design, and storage mode strategy with detailed assessment checklists across fact tables, dimensions, cardinality, and filter directions Includes three-phase review process: model architecture analysis, performance and scalability evaluation, and maintainability/governance assessment Provides specialized review types for pre-production validation, performance optimization, and modernization assessment with tailored deliverables Offers executive summary templates, detailed report structures, and quick (30-minute) to comprehensive (4-8 hour) review checklists for different engagement scopes
Systematic framework for diagnosing and resolving Power BI performance bottlenecks across models, reports, and infrastructure. Covers four diagnostic areas: model design and DAX efficiency, report layout and visual complexity, infrastructure capacity, and data source connectivity Includes step-by-step troubleshooting methodology with issue classification, baseline metrics collection, and targeted diagnosis workflows Provides concrete optimization patterns for DAX formulas, storage mode selection, and report design alongside anti-patterns to avoid Offers quick-win checklists (30 minutes), comprehensive analysis workflows (2–4 hours), and strategic optimization plans with performance monitoring setup and alerting thresholds
Chart selection guidance, Python code patterns, and design principles for effective data visualizations. Comprehensive chart selection table covering 13+ chart types with guidance on when to use each and common anti-patterns to avoid (pie charts, 3D, dual-axis) Ready-to-use Python code examples for line charts, bar charts, histograms, heatmaps, small multiples, and interactive Plotly visualizations with professional styling Design principles covering color theory (sequential, diverging, categorical palettes), typography, layout, and accuracy standards like zero-baseline bar charts Accessibility checklist including colorblind-friendly palettes, screen reader considerations, contrast requirements, and black-and-white printability validation
Credit risk data cleaning and variable screening pipeline for pre-loan modeling. Executes 11 independent steps covering data loading, abnormal period filtering, missing rate analysis, low-IV and high-PSI variable removal, null importance denoising, and correlation-based feature elimination Supports organization-level analysis with separate modeling and out-of-sample (OOS) sample handling, plus multi-process acceleration for IV and PSI calculations Generates comprehensive Excel report with 15 sheets detailing operation results, feature statistics, distributions, and removed variables across all pipeline stages Configurable thresholds for missing rate, IV, PSI, correlation, and null importance parameters with sensible defaults
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Build an interactive HTML dashboard with charts, filters, and tables. Use when creating an executive overview with KPI cards, turning query results into a…
Generates cost optimization guidance for Google Cloud workloads based on the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a…