Data & Analytics

Data analysis, BI, visualization, datasets, statistics, and ML workflows

skills in category: 12,625
pages available: 527

Security grades appear on each card once the skill has been scanned. Newly imported skills may briefly show without a grade until the backfill job runs.

Open in full browser

Browse data & analytics skills

Showing 11,425–11,448 of 12,625 skills

Fabric Onelake Perf RemediateADiagnose and resolve Microsoft Fabric OneLake performance issues including slow queries, cold cache latency, small file problems, Delta table fragmentation, V-Order optimization, Spark throttling, capacity SKU sizing, and cross-region data access. Use when remediate OneLake read/write performance, lakehouse query slowness, Direct Lake fallback, table maintenance failures, Spark concurrency limits, warehouse cold starts, or optimizing Delta parquet file layouts. Supports PowerShell, T-SQL, and...datashellsqlVotes: 0GitHub stars: 16
Fabric Notebook Perf RemediateADiagnose and resolve performance issues in Microsoft Fabric notebooks running Apache Spark. Use when notebooks are slow, Spark jobs are timing out, sessions hit HTTP 430 throttling errors, data skew causes straggling tasks, shuffle operations are inefficient, Delta Lake tables need optimization, V-Order configuration is needed, capacity utilization is high, OOM errors occur, or Spark Advisor warnings appear. Covers Spark session tuning, Native Execution Engine, autotune, custom Spark pools, p...datapythongoVotes: 0GitHub stars: 16
Fabric Lakehouse Views Perf RemediateATroubleshoot Microsoft Fabric materialized lake views (MLV) performance issues including slow refresh, incremental refresh failures, full refresh fallback, Spark job failures, lineage execution errors, data quality constraint violations, and optimal refresh configuration. Use when diagnosing MLV refresh duration, monitoring MLV runs in Monitor Hub, analyzing Spark logs for MLV failures, enabling change data feed (CDF), resolving delta table not found errors, or optimizing MLV query definition...datasqlnodeVotes: 0GitHub stars: 16
Fabric Lakehouse Perf RemediateADiagnose and resolve Microsoft Fabric Lakehouse performance issues including slow Spark queries, small file problems, Delta table fragmentation, V-Order configuration, table maintenance (OPTIMIZE, VACUUM, Z-Order), SQL analytics endpoint tuning, Direct Lake performance, resource profile selection, autotune configuration, capacity throttling, and streaming ingestion optimization. Use when asked to troubleshoot Fabric Lakehouse slowness, optimize Delta tables, fix small file problems, configure...datapythonshellVotes: 0GitHub stars: 16
Fabric IqAGuide for working with Microsoft Fabric IQ (preview), the semantic intelligence workload for unified data and business vocabulary. Use when creating or managing ontology items, defining entity types, binding data to ontologies, creating relationship types, configuring data agents with ontology sources, working with Graph in Microsoft Fabric, managing Fabric IQ tenant settings, querying ontology graphs, generating ontologies from Power BI semantic models, or remediate Fabric IQ preview feature...datarustgoVotes: 0GitHub stars: 16
Fabric Delta Spark PerfATroubleshoot and optimize Delta Lake and Apache Spark performance in Microsoft Fabric. Use when diagnosing slow Spark jobs, small file problems, data skew, shuffle bottlenecks, out-of-memory errors, V-Order tuning, OPTIMIZE/VACUUM operations, partition strategy, resource profile selection (writeHeavy, readHeavyForSpark, readHeavyForPBI), autotune configuration, Native Execution Engine, broadcast joins, AQE (Adaptive Query Execution), or when Spark notebooks or Spark Job Definitions run slower...datapythongoVotes: 0GitHub stars: 16
Skills DirectorySkills Directory 3 slots · $399/mo · one ad per page · sponsors can never buy grades.See placements
Fabric Dataflows Perf RemediateADiagnose and resolve Microsoft Fabric Dataflow Gen2 performance issues including slow refresh times, Fast Copy optimization, query folding failures, staging bottlenecks, gateway latency, incremental refresh tuning, capacity throttling, and data destination write performance. Use when troubleshooting dataflow refresh failures, optimizing Dataflow Gen2 execution time, debugging Power Query mashup engine performance, resolving staging Lakehouse or Warehouse compute issues, configuring Fast Copy ...datagoshellVotes: 0GitHub stars: 16
Fabric Data Factory Perf RemediateADiagnose and resolve Microsoft Fabric Data Factory pipeline performance issues. Use when pipelines are slow, copy activities timeout, dataflows stall, activities are stuck, throughput is low, capacity is throttled, or jobs queue indefinitely. Covers copy activity tuning (parallelCopies, DIU, ITO, partitioning), pipeline monitoring via Monitoring Hub and workspace monitoring, Spark job queueing, capacity SKU limits, error code resolution, and dataflow optimization. Keywords include Fabric pipe...datagoshellVotes: 0GitHub stars: 16
Fabric Data AgentACreate, configure, and manage Microsoft Fabric Data Agents that enable natural language Q&A over lakehouses, warehouses, Power BI semantic models, KQL databases, and ontologies. Use when asked to build data agents, configure NL2SQL/NL2DAX/NL2KQL experiences, write agent instructions, create example queries, automate data agent provisioning via REST API or PowerShell, integrate Fabric data agents with Azure AI Foundry, or troubleshoot data agent configuration issues.datashellsqlVotes: 0GitHub stars: 16
Fabric Data Agent RemediateADiagnose and resolve Microsoft Fabric Data Agent issues including tenant settings, data source configuration, query generation failures, cross-region capacity errors, XMLA endpoint setup, Power BI semantic model integration, lakehouse/warehouse/KQL connectivity, example query validation, publishing/sharing problems, and Azure AI Foundry integration. Use when asked to troubleshoot data agent, fix Fabric AI agent, debug NL2SQL/NL2DAX/NL2KQL, resolve Copilot tenant settings, or diagnose Fabric d...datagoshellVotes: 0GitHub stars: 16
Fabric Data Agent Perf RemediateADiagnose and resolve Microsoft Fabric Data Agent performance issues including slow query generation, capacity throttling (HTTP 430), Spark session startup delays, KQL/SQL/DAX query timeouts, data source misconfiguration, example query validation failures, resource profile tuning, VOrder optimization, autotune settings, and Lakehouse table maintenance. Use when asked to troubleshoot Fabric Data Agent response times, fix agent query accuracy, debug Operations Agent playbook performance, resolve...datagoshellVotes: 0GitHub stars: 16
Scientific EdaADefensive exploratory data analysis for scientific data (CSV, FASTA, etc.). Context-first, human-guided; one plot at a time, ask why before executing, append-only journal per session, scripts with PEP723 and uv run, WebP plots. Use when opening data files for EDA or when the user wants guided scientific data exploration.datapythongoVotes: 0GitHub stars: 39
Ml ExperimentationAConduct machine learning experiments from planning through evaluation and report writing. Use when running ML experiments, testing hypotheses, training models, or writing up results. Covers single-hypothesis scoping, fast iteration loops, targeted logging, JOURNAL.md protocol, data-backed diagnostic plots, and scientific report writing.datapythongoVotes: 0GitHub stars: 39
Analyze PerformanceAAnalyze engagement patterns across published posts to identify what works. Use when asked to review performance, find successful patterns, or optimize future content.datagoreactVotes: 0GitHub stars: 129
Task ProfileAMine the user's Claude Code + Cowork session history into a structured task profile, what they do with AI, how often, how successfully where friction lives, then propose atomic skills that would reduce iteration. Use when the user asks to "analyse my Claude use", "build a task profile", "what tasks do I do with Claude", "where am I spending tokens", "what skills would help me", or mentions reviewing past sessions for patterns. Produces profile.csv (shareable), explorer.html (personal coaching...datapythongoVotes: 0GitHub stars: 129
GradientAML-specific patterns for data pipelines, model training, MLOps, and evaluation — domain expertise for machine learning engineersdatatestingdebuggingVotes: 0GitHub stars: 68
Retention CohortsACohort retention analysis — triangle chart construction, curve shape analysis for PMF detection (flattening/declining/rising), layer cake chart, PMF-driven priority shifting, 5 retention anti-patterns, 4 improvement levers, three definitions setup. Use when measuring PMF, analyzing user retention, or deciding whether to scale or improve product.datagoVotes: 0GitHub stars: 6
Yfinance DataAFetch financial and market data with the yfinance Python library (Yahoo Finance). Use this skill whenever the user wants stock data: current quotes and price history, financial statements (income statement, balance sheet, cash flow), options chains, dividends and splits, earnings and analyst estimates, price targets and ratings, institutional and insider holdings, news, multi-ticker comparisons, stock screens, or sector and industry data. Use it even when the user gives only a ticker symbol (...datapythongoVotes: 0GitHub stars: 3,372
Stock LiquidityAAnalyze how liquid a stock is using Yahoo Finance data (yfinance): bid-ask spreads, volume and dollar volume (ADTV), top-of-book and options depth, square-root market impact and slippage estimates, turnover ratio, and Amihud illiquidity, rolled into a liquidity grade. Use this skill whenever the user asks about liquidity or trading costs — how easily a position can be entered or exited, what a large order would do to the price, spread or execution-cost estimates, order book depth, volume patt...datapythongoVotes: 0GitHub stars: 3,372
Stock CorrelationAAnalyze how stocks move together using Yahoo Finance price history (yfinance): find correlated peers for a ticker, measure correlation, beta, and spread between specific tickers, cluster a group into a correlation matrix, and track rolling or regime-dependent correlation. Use this skill whenever the user asks what moves with a stock, what else drops when it drops, related tickers or sympathy plays, sector or supply-chain peers, pair trading or hedging pairs, beta or relative performance, corr...datapythongoVotes: 0GitHub stars: 3,372
Sepa StrategyAAnalyze stocks with Mark Minervini's SEPA (Specific Entry Point Analysis) methodology: stage analysis, the 8-condition trend template, fundamentals, VCP and other base patterns, pivot-point entries, market environment, and risk-based position sizing. Use this skill whenever the user mentions SEPA, Minervini, superperformance, the trend template, VCP (volatility contraction pattern), Stage 2, pivot or breakout entries, moving-average stacking (price above the 50/150/200-day MAs), breakout volu...datagoapiVotes: 0GitHub stars: 3,372
Saas Valuation CompressionAAnalyze how a private SaaS company's ARR valuation multiple changed across funding rounds, and attribute the compression or expansion to rate cycles and macro selloffs, growth deceleration, narrative shifts (including an AI premium), competition, and investor demand, benchmarked against private-market medians and peers. Use this skill whenever the user asks about valuation compression, ARR multiples, round-to-round valuation or multiple changes, down rounds, or wants to compare a VC-backed so...datagoVotes: 0GitHub stars: 3,372
Etf PremiumACalculate an ETF's premium or discount to NAV from Yahoo Finance data (yfinance), compare or screen ETFs by premium, explain why a gap exists, and decompose a sudden ETF move into NAV-driven vs structural components (dealer gamma exposure, blocked AP arbitrage, sentiment). Use this skill whenever the user asks whether an ETF trades above or below NAV, compares ETF premiums or discounts, screens for the biggest ones, asks about ETF arbitrage or premium convergence, or wants to know why an ETF ...datapythongoVotes: 0GitHub stars: 3,372
Estimate AnalysisAAnalyze sell-side analyst estimates and how they are changing, using Yahoo Finance data (yfinance): EPS and revenue consensus by period, estimate ranges and dispersion, revision trends over 7/30/60/90 days and up/down revision breadth, growth estimates vs industry, sector, and the S&P 500, and historical estimate accuracy. Use this skill when the user wants more than a single estimate lookup: estimate revisions or momentum, EPS trend, consensus changes, forward or next-quarter and annual esti...datapythongoVotes: 0GitHub stars: 3,372