Data & Analytics

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

skills in category: 12,625
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Showing 12,529–12,552 of 12,625 skills

Customer Health AnalystAExpert customer health scoring and analytics guidance. Use when designing health scores, building churn prediction models, analyzing usage metrics, identifying at-risk accounts, creating executive dashboards, or performing cohort analysis. Use for leading indicator development, customer data enrichment, risk escalation frameworks, and retention analytics.datarustgoVotes: 0GitHub stars: 49
Sap Hana MlASAP HANA Machine Learning Python Client (hana-ml) development skill. Use when: Building ML solutions with SAP HANA's in-database machine learning using Python hana-ml library for PAL/APL algorithms, DataFrame operations, AutoML, model persistence, and visualization. Keywords: hana-ml, SAP HANA, machine learning, PAL, APL, predictive analytics, HANA DataFrame, ConnectionContext, classification, regression, clustering, time series, ARIMA, gradient boosting, AutoML, SHAP, model storagedatapythongoVotes: 0GitHub stars: 459
Sap Hana Cloud Data IntelligenceADevelops data processing pipelines, integrations, and machine learning scenarios in SAP Data Intelligence Cloud. Use when building graphs/pipelines with operators, integrating ABAP/S4HANA systems, creating replication flows, developing ML scenarios with JupyterLab, or using Data Transformation Language functions. Covers Gen1/Gen2 operators, subengines (Python, Node.js, C++), structured data operators, and repository objects.datajavascriptpythonVotes: 0GitHub stars: 459
Sap DatasphereAComprehensive plugin for SAP Datasphere development with 3 specialized agents, 5 slash commands, and validation hooks. Use when building data warehouses on SAP BTP, creating analytic models, configuring data flows and replication flows, setting up connections to SAP and third-party systems, managing spaces and users, implementing data access controls, using the datasphere CLI, creating data products for the marketplace, or monitoring data integration tasks. Covers Data Builder (graphical/SQL ...datapythongoVotes: 0GitHub stars: 459
XlsxAxlsxdatapythongoVotes: 0GitHub stars: 19
Creating Financial ModelsAThis skill provides an advanced financial modeling suite with DCF analysis, sensitivity testing, Monte Carlo simulations, and scenario planning for investment decisionsdatagotestingVotes: 0GitHub stars: 20
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XlsxAComprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulasdatapythongoVotes: 0GitHub stars: 197
ManimACreate mathematical animations and visualizations using Manim (ManimCE - Community Edition). Use this skill when users want to build Manim visualizations, create math animations, animate equations, graphs, geometric proofs, 3D objects, or any programmatic video animation. Triggers on requests mentioning "manim", "mathematical animation", "animate equation", "visualize algorithm", "create animation of", "3D visualization", or building explanatory math videos.datapythongoVotes: 0GitHub stars: 21
Rfm Customer SegmentationAPerform RFM (Recency, Frequency, Monetary) customer segmentation analysis on e-commerce data. Use when you need to analyze customer value, identify VIP customers, or create marketing segments. Automatically cleans data, calculates RFM metrics, applies K-means clustering, and generates visualization reports with Chinese language support.datapythonbashVotes: 0GitHub stars: 281
Retention AnalysisAAnalyze user retention and churn using survival analysis, cohort analysis, and machine learning. Calculate retention rates, build survival curves, predict churn risk, and generate retention optimization strategies. Use when working with user subscription data, membership information, or when user mentions retention, churn, survival analysis, or customer lifetime value.datapythonbashVotes: 0GitHub stars: 281
Regression Analysis ModelingAPerform comprehensive regression analysis and predictive modeling using linear regression, decision trees, and random forests. Use when you need to predict continuous values like housing prices, sales forecasts, demand predictions, or any numerical target variables. Includes automated feature engineering, model comparison, and visualization with Chinese language support.datapythongoVotes: 0GitHub stars: 281
Ltv PredictorA基于RFM模型和回归算法的客户生命周期价值(LTV)预测分析工具，支持电商和零售业务的客户价值预测。使用时需要客户交易数据、订单历史或消费记录，自动进行RFM特征工程、回归建模和价值预测。datapythonbashVotes: 0GitHub stars: 281
Growth Model AnalyzerA增长模型分析技能 - 提供全面的增长黑客分析工具，包括裂变策略评估、用户细分、Uplift建模、ROI优化等。支持多种增长场景的机器学习建模和智能决策建议。适用于用户增长、营销优化、产品迭代等增长分析场景。datapythonbashVotes: 0GitHub stars: 281
Funnel AnalysisAAnalyze user conversion funnels, calculate step-by-step conversion rates, create interactive visualizations, and identify optimization opportunities. Use when working with multi-step user journey data, conversion analysis, or when user mentions funnels, conversion rates, or user flow analysis.datapythonbashVotes: 0GitHub stars: 281
Data Exploration VisualizationA自动化数据探索和可视化工具，提供从数据加载到专业报告生成的完整EDA解决方案。支持多种图表类型、智能数据诊断、建模评估和HTML报告生成。适用于医疗、金融、电商等领域的数据分析项目。datapythongoVotes: 0GitHub stars: 281
Content AnalysisAAnalyze text content using both traditional NLP and LLM-enhanced methods. Extract sentiment, topics, keywords, and insights from various content types including social media posts, articles, reviews, and video content. Use when working with text analysis, sentiment detection, topic modeling, or content optimization.datapythongoVotes: 0GitHub stars: 281
Attribution Analysis ModelingAPerform multi-touch attribution analysis using Markov chains, Shapley values, and custom attribution models. Use when you need to analyze marketing channel effectiveness, calculate conversion attribution, optimize marketing budgets, or understand customer journey paths. Supports channel transition analysis, ROI calculation, and marketing optimization insights with Chinese language support.datapythongoVotes: 0GitHub stars: 281
Ab Testing AnalyzerA全面的AB测试分析工具，支持实验设计、统计检验、用户分群分析和可视化报告生成。用于分析产品改版、营销活动、功能优化等AB测试结果，提供统计显著性检验和深度洞察。datapythongoVotes: 0GitHub stars: 281
XlsxAComprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulasdatapythongoVotes: 0GitHub stars: 32,950
Optimizing Query TextAOptimizes Snowflake SQL query performance from provided query text. Use when optimizing Snowflake SQL for: (1) User provides or pastes a SQL query and asks to optimize, tune, or improve it (2) Task mentions "slow query", "make faster", "improve performance", "optimize SQL", or "query tuning" (3) Reviewing SQL for performance anti-patterns (function on filter column, implicit joins, etc.) (4) User asks why a query is slow or how to speed it updatasqlexpressVotes: 0GitHub stars: 124
Optimizing Query By IdAOptimizes Snowflake query performance using query ID from history. Use when optimizing Snowflake queries for: (1) User provides a Snowflake query_id (UUID format) to analyze or optimize (2) Task mentions "slow query", "optimize", "query history", or "query profile" with a query ID (3) Analyzing query performance metrics - bytes scanned, spillage, partition pruning (4) User references a previously run query that needs optimization Fetches query profile, identifies bottlenecks, returns optimize...datasqlperformanceVotes: 0GitHub stars: 124
Developing Incremental ModelsADevelops and troubleshoots dbt incremental models. Use when working with incremental materialization for: (1) Creating new incremental models (choosing strategy, unique_key, partition) (2) Task mentions "incremental", "append", "merge", "upsert", or "late arriving data" (3) Troubleshooting incremental failures (merge errors, partition pruning, schema drift) (4) Optimizing incremental performance or deciding table vs incremental Guides through strategy selection, handles common incremental got...datarustgoVotes: 0GitHub stars: 124
Data CatchallAData: data engineering, analytics, ETL, QA, testing. Triggers: data pipeline, etl, data warehouse, analytics, dashboard, metrics, kpi, testing, test automation, qa, quality assurance, ci/cd testing, data science.datatestingci/cdVotes: 0GitHub stars: 18
PytorchABuilding and training neural networks with PyTorch. Use when implementing deep learning models, training loops, data pipelines, model optimization with torch.compile, distributed training, or deploying PyTorch models.datapythongoVotes: 0GitHub stars: 23