100 engineering skills: architecture, fullstack, DevOps, security, AI/ML, data engineering, and agent tooling
101 skills
1,110
claude
data-analytics-skills
6 data analytics skills: data analysis, business intelligence, data science, statistics, ML ops, and analytics engineering
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Plugin data-analytics-skills from marketplace claude-code-skills in borghei/Claude-Skills. Commands read from the repo's manifest — 4 days ago.
What it installs
Skills (6)
analytics-engineerAnalytics engineering across data modeling, dbt, transformation, and semantic layers. Use when building dbt models, designing star schemas, writing staging or mart SQL, configuring data tests, or optimizing warehouse queries. version: 1.0.0 author: borghei category: data-analytics domain: analytics-
business-intelligenceBusiness intelligence across dashboard design, visualization, and reporting automation. Use when designing dashboards, building KPI frameworks, automating reports, creating data stories, or optimizing BI tool performance. version: 1.0.0 author: borghei category: data-analytics domain: business-intel
data-analystData analysis across SQL, visualization, statistics, and reporting. Use when writing SQL queries, building dashboards, performing cohort or funnel analysis, running hypothesis tests, or presenting data-driven recommendations. version: 1.0.0 author: borghei category: data-analytics domain: data-analy
data-scientistData science across machine learning, statistical modeling, and experimentation. Use when selecting ML algorithms, engineering features, designing A/B tests, evaluating model performance, or building predictive pipelines. version: 1.0.0 author: borghei category: data-analytics domain: data-science u
ml-ops-engineerMLOps across model deployment, ML pipelines, monitoring, and feature stores. Use when deploying models to production, building training pipelines, setting up drift detection, configuring feature stores, or automating ML CI/CD workflows. version: 1.0.0 author: borghei category: data-analytics domain:
statistical-analystApplied statistics for business and product questions — test selection, assumption checks, power planning, effect sizes with intervals, multiplicity correction. Use when interpreting an experiment, sizing a study, or vetting a claim. version: 1.0.0 author: borghei category: data-analytics domain: st
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