Total 30,737 skills, Data Processing has 1471 skills
Showing 12 of 1471 skills
Search for new preprints in infectious disease modelling from arXiv, medRxiv, and bioRxiv
Expert guidance for R package development following best practices for devtools, testthat, roxygen2, and R ecosystem tools
Professional data visualization expert, proficient in modern chart libraries, dashboard design, and interactive data presentation. Capable of transforming complex data into intuitive, beautiful, and insightful visual works.
Analyzes clinical trial protocols and generates CDISC-compliant (SDTM/ADaM) data schemas. Use when designing data ingestion pipelines for clinical research or preparing regulatory submissions.
Analyze sports data, identify exercise patterns, evaluate fitness progress, and provide personalized training recommendations. Supports correlation analysis with chronic disease data.
The practice of collecting, analyzing, and acting on data to drive product decisions. Great analytics isn't about dashboards—it's about insights that lead to action. Every metric should answer a question that changes behavior. This skill covers event tracking, metrics design, dashboards, user behavior analysis, and data-driven decision making. The best analytics teams measure what matters, not what's easy to measure. Use when "analytics, metrics, tracking, dashboard, funnel, cohort, retention, events, KPI, measure, data, insights, conversion, engagement, analytics, metrics, data, dashboards, tracking, funnels, cohorts, KPIs, insights" mentioned.
This skill should be used when the user asks to "create report", "dashboard", "chart", "visualization", "analytics", "scheduled report", "export data", or any ServiceNow reporting and dashboard development.
Observability and monitoring for data pipelines using OpenTelemetry (traces) and Prometheus (metrics). Covers instrumentation, dashboards, and alerting.
Using DuckDB with remote cloud storage via HTTPFS extension, fsspec, and Delta Lake integration. Covers S3, GCS, Azure, and S3-compatible endpoints.
Native Arrow filesystem integration with PyArrow. Optimized for Parquet workflows, zero-copy data transfer, predicate pushdown, and column pruning. Covers S3, GCS, HDFS with PyArrow datasets.
Interactive web apps for data science: Streamlit, Panel, and Gradio. Use for prototyping ML models, creating data exploration dashboards, and sharing insights with non-technical stakeholders.
Trade mean reversion setups in the style of Scarface Trades, the mean reversion specialist known for mathematical precision and statistical edge. Emphasizes standard deviation bands, RSI extremes, and calculated entries with defined risk. Use when trading overextended moves, fading extremes, or building systematic reversion strategies.