Total 50,473 skills, Data Processing has 2559 skills
Showing 12 of 2559 skills
Data acquisition for web scraping and data collection. Use when user needs "爬取数据/抓取网页/scrape data". Outputs structured JSON/CSV for analysis.
Calculate statistical significance for A/B tests. Sample size estimation, power analysis, and conversion rate comparisons with confidence intervals.
Expert 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.
Use when defining events, fields, and governance for GTM analytics pipelines.
Expert-level Apache Airflow orchestration, DAGs, operators, sensors, XComs, task dependencies, and scheduling
Initialize warehouse schema discovery. Generates .astro/warehouse.md with all table metadata for instant lookups. Run once per project, refresh when schema changes. Use when user says "/data:warehouse-init" or asks to set up data discovery.
NCBI BLAST sequence similarity search using BioPython. Use when a user wants to run BLAST programmatically with blastn/blastp and retrieve results in JSON format.
Excel spreadsheet toolkit for creating, reading, and manipulating .xlsx files. Supports formulas, formatting, charts, and financial modeling with industry-standard conventions. Use for data analysis, financial models, reports, and spreadsheet automation.
Bronze/Silver/Gold layer design patterns and templates for building scalable data lakehouse architectures. Includes incremental processing, data quality checks, and optimization strategies.
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.
Expert guidance on choosing the right geospatial tool based on problem type, accuracy requirements, and performance needs
Master data engineering, ETL/ELT, data warehousing, SQL optimization, and analytics. Use when building data pipelines, designing data systems, or working with large datasets.