Total 50,522 skills, Data Processing has 2561 skills
Showing 12 of 2561 skills
Best practices for Open Finance data retrieval and management. Use when working with accounts, transactions, investments, loans, or identity data.
Use when designing, tuning, or auditing revenue forecast models.
Use to design provider sequences, throttling logic, and credit policies for enrichment waterfalls.
Generates and analyzes financial models, P&L forecasts, and cash flow projections. Transforms business assumptions into multi-year financial statements.
Template pack for summarizing BI insights for ELT/board stakeholders.
Use when "GeoPandas", "geospatial", "GIS", "shapefile", "GeoJSON", or asking about "spatial analysis", "coordinate transformation", "spatial join", "choropleth map", "buffer analysis", "geographic data", "map visualization"
Apply production-ready Databricks SDK patterns for Python and REST API. Use when implementing Databricks integrations, refactoring SDK usage, or establishing team coding standards for Databricks. Trigger with phrases like "databricks SDK patterns", "databricks best practices", "databricks code patterns", "idiomatic databricks".
Use when asked to create publication-ready scientific figures, charts for research papers, or academic visualizations.
Best practices for Matplotlib data visualization, plotting, and creating publication-quality figures in Python
Expert data engineering covering data pipelines, ETL/ELT, data warehousing, streaming, and data quality.
Comprehensive epigenomics and gene regulation analysis integrating ENCODE functional genomics data, JASPAR transcription factor binding motifs, SCREEN cis-regulatory elements, ReMap TF binding sites, RegulomeDB variant regulatory scoring, 4D Nucleome chromatin conformation, and Ensembl regulatory features. Performs regulatory element cataloging, transcription factor analysis, variant regulatory impact scoring, chromatin conformation mapping, and gene-centric regulatory landscape profiling. Use when asked about gene regulation, enhancers, promoters, transcription factor binding, epigenetic modifications, chromatin structure, regulatory variants, or non-coding genome function.
Use when implementing skill data generation from HTML sources for game build planners - guides the parser-factory-generation pattern for extracting level-scaling values for active and passive skills (project)