Total 30,299 skills, Data Processing has 1446 skills
Showing 12 of 1446 skills
Validates DAG structures, performs topological sorting, detects cycles, and resolves dependency conflicts. Uses Kahn's algorithm for optimal execution ordering. Activate on 'resolve dependencies', 'topological sort', 'cycle detection', 'dependency order', 'validate dag'. NOT for building DAGs (use dag-graph-builder) or scheduling execution (use dag-task-scheduler).
Search and extract contact information for people or companies including names, phone numbers, emails, job titles, and LinkedIn profiles. Aggregates data from multiple sources and provides enriched contact details. Use when users need to find contact information, build prospect lists, or enrich existing contact data.
Use to define schemas, topic tags, and lineage metadata for enriched signals.
Monitor injury news across leagues. Fantasy impact analysis, backup player analysis, return timeline estimates.
dbt (data build tool) patterns for model organization, incremental strategies, and testing.
Designs reliable ETL and data synchronization jobs with incremental updates, idempotency guarantees, watermark tracking, error handling, and retry logic. Use for "ETL jobs", "data sync", "incremental sync", or "data pipeline".
data-collection for evidence-based learning research and evaluation.
Query macOS iMessage database (chat.db) via SQLite. Decode NSAttributedString messages, handle tapbacks, search conversations. TRIGGERS - imessage, chat.db, messages database, text messages, iMessage history, NSAttributedString, attributedBody
Microsoft Excel (.xlsx) spreadsheet manipulation using MCP server tools. Use this any time an Excel spreadsheet is involved - as input, output, or both. Activate the excel-server MCP for Excel operations. Covers creating workbooks, managing worksheets, formatting cells, writing formulas, creating charts, building pivot tables, and data analysis with professional standards.
Comprehensive guide for Azure Data Explorer (ADX) and Kusto Query Language (KQL); use when writing/optimizing KQL queries, setting up ingestion, building dashboards, doing time-series/ML analysis, configuring management/security, or when users mention Kusto, KQL, ADX, Azure Data Explorer, or log analytics queries.
Use when writing R code that manipulates expressions, builds code programmatically, or needs to understand rlang's defuse/inject mechanics. Covers: defusing with expr()/enquo()/enquos(), quosure environment tracking, injection with !!/!!!/{{, symbol construction with sym()/syms(). Does NOT cover: data-mask programming patterns (tidy-evaluation), error handling (rlang-conditions), function design (designing-tidy-r-functions).
Use when validating data with Standard Schema-compatible schemas or handling ValidationError results.