Total 54,636 skills, Data Processing has 2807 skills
Showing 12 of 2807 skills
Alibaba Cloud DMS Database Read/Write Skill. Use this skill to search for target databases in DMS and execute SQL queries and data modifications. Triggers: "DMS query", "database query", "execute SQL", "search database", "DMS SQL", "insert data", "update data".
Databricks CLI operations: auth, profiles, data exploration, and bundles. Contains up-to-date guidelines for Databricks-related CLI tasks.
Diagnose ClickHouse INSERT performance, batch sizing, part creation patterns, and ingestion bottlenecks. Use for slow inserts and data pipeline issues.
Create and configure Databricks Asset Bundles (DABs) with best practices for multi-environment deployments. Use when working with: (1) Creating new DAB projects, (2) Adding resources (dashboards, pipelines, jobs, alerts), (3) Configuring multi-environment deployments, (4) Setting up permissions, (5) Deploying or running bundle resources
Configure Databricks profile and authenticate for Databricks Connect, Databricks CLI, and Databricks SDK.
Convert JSON rows with latitude/longitude fields into a GeoJSON FeatureCollection using raw PostGIS SQL.
Sync retirement account data from Vanguard and Fidelity CSV exports to Google Sheets DataHub. Handles multiple accounts, aggregates holdings by ticker, and updates quantities in retirement section (rows 46-62). Triggers on sync retirement, update retirement, vanguard sync, 401k update, IRA sync, or working with notebooks/retirement-accounts/ files.
Expert blueprint for save/load systems using JSON/binary serialization, PERSIST group pattern, versioning, and migration. Covers player progress, settings, game state persistence, and error recovery. Use when implementing save systems OR data persistence. Keywords save, load, JSON, FileAccess, user://, serialization, version migration, PERSIST group.
Use for creating websets, running searches, importing CSV data, managing items, and adding enrichments to extract structured data.
Post-mortem analysis for any Intelligems A/B test. Extracts learnings from funnel data, segment patterns, and customer behavior — then suggests what to test next based on findings.
PostgreSQL-based semantic and hybrid search with pgvector and ParadeDB. Use when implementing vector search, semantic search, hybrid search, or full-text search in PostgreSQL. Covers pgvector setup, indexing (HNSW, IVFFlat), hybrid search (FTS + BM25 + RRF), ParadeDB as Elasticsearch alternative, and re-ranking with Cohere/cross-encoders. Supports vector(1536) and halfvec(3072) types for OpenAI embeddings. Triggers: pgvector, vector search, semantic search, hybrid search, embedding search, PostgreSQL RAG, BM25, RRF, HNSW index, similarity search, ParadeDB, pg_search, reranking, Cohere rerank, pg_trgm, trigram, fuzzy search, LIKE, ILIKE, autocomplete, typo tolerance, fuzzystrmatch
Statistical scoring with z-scores, percentiles, freshness decay, and cross-category normalization. Rank and compare items with confidence scoring.