Total 53,577 skills, Data Processing has 2764 skills
Showing 12 of 2764 skills
Design measurement frameworks including event taxonomy, KPI hierarchy, dashboard architecture, attribution models, and analytics implementation strategy. Use this skill whenever the user wants to plan analytics, design dashboards, build event taxonomies, define KPIs, set up tracking, or audit existing measurement. Triggers on analytics strategy, measurement plan, event taxonomy, tracking plan, KPI framework, dashboard design, north star metric, attribution model, conversion tracking, GA4 setup, Mixpanel setup, analytics audit. Also triggers when the user has data but no clear way to use it, or wants to make decisions but doesn't know what to track.
Screen US equities for parabolic exhaustion patterns and generate conditional pre-market short plans, then evaluate intraday trigger fires from live 5-min bars. Phase 1 daily 5-factor scorer (MA extension / acceleration / volume climax / range expansion / liquidity), Phase 2 per-candidate plans for ORL break / first-red 5-min / VWAP fail with explicit borrow / SSR / manual-confirmation gating, Phase 3 one-shot intraday FSM that detects trigger fires and resolves concrete share counts. Covers Phase 1 + Phase 2 + Phase 3.
SEC 13F fund-manager–centric view via Longbridge — top-50 active institutional investors by AUM, a specific manager's full portfolio snapshot (by CIK), and quarter-over-quarter holding changes (NEW / ADDED / REDUCED / EXITED). US stocks only. Different from longbridge-flows (stock-centric: who holds a symbol); this skill is manager-centric. Triggers: "基金经理持仓", "机构持仓排名", "大基金持仓", "巴菲特持仓", "贝莱德持仓", "13F基金视角", "基金经理排名", "AUM排名", "季度持仓变化", "基金經理持倉", "機構持倉排名", "大基金持倉", "13F基金視角", "季度持倉變化", "fund manager holdings", "institutional investor", "13F portfolio", "Berkshire holdings", "BlackRock positions", "fund manager ranking", "AUM ranking", "quarterly position changes", "CIK lookup".
Use when validating data with Standard Schema-compatible schemas or handling ValidationError results.
Use when tasks involve creating, editing, analyzing, or formatting spreadsheets (`.xlsx`, `.csv`, `.tsv`) using Python (`openpyxl`, `pandas`), especially when formulas, references, and formatting need to be preserved and verified.
Use when asked to normalize audio volume, match loudness, or apply peak/RMS normalization to audio files.
Julia: multiple dispatch, type system, metaprogramming, Pkg, scientific computing, GPU CUDA.jl
Develop and deploy Lakeflow Jobs on Databricks. Use when creating data engineering jobs with notebooks, Python wheels, or SQL tasks. Invoke BEFORE starting implementation.
Эксперт Airbyte. Используй для настройки ETL/ELT пайплайнов, коннекторов, синхронизации данных и data pipelines.
Generate statistical analysis code with 4-round review. Select appropriate statistical tests, interpret results, and produce analysis reports with p-values, effect sizes, and confidence intervals. Use when analyzing experimental data for a paper.
Codified expertise for demand forecasting, safety stock optimization, replenishment planning, and promotional lift estimation at multi-location retailers. Informed by demand planners with 15+ years experience managing hundreds of SKUs. Includes forecasting method selection, ABC/XYZ analysis, seasonal transition management, and vendor negotiation frameworks. Use when forecasting demand, setting safety stock, planning replenishment, managing promotions, or optimizing inventory levels.
Ingest and transform data files (CSV/JSON/Parquet/Arrow IPC) into Elasticsearch with stream processing, custom transforms, and cross-version reindexing. Use when loading files, batch importing data, or migrating indices across versions — not for general ingest pipeline design or bulk API patterns.