Total 30,646 skills, Data Processing has 1469 skills
Showing 12 of 1469 skills
Comprehensive guide to Spark Structured Streaming for production workloads. Use when building streaming pipelines, implementing real-time data processing, handling stateful operations, or optimizing streaming performance.
Stream Light Protocol account state via Laserstream gRPC. Covers token accounts, mint accounts, and compressible PDAs with hot/cold lifecycle tracking. Use when building custom data pipelines, aggregators, or indexers.
Write Arcade expressions for dynamic calculations in popups, renderers, labels, and field calculations. Use for data-driven styling, custom labels, and computed fields.
Use when developing, reviewing, or explaining Rill projects and project files (connectors, models, metrics views, explores, canvases, themes, rill.yaml, sources, alerts, reports, APIs). Apply runtime workflow guidance and project-file reference docs, and cite rule files and source URLs.
You must use this when designing qualitative studies, developing coding schemes, or performing thematic analysis.
Data visualization design based on Stanford CS448B. Use when: (1) Choosing appropriate chart types for data (2) Selecting visual encodings (position, color, size) (3) Critiquing or improving visualizations (4) Building D3.js visualizations (5) Designing interactions and animations (6) Choosing color palettes for accessibility (7) Visualizing networks or text data Covers Bertin, Mackinlay, Cleveland & McGill principles.
Real DCF (Discounted Cash Flow) model creation for equity valuation. Retrieves financial data from SEC filings and analyst reports, builds comprehensive cash flow projections with proper WACC calculations, performs sensitivity analysis, and outputs professional Excel models with executive summaries. Use when users need to value a company using DCF methodology, request intrinsic value analysis, or ask for detailed financial modeling with growth projections and terminal value calculations.
Apply Web Scraping with Python practices (Ryan Mitchell). Covers First Scrapers (Ch 1: urllib, BeautifulSoup), HTML Parsing (Ch 2: find, findAll, CSS selectors, regex, lambda), Crawling (Ch 3-4: single-domain, cross-site, crawl models), Scrapy (Ch 5: spiders, items, pipelines, rules), Storing Data (Ch 6: CSV, MySQL, files, email), Reading Documents (Ch 7: PDF, Word, encoding), Cleaning Data (Ch 8: normalization, OpenRefine), NLP (Ch 9: n-grams, Markov, NLTK), Forms & Logins (Ch 10: POST, sessions, cookies), JavaScript (Ch 11: Selenium, headless, Ajax), APIs (Ch 12: REST, undocumented), Image/OCR (Ch 13: Pillow, Tesseract), Avoiding Traps (Ch 14: headers, honeypots), Testing (Ch 15: unittest, Selenium), Parallel (Ch 16: threads, processes), Remote (Ch 17: Tor, proxies), Legalities (Ch 18: robots.txt, CFAA, ethics). Trigger on "web scraping", "BeautifulSoup", "Scrapy", "crawler", "spider", "scraper", "parse HTML", "Selenium scraping", "data extraction".
Arquiteto de Dados especialista em PostgreSQL, Supabase e modelagem multi-tenant para a plataforma PAPO
Construct SQD Portal Stream API queries for EVM event logs. Track token transfers, DeFi events, and on-chain activity using indexed topic filters.
Split Excel workbooks into separate Excel files by worksheet, with each worksheet generating an individual file. Application scenarios: (1) Split multi-worksheet Excel files into separate files, (2) Extract specific worksheets as independent files, (3) Distribute worksheets from merged workbooks, (4) Create copies of worksheets for separate processing or distribution.
Design, audit, and improve analytics tracking systems that produce reliable, decision-ready data. Use when the user wants to set up, fix, or evaluate analytics tracking (GA4, GTM, product analytics, events, conversions, UTMs). This skill focuses on measurement strategy, signal quality, and validation— not just firing events.