Total 53,920 skills, Data Processing has 2767 skills
Showing 12 of 2767 skills
Expert knowledge for Azure Data Factory development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when designing ADF pipelines, mapping data flows, SHIR/SSIS IR, SAP CDC, or CI/CD with ARM/DevOps, and other Azure Data Factory related development tasks. Not for Azure Synapse Analytics (use azure-synapse-analytics), Azure Databricks (use azure-databricks), Azure Stream Analytics (use azure-stream-analytics), Azure Data Explorer (use azure-data-explorer).
Extract market, financial, earnings, industry, and company metrics with Firecrawl. Use when the user asks for market research, industry trends, public company data, financial comparisons, earnings research, or structured market reports.
This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.
Performs financial ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction for strategic decision-making
Query Google Analytics 4 (GA4) data via the Analytics Data API. Use when you need to pull website analytics like top pages, traffic sources, user counts, sessions, conversions, or any GA4 metrics/dimensions. Supports custom date ranges and filtering.
Triggered when users need to crawl or collect Xiaohongshu (RedNote) data, including scenarios such as searching notes/content, topic discovery, searching users/bloggers, discovering KOLs/influencers, researching account information, capturing user notes, and collecting note comments/replies (public opinion, sentiment, community monitoring). Retrieve data by calling Xiaohongshu interfaces via JustOneAPI.
Use this skill for MaxFrame SDK development on Alibaba Cloud MaxCompute (ODPS). Helps create data processing programs, read/write MaxCompute tables, debug jobs (remote or local), and build custom DPE runtime images. Trigger when users mention MaxFrame, MaxCompute, ODPS, DPE runtime, or need to work with ODPS tables, DataFrame operations, Tensor operations, or GPU runtime setup. Works for both English and Chinese queries about Alibaba Cloud data processing with MaxFrame.
Эксперт AWS Kinesis. Используй для stream processing, real-time data и Kinesis patterns.
Creates structured bug reports for defects found during Oracle-to-PostgreSQL migration. Use when documenting behavioral differences between Oracle and PostgreSQL as actionable bug reports with severity, root cause, and remediation steps.
Use this skill when measuring CSAT, NPS, resolution time, deflection rates, or analyzing support trends. Triggers on CSAT, NPS, resolution time, deflection rate, support metrics, trend analysis, support reporting, and any task requiring customer support data analysis or reporting.
Databricks SQL query optimizer: analyzes a slow SQL query, rewrites it for speed using SQL-level optimizations only, validates byte-for-byte result equivalence, and benchmarks both versions with statistical significance testing. Use this skill whenever the user wants to optimize, speed up, tune, or benchmark a SQL query on Databricks. Trigger on: "/databricks-sql-autotuner", "optimize this SQL", "make this query faster", "tune my Databricks query", "benchmark SQL on Databricks", "speed up this spark SQL", "SQL performance on Databricks", "EXPLAIN this query", "why is my query slow on Databricks", "SQL query optimization Databricks", or whenever a user pastes a SQL query and mentions performance, slowness, or runtime.
Identifies Oracle-to-PostgreSQL migration risks by cross-referencing code against known behavioral differences (empty strings, refcursors, type coercion, sorting, timestamps, concurrent transactions, etc.). Use when planning a database migration, reviewing migration artifacts, or validating that integration tests cover Oracle/PostgreSQL differences.