Total 54,287 skills, Data Processing has 2781 skills
Showing 12 of 2781 skills
AKShare is an open-source financial data interface library that provides full-category financial data including stocks, futures, options, funds, foreign exchange, bonds, indices, and cryptocurrencies; it is used when users need to obtain various financial market data
Obtain securities and financial information such as A-share market quotes, historical K-lines, financial data, macroeconomic data; Use this when users mention Tushare or need to obtain A-share data
EODHD APIs integration. Manage data, records, and automate workflows. Use when the user wants to interact with EODHD APIs data.
Workload-aware architecture design for Apache Doris. MUST USE when designing data architectures, choosing between data models, planning ingestion strategies, sizing clusters, or translating business requirements into Apache Doris system designs. Complements doris-best-practices with decision frameworks and sizing-first workflow. Use when user describes a workload involving: IoT, sensor data, telemetry, real-time analytics, dashboard, log analysis, log search, CDC sync, time-series, device monitoring, point query service, ad-hoc analytics, lakehouse federation, ETL/ELT pipeline, report analytics, clickstream, user behavior, observability, metrics, fleet tracking, or any OLAP workload requiring table design from scratch. Also triggers on prompts like: "design a table for...", "how should I store...", "build an architecture for...", "we have X devices sending data every Y seconds", "recommend a cluster size for...", "what data model should I use for...", "we need to ingest X GB/day", "migrate from MySQL/PostgreSQL to Apache Doris". Also use for legacy analytics/search/serving stack consolidation prompts even when Apache Doris is not named explicitly, including replacing or migrating from Impala, Kudu, Elasticsearch/ES, Greenplum, Presto, HBase, Hive, Hadoop, Redis, or Lambda-style multi-engine data platforms.
Use when defining field mappings for data streams, populating ecs.yml with ECS field references, selecting ECS categorization values, choosing custom field types, or troubleshooting mapping validation failures.
Financial statements, business segments, dividends, valuation multiples (PE/PB/PS), industry comparison, operating data, corporate actions, company and executive profiles, cross-stock comparison, and valuation ranking via Longbridge. Also: DCF models, value investing screens (low PE/PB, margin of safety), and behavioral finance analysis frameworks. Triggers: "财报", "三表", "利润表", "资产负债", "现金流", "估值", "PE", "PB", "分红", "公司信息", "高管", "行业估值", "并购", "DCF", "内在价值", "低估值", "安全边际", "行为金融", "小盘成长", "专精特新", "財報", "估值", "分紅", "內在價值", "安全邊際", "financial report", "income statement", "balance sheet", "valuation", "dividend", "company info", "industry valuation", "DCF", "value screen", "behavioral finance", "利潤表", "資產負債", "現金流", "行業估值", "併購", "行為金融", "小盤成長"
Develop and deploy Data Cloud Code Extensions using SF CLI plugin. Use this skill when creating custom Python transformations for Data Cloud, deploying code extensions, or testing data transformations. Supports init, run, scan, and deploy operations.
Salesforce Data Cloud Retrieve phase. Use this skill when the user runs Data Cloud SQL, async queries, vector search, search-index workflows, or metadata introspection for Data Cloud objects. TRIGGER when: user runs Data Cloud SQL, describe, async queries, vector search, search-index workflows, or metadata introspection for Data Cloud objects. DO NOT TRIGGER when: the task is standard CRM SOQL (use platform-soql-query), segment creation or calculated insight design (use data360-segment), or STDM/session tracing/parquet analysis (use agentforce-observe).
Manages Google Analytics reporting data, enables the Analytics Data API via the Cloud CLI, and creates reports using the Google Analytics Data API (v1beta). Use when you need to interact with Google Analytics properties, run customized analytics reports, query metrics (like activeUsers, screenPageViews) and dimensions (like city, date), check metrics and dimensions compatibility, or verify API enablement.
Query NCBI Gene via E-utilities/Datasets API. Search by symbol/ID, retrieve gene info (RefSeqs, GO, locations, phenotypes), batch lookups, for gene annotation and functional analysis.
Direct REST API access to KEGG (academic use only). Pathway analysis, gene-pathway mapping, metabolic pathways, drug interactions, ID conversion. For Python workflows with multiple databases, prefer bioservices. Use this for direct HTTP/REST work or KEGG-specific control.
NGS analysis toolkit. BAM to bigWig conversion, QC (correlation, PCA, fingerprints), heatmaps/profiles (TSS, peaks), for ChIP-seq, RNA-seq, ATAC-seq visualization.