Dados e Análise

SDK do Azure Data Lake Storage Gen2 para Python, utilizado para sistemas de arquivos hierárquicos, análise de big data e operações de arquivo/diretório.

Azure Data Lake Storage Gen2 SDK for Python. Use for hierarchical file systems, big data analytics, and file/directory operations.

Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, faster pandas replacement. For larger-than-RAM data use dask or vaex.

Interactive visualization library. Use when you need hover info, zoom, pan, or web-embeddable charts. Best for dashboards, exploratory analysis, and presentations. For static publication figures use matplotlib or scientific-visualization.

Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.

Azure PostgreSQL Flexible Server SDK for .NET. Database management for PostgreSQL Flexible Server deployments.

SDK v2 do Azure Machine Learning para Python. Use para workspaces de ML, trabalhos, modelos, conjuntos de dados, computação e pipelines.

Automatize consultas de banco de dados Supabase, gerenciamento de tabelas, administração de projetos, armazenamento, funções de borda e execução de SQL via Rube MCP (Composio). Sempre pesquise as ferramentas primeiro para os esquemas atuais.

Orientação especializada para bancos de dados NoSQL distribuídos (Cassandra, DynamoDB). Foca em modelos mentais, modelagem query-first, design de tabela única e como evitar hot partitions em sistemas de alta escala.

Database development and operations workflow covering SQL, NoSQL, database design, migrations, optimization, and data engineering.

Comprehensive Snowflake development assistant covering SQL best practices, data pipeline design (Dynamic Tables, Streams, Tasks, Snowpipe), Cortex AI functions, Cortex Agents, Snowpark Python, dbt integration, performance tuning, and security hardening.

Design a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features