Results for “data-warehouse”

Integrate with Benchling's Python SDK and REST API to manage registry entities, inventory, ELN entries, workflows, and Data Warehouse queries for life sciences R&D automation.

Transforms data in warehouses using dbt with SQL models, tests, and documentation. Use for analytics engineering and data transformation.

Provides ClickHouse-specific patterns for schema design, query optimization, data ingestion, and analytics, including materialized views and performance monitoring.

Design, build, and optimize Microsoft Fabric Lakehouse solutions with guidance on core concepts, components, security, shortcuts, and performance optimization.

Create and validate Earth2Studio data source wrappers (DataSource, ForecastSource, DataFrameSource, ForecastFrameSource) from remote stores like S3, GCS, Azure, HTTP, or HuggingFace.

ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.

ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.

Provides ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.

ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.

Extract Warehouse DDL & Metadata

Designs and implements big data architectures, processes large-scale datasets with distributed systems, and optimizes data pipelines for throughput using Hadoop, Spark, and cloud platforms.

Provides ClickHouse schema design, query optimization, and data ingestion patterns for high-performance analytical workloads.

Build synthetic datasets and data generation pipelines using the Data Designer library.

Generate production-ready Dataverse SDK solutions with architecture recommendations, data models, and implementation code for common business use cases.

For analysis/task/review agents using a Professional Skill on batch, stream, warehouse, lineage, replay, or data quality; not for transactions without distributed-data impact.

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

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

Guides database design, implementation, optimization, migrations, data pipelines, and operations across SQL and NoSQL platforms.

Manage biological datasets and models with LaminDB, an open-source lineage-native lakehouse. Covers setup, artifact registration, query/search, lineage tracking, validation, ontology-backed annotation, collections, branches, storage, and workflow integrations.

Agent profile for design data pipelines, transformations, imports, exports, warehouse models, validation, and freshness checks. Use when Codex needs a specialist agent perspective for planning, implementation, review, debugging, validation, or handoff in this domain.

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

Expert database architect specializing in data layer design from scratch, technology selection, schema modeling, and scalable database architectures. Masters SQL/NoSQL/TimeSeries database selection, normalization strategies, migration planning, and performance-first design. Handles both greenfield architectures and re-architecture of existing systems. Use PROACTIVELY for database architecture, technology selection, or data modeling decisions.

Provides a SQLite-backed persistence layer for skill execution metrics, feedback, improvement candidates, and version history, with query and maintenance workflows.

Transforms raw data into analytics-ready models using dbt, covering models, tests, macros, sources, snapshots, documentation, and packages.

Documenta, versiona y cierra proyectos de análisis de datos para que queden ordenados y reproducibles en el futuro.

Expert guidance for Cube, the headless BI and semantic layer that sits between your data warehouse and analytics applications. Helps developers define data models, create metrics APIs, and build analytics features in applications with consistent, governed access to business metrics.

Analyze product data and manage product tooling in PostHog. Use when the user wants product analytics or insights, HogQL/SQL queries, feature flags, experiments and A/B tests, error tracking, session replay, surveys, LLM analytics, dashboards, data warehouse, or PostHog documentation.

You are a data triager that answers data questions by routing them across a network of skills and agents. These questions may involve pulling data from a Snowflake warehouse, computing metrics, locating relevant tables or fields, diagnosing a metric change, or performing exploratory analysis. Your job is to determine how to answer a question and which skills and subagents to invoke.

You are a data triager that answers data questions by routing them across a network of skills and agents. These questions may involve pulling data from a Snowflake warehouse, computing metrics, locating relevant tables or fields, diagnosing a metric change, or performing exploratory analysis. Your job is to determine how to answer a question and which skills and subagents to invoke.