Results for “data-table”

Generates a comprehensive, editable schema reference file for a data warehouse, including table metadata, row counts, and codebase context, to enable instant concept-to-table lookups.

Documents MariaDB-specific UPDATE syntax and behavior, including single-table vs multi-table forms, assignment evaluation order, RETURNING with OLD_VALUE(), temporal tables, and common pitfalls. Use when writing, generating, or reviewing UPDATE statements targeting MariaDB.

Access and manage NocoDB databases, tables, and records via REST API. Use when the user wants to view bases, list tables, inspect column schemas, query or filter row data, or insert new records into a self-hosted NocoDB instance. Also use for spreadsheet-style database lookups and data entry.

Performs astronomical data analysis with astropy: coordinate transformations, unit conversions, FITS file handling, cosmological calculations, time systems, tables, and WCS.

Analyzes the downstream impact (blast radius) when a BigQuery table or view is broken, stale, or modified, identifying all affected downstream tables, dashboards, and processes.

Performs astronomical data analysis with astropy: coordinate transformations, unit conversions, FITS file handling, cosmological calculations, time handling, and table operations.

Perform astronomical research and data analysis with coordinate transformations, unit conversions, FITS file handling, cosmological calculations, time handling, and table operations.

Bulk-load text files into MariaDB tables using the mariadb-import client, covering table-name-from-filename rules, TAB defaults, --local vs server-side reads, duplicate handling, and parallel loads.

Automate Snowflake data warehouse operations: list databases, schemas, and tables, execute SQL statements, and manage data workflows via the Composio MCP integration.

Compare identical tables across two SQL Server instances using Python with mssql-python and Apache Arrow, detecting missing rows, column mismatches, schema drift, and generating a reconciliation report.

Diagnose and observe an Oxla distributed analytical database using system catalog tables, Prometheus metrics, runtime log-level changes, and troubleshooting workflows for slow queries, node health, and memory/OOM pressure. Also covers debugging Oxla's external data sources, including the Redpanda/Kafka ingestion path.

Provides reference information and CLI commands for Azure Storage services including Blob, File Shares, Queue, Table, and Data Lake, along with guidance on access tiers, redundancy options, and SDK usage.

Converts CSV, Excel, or JSON data into a polished, interactive visual report page with KPI cards, charts, data tables, and insights.

Provision Bigtable instances, design performant schemas, and query data using gcloud, cbt, or client libraries.

Manage datasets, tables, and jobs in BigQuery. Run SQL queries, manage BigQuery resources, and perform basic data ingestion and analysis.

Write and run analytical SQL queries against Redpanda SQL (Oxla), a distributed PostgreSQL-wire-compatible columnar database, including data loading, external sources, and type handling.

Structured data + RAG. NL2SQL hybrid patterns (text-to-SQL then execute vs embed rows), table embedding strategies (row-level, schema-level, hybrid), semantic layer integration (Cube, dbt metrics), LangChain SQLDatabaseChain, LlamaIndex PandasQueryEngine, safe SQL execution (read-only, sandboxed), schema-aware retrieval. Full PostgreSQL + pgvector hybrid code. USE WHEN: user mentions "tabular RAG", "NL2SQL", "text to SQL", "RAG on tables", "database RAG", "SQL RAG", "semantic layer", "structured data RAG" DO NOT USE FOR: unstructured doc RAG - use `rag-architecture`; metadata filtering only - use `self-querying-retriever`; KG retrieval - use `graph-rag`

Reads from, writes to, and manages relational databases using MATLAB Database Toolbox. Use when connecting to databases, reading data with sqlread or fetch, filtering with rowfilter, writing with sqlwrite, updating with sqlupdate, executing SQL statements, managing transactions with commit and rollback, mapping MATLAB classes to tables with ORM (Mappable, ormread, ormwrite, ormupdate), or performing any database operation from MATLAB. Triggers on: database, SQL, sqlread, sqlwrite, sqlupdate, fetch, execute, rowfilter, RowFilter, ORM, Mappable, ormread, ormwrite, ormupdate, orm2sql, transaction, commit, rollback, Database Toolbox, PostgreSQL, MySQL, SQLite, SQL Server, Oracle, database connection, database table, query database, insert data, update rows, delete rows, stored procedure, prepared statement, odbc, databaseConnectionOptions, datasource, data source, DSN, connection string, multithreaded, parallel.

Create clear, effective charts and dashboards from structured data using matplotlib, seaborn, and plotly. Use when the user requests data visualization or provides relevant inputs for this workflow.

Use this skill for any data or analytics task — querying databases, analyzing metrics, exploring data warehouses, processing datasets, or creating visualizations.

Provides safe, reversible database schema change patterns for PostgreSQL, MySQL, and common ORMs, with guidance on zero-downtime deployments, rollbacks, and migration tooling.

Use this skill for any data or analytics task — querying databases, analyzing metrics, exploring data warehouses, processing datasets, or creating visualizations.

Generates SQL queries against a custom database schema (Vika/Airtable-like) to look up table names, dst_ids, records, and field metadata.

Oracle Database specific features. Covers data types, sequences, synonyms, partitioning, and Oracle-specific SQL syntax. Use for Oracle database work. USE WHEN: user mentions "oracle", "oracle database", "sequences", "synonyms", "DUAL", "SYSDATE", "NVL", "DECODE", "Oracle partitioning", "Oracle specifics" DO NOT USE FOR: PostgreSQL - use `postgresql` instead, SQL Server - use `sqlserver` instead, PL/SQL programming - use `plsql` instead

Data analysis best practices with pandas, numpy, matplotlib, seaborn, and Jupyter notebooks.

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.

Execute SQL on a Databricks SQL Warehouse

Administra bases de datos PostgreSQL, MySQL, Redis y SQLite: diseña esquemas, optimiza queries, configura migraciones, replicación y backups.

DataFrame operations with pandas and polars — groupby, joins, reshaping, performance. Use when manipulating tabular data, choosing between pandas and polars, optimizing DataFrame code, or translating between the two libraries.