AI tools for “data”
852 results (tools & skills) · 152 ms · understood as category: Data & Analytics
…upcoming, not-yet-listed company using its S-1/F-1 plus Bigdata.com data. Covers deal structure (price range, shares, greenshoe, implied valuation, underwriters, lock-ups, share classes), two years plus interim…
The entry point to all Bright Data skills - start here, and it guides the agent to the right skill for the task at hand - web data and scraping, fetching or unblocking a page, search, browser automation, and the CLI,…
Set up checked-in seed data so authenticated HawkScan can reach non-trivial paths. Drives the `hawk perch seed` preflight, designs the minimum seed manifest from the repo digest, then validates and finalizes it via…
…feature, fix, or prioritization task where Pendo usage data, signals, issues, or customer feedback could ground the plan in real product behavior — e.g. "plan a fix for the pricing-page dropoff", "what should I…
Adds and runs data quality checks (dbt-test style assertions) on a project's warehouse tables and saved-query views, and HogQL catalog metrics: not-null, uniqueness, accepted values, referential integrity, row-count…
Finds out why a data quality check failed or errored, looks at the rows it matched, and recommends the fix. Also covers a materialized view refresh that the data quality gate did not publish. Use when asked why a check…
Get PostHog data into a canvas correctly: the host-injected `ph` SDK (loadInsight, query, capture, state, connectors, openExternal, navigate), the data hierarchy (saved insights first, typed query nodes second, inline…
Explains how to query PostHog data, defaulting to typed runners for supported product analytics. Read it before you write HogQL/SQL. Also read it before you call execute-sql against PostHog. Use it to find or aggregate…
Signals scout for PostHog data pipelines — CDP destinations and transformations, batch exports, and hog flows. Watches for delivery failures, degraded functions, and stalled exports against each pipeline's baseline.
Signals scout for warehouse imports. Watches external data sources, sync schemas, webhook push channels, and materialized views for failures, silent staleness, and row-volume cliffs, and suggests materialization…
Populates and maintains a project's data catalog (semantic layer): canonical metrics, trust marks (certifications) on warehouse tables/views, and reviewed table relationships. Use when asked to set up / seed / bootstrap…
Guide the user through connecting a new data warehouse source, including databases, SaaS tools, and bucket files. Use when the user wants to "connect Stripe", "import data from Postgres", "import files from a bucket",…
Guides Qdrant data volume scaling decisions. Use when someone asks 'data doesn't fit on one node', 'too much data', 'need more storage', 'vertical or horizontal scaling', 'tenant scaling', 'time window rotation', or…
…billing, CRM deals, support tickets, ad spend, production database tables, bucket files, or local file uploads. Also use when the user wants to join PostHog events with external data, or when a query fails because an…
Use Superset MCP data-returning tools for chart data, chart previews, rendered chart SQL, and dataset query results. Use only for MCP tool workflows; do not use for direct API work.
Use Superset MCP tools for dataset inspection, semantic-layer querying, and virtual dataset creation. Use only for MCP tool workflows; do not use for direct API work.
Inspect Preset workspace datasets, database metadata, schemas, tables, columns, metrics, and dataset/database workflow routing through direct Superset API calls. Use only for direct API workflows; Do not use for…
Inspect or route Preset database connection configuration, validation, OAuth, upload, create, update, and delete workflows through direct Superset API calls. Use only for direct API workflows; Do not use for MCP-only…
Use when creating or repairing dataset manifests, or when a collection needs queried or joined test inputs, a reusable named view, spreadsheet worksheet data, live database rows, or script access through pm.datasets().…
Builds Databricks data products from live web data, end to end: discovers the right Nimble web-data agents, scrapes into Delta tables, and produces an AI/BI dashboard and/or a deployed Databricks App — a table →…