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AI Business Cloud Core Data Infrastructure

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Analyze salaries of data professionals using a SQL query in DuckDB

Download a CSV, run a SQL aggregation in DuckDB, and export the results back to CSV.

Build a Python ELT pipeline to extract Google Analytics data and load it into DuckDB with dlt

Create a production-ready ELT pipeline in Python that pulls analytics data from Google Analytics (GA4) and loads it into DuckDB using dlt (data load tool).

Build a Python pipeline to load JSON API data into DuckDB using dlt

Extract JSON from a REST API and load it into DuckDB with dlt, fully orchestrated in a single Python task.

DocumentDB analytics report with Slack digest

Aggregate a day of DocumentDB orders, export the summary to CSV, and post a Slack digest with real figures.

Download a Parquet file from Databricks DBFS and process it with Python

Download a Parquet file from Databricks DBFS into Kestra and inspect it with a Python and Pandas script.

Execute dbt transformations on Snowflake using a Git-based workflow

Clone a dbt project from Git and run it against Snowflake in an isolated Docker container, end to end with Kestra.

Fetch data from Apache Druid and transform it in Python with Pandas

Query Apache Druid with SQL, export to CSV, and analyze the results in Python with Pandas.

Getting started with Kestra, a Data Warehouse and Analytics workflow example

Clone a dbt project from Git, build it on DuckDB, and export the modeled tables to CSV.

Ingest a public JSON API into DocumentDB

Fetch a JSON API and upsert every record into a DocumentDB collection, idempotently.

Ingest Zendesk data into DuckDB using dlt

Extract Zendesk support tickets into DuckDB with a dlt Python pipeline orchestrated by Kestra.

Ingest Zendesk data into Weaviate using dlt

Load Zendesk support tickets into a Weaviate vector store with dlt, ready for semantic search and RAG.

Load Pipedrive CRM data into BigQuery with a scheduled dlt pipeline

Sync Pipedrive CRM data into BigQuery every hour with a dlt Python pipeline orchestrated by Kestra.

Monitor MySQL DELETE events in real time with Debezium and send Slack alerts

Stream MySQL change data capture events with Debezium and fire a Slack alert the instant a row is deleted.

Query data from Dremio and process it in Polars with a Python script

Query a Dremio lakehouse with SQL, then transform the results in Python with Polars.

Query data from Druid and load it to Redshift

Query Apache Druid, convert results to CSV, stage them on S3, and load into Amazon Redshift.

Run a dbt job and Hightouch sync, send a Telegram message on workflow completion

Run a dbt transformation, push the results to operational tools with a Hightouch reverse ETL sync, then notify your team on Telegram.

Run a scheduled ELT pipeline in Python: extract Chess.com API data and load it into DuckDB with dltHub

Run a Python ELT pipeline with dlt that extracts Chess.com API data and loads it into DuckDB on a schedule.

Run dbt ELT pipelines on MotherDuck from Git using Docker

Run a full dbt build against MotherDuck, cloning your dbt project from Git and executing it in a reproducible Docker container.

Run dbt ELT pipelines on Postgres from Git using Docker

Run a dbt ELT pipeline on PostgreSQL by cloning a dbt project from Git and executing dbt build inside a Docker container.

Run dbt ELT pipelines with DuckDB from Git using Docker

Clone a dbt project from Git and run dbt deps plus dbt build on DuckDB inside one Docker container.

Run dbt models on Amazon Redshift directly from a Git repository

Pull a dbt project from Git and run dbt build against Amazon Redshift inside a reproducible Docker container.

Run dbt transformations on DuckDB from Git for local analytics and ELT

Run dbt Core transformations on DuckDB straight from a Git repository for fast, reproducible, zero-infrastructure analytics.

Scheduled dbt Core Run with Failure Alerting

Run dbt Core models and tests on a schedule and alert Slack the moment a build or test fails.

Upsert a DocumentDB record from an external source

Keep a DocumentDB collection in sync with an external source using a serialized, race-safe emulated upsert and optional id-scoped retirement.