Creating interactive dashboards is essential for data-driven decision making in modern organizations. Combining Dagster, a data orchestrator, with Metabase, a business intelligence tool, allows you to automate data pipelines and visualize data effectively. This step-by-step tutorial guides you through the process of building interactive dashboards using these powerful tools.

Prerequisites

  • Basic knowledge of Python and SQL
  • Installed Docker on your machine
  • Accounts for Dagster Cloud or local setup
  • Metabase installed locally or on a server

Setting Up Dagster

Start by creating a new Dagster project. Use Docker to run Dagster services locally for development and testing.

Initialize a new Dagster repository:

dagster project scaffold my_project

Navigate into your project directory and start the Dagster UI:

cd my_project
docker-compose up -d

Creating a Data Pipeline

Define a pipeline that extracts data from your source, transforms it, and loads it into a database accessible by Metabase.

Example Python code for a simple pipeline:

from dagster import pipeline, solid
import pandas as pd

@solid
def extract_data(context):
    data = pd.read_csv('data.csv')
    return data

@solid
def transform_data(context, data):
    data['new_column'] = data['existing_column'] * 2
    return data

@solid
def load_data(context, data):
    data.to_sql('my_table', con=your_database_connection, if_exists='replace')
    
@pipeline
def my_pipeline():
    data = extract_data()
    transformed = transform_data(data)
    load_data(transformed)

Configuring Metabase

Set up Metabase to connect to your database where Dagster loads the data. Access Metabase via your browser and add a new database connection.

Enter your database details, test the connection, and save.

Creating a Dashboard

Use Metabase's interface to create questions (queries) based on your data. Save these questions to include in your dashboard.

Arrange questions on the dashboard, add filters, and customize the layout for interactivity.

Automating Data Refresh

Schedule Dagster to run your pipeline at regular intervals, ensuring your dashboard reflects the latest data.

In Dagster, add a schedule to trigger your pipeline:

from dagster import schedule

@schedule(cron_schedule="0 0 * * *", job=my_pipeline)
def daily_schedule():
    return {}  # No configuration needed

Configure Dagster to run this schedule automatically.

Final Tips

Test your pipeline and dashboard thoroughly. Use Metabase's sharing features to distribute dashboards to stakeholders. Continuously monitor and optimize your data pipelines for better performance and insights.