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Begin by exporting your data from Notion. Navigate to the page or database you want to export. Click on the three-dot menu at the top right corner of the page, select "Export," and choose the format you prefer. For structured data, CSV is recommended as it is easy to import into DuckDB. Download the export file to your local machine.
If you haven't already, install DuckDB on your system. You can do this by visiting the DuckDB website and downloading the appropriate version for your operating system. Follow the installation instructions provided to set up DuckDB on your local machine.
Once DuckDB is installed, open a command-line interface (CLI) or terminal and launch the DuckDB shell. You can do this by typing `duckdb` and hitting enter. This will open an interactive shell where you can execute DuckDB commands.
In the DuckDB shell, create a new database for your Notion data. Use the command `CREATE DATABASE notion_data.duckdb;` to initialize a new database file named `notion_data.duckdb` in your current directory. This file will store your DuckDB database.
With the database created, you can now load your exported CSV data into DuckDB. Use the `COPY` command to import the CSV file into a new table. For example, if your file is named `notion_data.csv`, use:
```
COPY notion_table FROM 'path/to/notion_data.csv' (AUTO_DETECT TRUE);
```
Replace `'path/to/notion_data.csv'` with the actual path to your CSV file. The `AUTO_DETECT TRUE` option allows DuckDB to automatically determine the data types and delimiters.
After importing the data, it's important to verify that it has been correctly imported. Run a simple query to check the contents of the table. For example:
```
SELECT * FROM notion_table LIMIT 10;
```
This command will display the first 10 rows of your table, allowing you to confirm that the data looks as expected.
Once you've verified that the data import is successful, save your changes and exit the DuckDB shell. Your data is now stored in `notion_data.duckdb`, and you can access it anytime using DuckDB commands. To exit, simply type `.quit` or `CTRL+D` in the DuckDB shell.
By following these steps, you will have successfully moved data from Notion to DuckDB without relying on third-party connectors or integrations.
FAQs
What is ETL?
ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.
Notion is an all-in-one workspace that allows users to organize their personal and professional lives in one place. It combines features of note-taking apps, project management tools, and databases to create a customizable and flexible platform. Users can create pages, databases, and boards to manage tasks, projects, and information. Notion also offers a variety of templates and integrations with other apps to enhance productivity. Its user-friendly interface and collaborative features make it a popular choice for individuals and teams looking to streamline their workflows and stay organized.
Notion's API provides access to a wide range of data types, including:
1. Pages: This includes all the pages in a Notion workspace, including their properties and content.
2. Databases: Notion's databases are a powerful way to organize and manage data. The API provides access to all the databases in a workspace, including their properties and content.
3. Blocks: Notion's blocks are the building blocks of pages and databases. The API provides access to all the blocks in a workspace, including their content and properties.
4. Users: Notion's API provides access to information about the users in a workspace, including their name, email address, and profile picture.
5. Workspaces: The API provides access to information about the workspaces themselves, including their name and ID.
6. Integrations: Notion's API allows developers to create integrations with other tools and services, such as Slack or Zapier.
Overall, Notion's API provides a comprehensive set of tools for accessing and manipulating data within a workspace, making it a powerful platform for building custom applications and workflows.
What is ELT?
ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.
Difference between ETL and ELT?
ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:
