TL;DR

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps:

1. set up Excel File as a source connector (using Auth, or usually an API key)
2. set up DuckDB as a destination connector
3. define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is Excel File

Excel File is a software application developed by Microsoft that allows users to create, edit, and analyze spreadsheets. It is widely used in businesses, schools, and personal finance to organize and manipulate data. Excel File offers a range of features including formulas, charts, graphs, and pivot tables that enable users to perform complex calculations and data analysis. It also allows users to collaborate on spreadsheets in real-time and share them with others. Excel File is available on multiple platforms including Windows, Mac, and mobile devices, making it a versatile tool for data management and analysis.

What is DuckDB

DuckDB is an in-process SQL OLAP database management system. It has strong support for SQL. DuckDB is borrowing the SQLite shell implementation. Each database is a single file on disk. It’s analogous to “ SQLite for analytical (OLAP) workloads” (direct comparison on the SQLite vs DuckDB paper here), whereas SQLite is for OLTP ones. But it can handle vast amounts of data locally. It’s the smaller, lighter version of Apache Druid and other OLAP technologies.

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Prerequisites

1. A Excel File account to transfer your customer data automatically from.
2. A DuckDB account.
3. An active Airbyte Cloud account, or you can also choose to use Airbyte Open Source locally. You can follow the instructions to set up Airbyte on your system using docker-compose.

Airbyte is an open-source data integration platform that consolidates and streamlines the process of extracting and loading data from multiple data sources to data warehouses. It offers pre-built connectors, including Excel File and DuckDB, for seamless data migration.

When using Airbyte to move data from Excel File to DuckDB, it extracts data from Excel File using the source connector, converts it into a format DuckDB can ingest using the provided schema, and then loads it into DuckDB via the destination connector. This allows businesses to leverage their Excel File data for advanced analytics and insights within DuckDB, simplifying the ETL process and saving significant time and resources.

Methods to Move Data From Excel to duckdb

• Method 1: Connecting Excel to duckdb using Airbyte.
• Method 2: Connecting Excel to duckdb manually.

Method 1: Connecting Excel to duckdb using Airbyte

Step 1: Set up Excel File as a source connector

1. Open the Airbyte platform and navigate to the "Sources" tab on the left-hand side of the screen.
2. Click on the "Excel File" source connector and select "Create new connection."
3. In the "Connection Configuration" page, enter a name for your connection and select the version of Excel you are using.
4. Click on "Add Credential" and enter the path to your Excel file in the "File Path" field.
5. If your Excel file is password-protected, enter the password in the "Password" field.
6. Click on "Test" to ensure that the connection is successful.
7. Once the connection is successful, click on "Create Connection" to save your settings.
8. You can now use this connection to extract data from your Excel file and integrate it with other data sources on Airbyte.

Step 2: Set up DuckDB as a destination connector

1. Open the Airbyte platform and navigate to the "Destinations" tab on the left-hand side of the screen.
2. Click on the "Add Destination" button located in the top right corner of the screen.
3. Scroll down the list of available destinations until you find "DuckDB" and click on it.
4. Fill in the required information for your DuckDB database, including the host, port, database name, username, and password.
5. Test the connection to ensure that the information you provided is correct and that Airbyte can successfully connect to your DuckDB database.
6. If the connection is successful, click on the "Save" button to save your DuckDB destination connector.
7. You can now use this connector to transfer data from your source connectors to your DuckDB database. Simply select the DuckDB destination connector when setting up your data integration pipelines in Airbyte.

Step 3: Set up a connection to sync your Excel File data to DuckDB

Once you've successfully connected Excel File as a data source and DuckDB as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

1. Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
2. Choose your source: Select Excel File from the dropdown list of your configured sources.
3. Select your destination: Choose DuckDB from the dropdown list of your configured destinations.
4. Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
5. Select the data to sync: Choose the specific Excel File objects you want to import data from towards DuckDB. You can sync all data or select specific tables and fields.
6. Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
7. Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
8. Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Excel File to DuckDB according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your DuckDB data warehouse is always up-to-date with your Excel File data.

Method 2: Connecting Excel to duckdb manually

Moving data from Excel to DuckDB without using third-party connectors or integrations can be done by exporting the Excel data to a CSV file and then importing that CSV file into DuckDB. Here's a step-by-step guide to accomplish this:

Step 1: Prepare the Excel Data

1. Open your Excel workbook and ensure that the data is clean and well-structured.

2. Make sure that the first row contains column headers, as these will be used as column names in DuckDB.

3. Check for any data inconsistencies, such as non-uniform date formats, and correct them.

Step 2: Export Excel Data to a CSV File

1. In Excel, go to the worksheet that contains the data you want to export.

2. Click on 'File' > 'Save As' or press `F12` to open the 'Save As' dialog.

3. Choose the location where you want to save the file.

4. In the 'Save as type' dropdown, select 'CSV (Comma delimited) (*.csv)'.

5. Click 'Save'. If your workbook has multiple sheets, Excel will prompt you that only the active sheet will be saved in the CSV file. Click 'OK' to proceed.

6. If you receive a message about features not being compatible with CSV format, click 'Yes' to keep the workbook in this format.

Step 3: Install DuckDB (if not already installed)

1. Download DuckDB from the official website (https://duckdb.org/) or install it using a package manager like pip for Python:

   ```

   pip install duckdb

   ```

2. Follow the installation instructions appropriate for your operating system.

Step 4: Import CSV Data into DuckDB

1. Open a command-line interface (CLI) or a scripting environment where you can interact with DuckDB.

2. Start the DuckDB CLI by typing `duckdb` in your terminal or command prompt. Alternatively, you can use DuckDB in a scripting language like Python:

   ```python

   import duckdb

   con = duckdb.connect(database=':memory:', read_only=False)

   ```

3. Create a table in DuckDB that corresponds to the structure of your Excel data. For example:

   ```sql

   CREATE TABLE my_table (

       column1 INTEGER,

       column2 VARCHAR,

       column3 DATE

   );

   ```

4. Import the CSV data into the newly created table using the `COPY` command. Adjust the file path and table name accordingly:

   ```sql

   COPY my_table FROM '/path/to/your/csvfile.csv' WITH (HEADER true, DELIMITER ',');

   ```

   If using a scripting language like Python:

   ```python

   con.execute("COPY my_table FROM '/path/to/your/csvfile.csv' WITH (HEADER true, DELIMITER ',')")

   ```

Step 5: Verify the Data Import

1. To check if the data has been imported correctly, run a simple query to retrieve some records:

   ```sql

   SELECT * FROM my_table LIMIT 10;

   ```

   In Python:

   ```python

   print(con.execute("SELECT * FROM my_table LIMIT 10").fetchall())

   ```

Step 6: Save the DuckDB Database (Optional)

1. If you want to save the DuckDB database to a file for persistence, you can do so by connecting to a specific file when starting DuckDB:

   ```sql

   .open 'my_duckdb_database.duckdb'

   ```

   In Python:

   ```python

   con = duckdb.connect(database='my_duckdb_database.duckdb', read_only=False)

   ```

Step 7: Clean Up

1. If you used a temporary CSV file, you might want to delete it after the import is complete to save space and keep your working directory clean.

By following these steps, you should be able to move data from Excel to DuckDB without the need for third-party connectors or integrations. Remember to adjust file paths, table names, and column types according to your specific data and environment.

Use Cases to transfer your Excel File data to DuckDB

Integrating data from Excel File to DuckDB provides several benefits. Here are a few use cases:

1. Advanced Analytics: DuckDB’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Excel File data, extracting insights that wouldn't be possible within Excel File alone.
2. Data Consolidation: If you're using multiple other sources along with Excel File, syncing to DuckDB allows you to centralize your data for a holistic view of your operations, and to set up a change data capture process so you never have any discrepancies in your data again.
3. Historical Data Analysis: Excel File has limits on historical data. Syncing data to DuckDB allows for long-term data retention and analysis of historical trends over time.
4. Data Security and Compliance: DuckDB provides robust data security features. Syncing Excel File data to DuckDB ensures your data is secured and allows for advanced data governance and compliance management.
5. Scalability: DuckDB can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Excel File data.
6. Data Science and Machine Learning: By having Excel File data in DuckDB, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
7. Reporting and Visualization: While Excel File provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to DuckDB, providing more advanced business intelligence options. If you have a Excel File table that needs to be converted to a DuckDB table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

1. Configure a Excel File account as an Airbyte data source connector.
2. Configure DuckDB as a data destination connector.
3. Create an Airbyte data pipeline that will automatically be moving data directly from Excel File to DuckDB after you set a schedule

With Airbyte, creating data pipelines take minutes, and the data integration possibilities are endless. Airbyte supports the largest catalog of API tools, databases, and files, among other sources. Airbyte's connectors are open-source, so you can add any custom objects to the connector, or even build a new connector from scratch without any local dev environment or any data engineer within 10 minutes with the no-code connector builder.

We look forward to seeing you make use of it! We invite you to join the conversation on our community Slack Channel, or sign up for our newsletter. You should also check out other Airbyte tutorials, and Airbyte’s content hub!