How to load data from SFTP to Google Sheets

Learn how to use Airbyte to synchronize your SFTP data into Google Sheets within minutes.

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Set up a SFTP connector in Airbyte

Connect to SFTP or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Google Sheets for your extracted SFTP data

Select Google Sheets where you want to import data from your SFTP source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the SFTP to Google Sheets in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

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How to Sync SFTP to Google Sheets Manually

Begin by accessing the SFTP server where your data is stored. You can use an SFTP client like FileZilla or a command-line tool like `sftp` on Unix-based systems. Log in using your credentials to gain access to the files you need to transfer.

Once logged into the SFTP server, navigate to the directory containing the data you want to move. Use the download option in your SFTP client or the `get` command in the command line to download the file(s) to your local machine. Ensure you know the exact file format and encoding (e.g., CSV, TSV) of the data for easy processing later.

If the data is not already in CSV format, open the file using a suitable application (e.g., Excel, a text editor) and save it as a CSV file. CSV is the preferred format for easy import into Google Sheets. Make sure that the data is properly structured, with each field separated by commas and each record on a new line.

Navigate to Google Sheets in your web browser and open a new or existing spreadsheet where you want to import the data. Ensure you are logged into your Google account and have the necessary permissions to edit the spreadsheet.

In Google Sheets, click on "File" in the top menu, then select "Import." Choose "Upload" and drag your CSV file from your local machine into the upload area or use the "Select a file from your device" option. Once the file is uploaded, you will be prompted with import options. Choose "Replace current sheet" or "Append to current sheet" based on your needs, and ensure that the file delimiter is correctly set to commas.

After importing, review the data in Google Sheets to ensure that it has been transferred correctly. Check for any formatting issues or misplaced data. Use Google Sheets functions to clean or reformat the data if necessary, such as trimming whitespace, converting text to numbers, or adjusting date formats.

If you anticipate regularly updating the data, consider creating a Google Apps Script to automate the import process. Write a script that can fetch the SFTP data, convert it to CSV, and upload it to Google Sheets. While this involves more technical setup, it can save time in the long run. Google Apps Script can be accessed by clicking on "Extensions" in the menu and then selecting "Apps Script."
By following these steps, you can efficiently transfer and manage data from an SFTP server to Google Sheets without relying on third-party tools.

How to Sync SFTP to Google Sheets Manually - Method 2:

FAQs

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.

SFTP (Secure File Transfer Protocol) is a secure way to transfer files between two computers over the internet. It uses encryption to protect the data being transferred, making it more secure than traditional FTP (File Transfer Protocol). SFTP is commonly used by businesses and organizations to transfer sensitive data such as financial information, medical records, and personal data. It requires authentication using a username and password or public key authentication, ensuring that only authorized users can access the files. SFTP is also platform-independent, meaning it can be used on any operating system, making it a versatile and reliable option for secure file transfers.

SFTP provides access to various types of data that can be used for different purposes. Some of the categories of data that SFTP's API gives access to are:  

1. File data: SFTP's API allows users to access and transfer files securely over the internet. This includes uploading, downloading, and managing files.  
2. User data: SFTP's API provides access to user data such as usernames, passwords, and permissions. This allows users to manage and control access to their files and folders.  
3. Server data: SFTP's API gives access to server data such as server logs, server configurations, and server status. This allows users to monitor and manage their server resources.  
4. Security data: SFTP's API provides access to security data such as encryption keys, certificates, and security policies. This allows users to ensure that their data is secure and protected from unauthorized access.  
5. Network data: SFTP's API gives access to network data such as IP addresses, network configurations, and network traffic. This allows users to monitor and manage their network resources.

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 SFTP to Google Sheets as a source connector (using Auth, or usually an API key)
2. Choose a destination (more than 50 available destination databases, data warehouses or lakes) to sync data too and set it up as a destination connector
3. Define which data you want to transfer from SFTP to Google Sheets and how frequently
You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud. 

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.

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.

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