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How to load data from TPLcentral to Google Firestore

Learn how to use Airbyte to synchronize your TPLcentral data into Google Firestore within minutes.

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 TPLcentral as a source connector (using Auth, or usually an API key)
  2. set up Google Firestore 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 TPLcentral

TPLcentral is a platform that provides a comprehensive solution for managing and optimizing third-party logistics (3PL) operations. It offers a range of tools and features that enable businesses to streamline their supply chain processes, improve visibility and control, and enhance collaboration with their 3PL partners. TPLcentral's cloud-based software allows users to manage inventory, orders, shipments, and billing in real-time, while also providing analytics and reporting capabilities to help businesses make data-driven decisions. The platform is designed to be user-friendly and customizable, making it suitable for businesses of all sizes and industries. Overall, TPLcentral aims to simplify and improve the 3PL experience for businesses and their partners.

What is Google Firestore

Google Firestore is a cloud-based NoSQL document database that allows developers to store, sync, and query data for their web, mobile, and IoT applications. It is designed to provide real-time updates and offline support, making it ideal for applications that require fast and responsive data access. Firestore offers a flexible data model, allowing developers to store data in collections and documents, and supports complex queries and transactions. It also integrates with other Google Cloud services, such as Cloud Functions and Cloud Storage, to provide a complete backend solution for building scalable and reliable applications.

Integrate TPLcentral with Google Firestore in minutes

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Prerequisites

  1. A TPLcentral account to transfer your customer data automatically from.
  2. A Google Firestore 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 TPLcentral and Google Firestore, for seamless data migration.

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

Step 1: Set up TPLcentral as a source connector

1. First, navigate to the TPLcentral source connector on Airbyte's website.
2. Click on the ""Get Source"" button to download the connector.
3. Extract the downloaded file to a folder on your computer.
4. Open the folder and locate the ""config.json"" file.
5. Open the ""config.json"" file in a text editor and fill in the required fields with your TPLcentral API credentials.
6. Save the ""config.json"" file and close the text editor.
7. Open a terminal or command prompt and navigate to the folder where you extracted the connector files.
8. Run the command ""docker-compose up"" to start the connector.
9. Once the connector is running, navigate to Airbyte's web interface and click on ""Create Connection"".
10. Select the TPLcentral source connector from the list of available connectors.
11. Fill in the required fields with the necessary information, such as the name of the connection and the credentials for your TPLcentral account.
12. Test the connection to ensure that it is working properly.
13. If the connection is successful, save the connection and start syncing data from TPLcentral to your desired destination.

Step 2: Set up Google Firestore as a destination connector

1. First, navigate to the Airbyte website and log in to your account.
2. Once you are logged in, click on the "Destinations" tab on the left-hand side of the screen.
3. Scroll down until you find the "Google Firestore" destination connector and click on it.
4. You will be prompted to enter your Google Cloud Platform project ID and a service account key. Follow the instructions provided to obtain these credentials.
5. Once you have entered your credentials, click on the "Test" button to ensure that the connection is successful.
6. If the test is successful, click on the "Save" button to save your configuration.
7. You can now use the Google Firestore destination connector to transfer data from your source to your Google Firestore database.
8. To set up a data integration pipeline, navigate to the "Sources" tab and select the source connector you wish to use.
9. Follow the instructions provided to configure your source connector and select the Google Firestore destination connector as your destination.
10. Once you have configured your pipeline, click on the "Run" button to start transferring data from your source to your Google Firestore database.

Step 3: Set up a connection to sync your TPLcentral data to Google Firestore

Once you've successfully connected TPLcentral as a data source and Google Firestore 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 TPLcentral from the dropdown list of your configured sources.
  3. Select your destination: Choose Google Firestore 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 TPLcentral objects you want to import data from towards Google Firestore. 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 TPLcentral to Google Firestore according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your Google Firestore data warehouse is always up-to-date with your TPLcentral data.

Use Cases to transfer your TPLcentral data to Google Firestore

Integrating data from TPLcentral to Google Firestore provides several benefits. Here are a few use cases:

  1. Advanced Analytics: Google Firestore’s powerful data processing capabilities enable you to perform complex queries and data analysis on your TPLcentral data, extracting insights that wouldn't be possible within TPLcentral alone.
  2. Data Consolidation: If you're using multiple other sources along with TPLcentral, syncing to Google Firestore 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: TPLcentral has limits on historical data. Syncing data to Google Firestore allows for long-term data retention and analysis of historical trends over time.
  4. Data Security and Compliance: Google Firestore provides robust data security features. Syncing TPLcentral data to Google Firestore ensures your data is secured and allows for advanced data governance and compliance management.
  5. Scalability: Google Firestore can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding TPLcentral data.
  6. Data Science and Machine Learning: By having TPLcentral data in Google Firestore, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
  7. Reporting and Visualization: While TPLcentral provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to Google Firestore, providing more advanced business intelligence options. If you have a TPLcentral table that needs to be converted to a Google Firestore table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

  1. Configure a TPLcentral account as an Airbyte data source connector.
  2. Configure Google Firestore as a data destination connector.
  3. Create an Airbyte data pipeline that will automatically be moving data directly from TPLcentral to Google Firestore 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!

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Frequently Asked Questions

What data can you extract from TPLcentral?

TPLcentral's API provides access to a wide range of data related to shipping and logistics. The following are the categories of data that can be accessed through the API:

1. Shipment data: This includes information about the shipment such as the tracking number, carrier, origin, destination, weight, and dimensions.

2. Carrier data: This includes information about the carrier such as their name, contact information, and service offerings.

3. Rate data: This includes information about the rates charged by carriers for different shipping services.

4. Transit time data: This includes information about the estimated time it will take for a shipment to reach its destination.

5. Address validation data: This includes information about the validity and accuracy of shipping addresses.

6. Customs data: This includes information about customs regulations and requirements for international shipments.

7. Inventory data: This includes information about the availability and location of inventory items.

8. Order data: This includes information about customer orders, including order status and tracking information.

Overall, TPLcentral's API provides a comprehensive set of data that can be used to optimize shipping and logistics operations.

What data can you transfer to Google Firestore?

You can transfer a wide variety of data to Google Firestore. This usually includes structured, semi-structured, and unstructured data like transaction records, log files, JSON data, CSV files, and more, allowing robust, scalable data integration and analysis.

What are top ETL tools to transfer data from TPLcentral to Google Firestore?

The most prominent ETL tools to transfer data from TPLcentral to Google Firestore include:

  • Airbyte
  • Fivetran
  • Stitch
  • Matillion
  • Talend Data Integration

These tools help in extracting data from TPLcentral and various sources (APIs, databases, and more), transforming it efficiently, and loading it into Google Firestore and other databases, data warehouses and data lakes, enhancing data management capabilities.