How to load data from Pendo to BigQuery
Learn how to use Airbyte to synchronize your Pendo data into BigQuery within minutes.
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How to Sync to Manually
Step 1: Export Data from Pendo
Begin by exporting the data from Pendo. Log into your Pendo account and navigate to the analytics section. Use Pendo's export functionality to download the data you need. Pendo offers CSV export options, which you can use to download your data in a structured format. Make sure to format the data in a way that is compatible with BigQuery's requirements.
Step 2: Prepare Data for BigQuery
Once the data is exported, the next step is to prepare it for import into BigQuery. Ensure the CSV files are cleaned and properly formatted. Check for any inconsistencies or errors in the data that might cause issues during the upload process. Correct any malformed data entries and ensure that the data types in your CSV match the schema you plan to use in BigQuery.
Step 3: Set Up Google Cloud Project
If you haven�t already, set up a Google Cloud Platform (GCP) project. Go to the Google Cloud Console, create a new project, and enable billing if necessary. This project will host your BigQuery dataset and tables. Ensure that you have the necessary permissions to create datasets and tables within BigQuery.
Step 4: Create BigQuery Dataset and Table
In your GCP project, navigate to the BigQuery section. Create a new dataset where you will store your data. Within the dataset, create tables that match the structure of your CSV files. Define the schema for each table, specifying the correct data types for each column based on the data you exported from Pendo.
Step 5: Upload CSV Files to Google Cloud Storage
Before uploading your data to BigQuery, you need to store your CSV files in Google Cloud Storage (GCS). Open the GCS console and create a new bucket if necessary. Upload your CSV files to this bucket. GCS serves as an intermediary storage location that allows BigQuery to access your data for importing.
Step 6: Load Data from GCS to BigQuery
With your CSV files in GCS, you can now load them into BigQuery. In the BigQuery console, use the "Create Table" option and select "Google Cloud Storage" as the source. Provide the URI of your GCS bucket and files. Ensure you select the correct file format (CSV) and specify the schema if not already done. Execute the load job to import your data into BigQuery.
Step 7: Verify Data Integrity in BigQuery
After loading the data, verify its integrity in BigQuery. Run queries to check that the data has been imported correctly and that there are no discrepancies. Compare a sample of the data in BigQuery with your original Pendo export to ensure accuracy. Fix any issues that arise, such as data type mismatches or missing data, by adjusting your import process and reloading the data if necessary.