How to load data from TikTok Marketing to BigQuery
Learn how to use Airbyte to synchronize your TikTok Marketing data into BigQuery within minutes.
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How to Sync to Manually
Step 1: Setup Access to TikTok Marketing API
Create a Developer Account:
- Register as a developer on the TikTok Ads platform.
- Apply for access to the Marketing API by submitting your application for review. Once approved, you’ll receive credentials such as Client ID, Client Secret, and Access Token.
Authenticate Using OAuth 2.0:
Use TikTok’s OAuth flow to obtain an access token. This involves generating an authorization URL, logging in with your TikTok account, granting permissions, and exchanging the authorization code for an access token.
Test API Access:
Verify your access by sending test requests to endpoints like /v1.3/ad/get/ using tools like Postman or cURL. (Check the latest TikTok Marketing API documentation for the exact endpoint names and versions since these can change over time.)
Step 2: Extract Data from TikTok Ads
Select Relevant API Endpoints:
- Use endpoints such as GetAdDetailData to retrieve metrics like impressions, clicks, and conversions.
- Specify filters (e.g., date range, campaign IDs) in your API requests to narrow down the dataset.
Retrieve Data:
Send GET requests using your access token to fetch data in JSON format.
Save Data Locally:
Store the JSON response in a local file or database for further processing.
Step 3: Transform Data
TikTok’s API returns data in JSON format, which needs to be structured before loading into BigQuery:
Parse JSON Data:
- Extract nested fields like advertiser, ad_group, and ad from the API response.
- Flatten hierarchical data into tabular format suitable for relational databases.
Map Fields:
- Map TikTok’s data structure (e.g., impressions, clicks) to corresponding columns in BigQuery tables.
- Ensure consistency in column names and data types.
Clean Data:
- Remove unnecessary fields or rows.
- Handle missing values and ensure proper formatting of date/time fields.
Step 4: Load Data into BigQuery
Prepare BigQuery Dataset:
- Create a dataset in BigQuery to organize your tables.
- Define table schemas based on the transformed TikTok data structure.
Batch Load Using CSV or JSON Files:
- Export transformed data into CSV or newline-delimited JSON files.
- Use the BigQuery Web UI or CLI (bq load) to upload files into tables.
Streaming Load for Real-Time Updates:
If real-time updates are required, use BigQuery’s Streaming API or Pub/Sub integration to stream TikTok data directly into tables.
Step 5: Validate Migration
Verify Row Counts:
Compare row counts between the source (TikTok API response) and destination (BigQuery tables).
Check Schema Accuracy:
Ensure that all columns match the expected schema in BigQuery.
Run Sample Queries:
Query metrics like total impressions or ad spend in BigQuery and cross-check against TikTok Ads Manager reports.