How to load data from Adjust to Teradata
Learn how to use Airbyte to synchronize your Adjust data into Teradata within minutes.
Building your pipeline or Using Airbyte
Airbyte is the only open source solution empowering data teams to meet all their growing custom business demands in the new AI era.
Building in-house pipelines
- Inconsistent and inaccurate data
- Laborious and expensive
- Brittle and inflexible
After Airbyte
- Reliable and accurate
- Extensible and scalable for all your needs
- Deployed and governed your way
Start syncing with Airbyte in 3 easy steps within 10 minutes
Take a virtual tour
Demo video of Airbyte Cloud
Demo video of AI Connector Builder
Setup Complexities simplified!
Simple & Easy to use Interface
Airbyte is built to get out of your way. Our clean, modern interface walks you through setup, so you can go from zero to sync in minutes—without deep technical expertise.
Guided Tour: Assisting you in building connections
Whether you’re setting up your first connection or managing complex syncs, Airbyte’s UI and documentation help you move with confidence. No guesswork. Just clarity.
Airbyte AI Assistant that will act as your sidekick in building your data pipelines in Minutes
Airbyte’s built-in assistant helps you choose sources, set destinations, and configure syncs quickly. It’s like having a data engineer on call—without the overhead.
What sets Airbyte Apart
Modern GenAI Workflows
Streamline AI workflows with Airbyte: load unstructured data into vector stores like Pinecone, Weaviate, and Milvus. Supports RAG transformations with LangChain chunking and embeddings from OpenAI, Cohere, etc., all in one operation.
Move Large Volumes, Fast
Quickly get up and running with a 5-minute setup that enables both incremental and full refreshes for databases of any size, seamlessly scaling to handle large data volumes. Our optimized architecture overcomes performance bottlenecks, ensuring efficient data synchronization even as your datasets grow from gigabytes to petabytes.
An Extensible Open-Source Standard
More than 1,000 developers contribute to Airbyte’s connectors, different interfaces (UI, API, Terraform Provider, Python Library), and integrations with the rest of the stack. Airbyte’s AI Connector Builder lets you edit or add new connectors in minutes.
Full Control & Security
Airbyte secures your data with cloud-hosted, self-hosted or hybrid deployment options. Single Sign-On (SSO) and Role-Based Access Control (RBAC) ensure only authorized users have access with the right permissions. Airbyte acts as a HIPAA conduit and supports compliance with CCPA, GDPR, and SOC2.
Fully Featured & Integrated
Airbyte automates schema evolution for seamless data flow, and utilizes efficient Change Data Capture (CDC) for real-time updates. Select only the columns you need, and leverage our dbt integration for powerful data transformations.
Enterprise Support with SLAs
Airbyte Self-Managed Enterprise comes with dedicated support and guaranteed service level agreements (SLAs), ensuring that your data movement infrastructure remains reliable and performant, and expert assistance is available when needed.
What our users say
Raman Singh
Predictable, straightforward pricing model that simplified budgeting and significantly reduced overall spend
Chase Zieman
“Airbyte helped us accelerate our progress by years, compared to our competitors. We don’t need to worry about connectors and focus on creating value for our users instead of building infrastructure. That’s priceless. The time and energy saved allows us to disrupt and grow faster.”
Rupak Patel
"With Airbyte, we could just push a few buttons, allow API access, and bring all the data into Google BigQuery. By blending all the different marketing data sources, we can gain valuable insights."
How to Sync to Manually
Step 1: Extract Data from Adjust
Begin by using Adjust's API to extract the data you need. You will have to authenticate using your API token and specify the data type and date range for extraction. You can use a script in a language like Python to send HTTP requests to the Adjust API and save the response data in a structured format like JSON or CSV.
Step 2: Transform and Clean Data
Once you've extracted the data, clean and transform it to match the schema of your Teradata database. This may involve normalizing data types, handling missing values, and restructuring JSON data into tabular format. This transformation can be performed using Python libraries such as Pandas or by writing SQL scripts if you have access to a local SQL environment.
Step 3: Create Teradata Table Structure
Before importing data, ensure your Teradata database has the necessary table structures to accommodate the incoming data. Use Teradata SQL Assistant or a suitable command-line interface to create tables with the appropriate columns and data types.
Step 4: Convert Data to Teradata-Compatible Format
Convert your cleaned and transformed data into a format compatible with Teradata's bulk loading utilities. This often involves converting your data into CSV or a delimited text file. Ensure your file format matches the field separators and line endings expected by Teradata.
Step 5: Transfer Data to Teradata Server
Transfer the prepared data file to the Teradata server environment. You can use secure file transfer methods such as SFTP or SCP to move the file from your local machine or a cloud environment to the Teradata server.
Step 6: Load Data Using Teradata FastLoad or MultiLoad
Utilize Teradata's native utilities like FastLoad or MultiLoad to import the data file into your Teradata tables. These utilities are designed for high-speed data loading and can handle large volumes of data efficiently. Follow the utility documentation to set up the loader scripts, specifying the source data file and the target table.
Step 7: Verify and Validate Data Integrity
Once the data is loaded, run validation queries to ensure data integrity and accuracy. Compare record counts and summary statistics between the source data and the data now residing in Teradata. Address any discrepancies by reloading data or adjusting transformations as necessary.
By following these steps, you can effectively move data from Adjust to Teradata without relying on third-party connectors or integrations. Each step ensures that the data is carefully handled, transformed, and verified during the migration process.