How to load data from Smartsheets to Teradata
Learn how to use Airbyte to synchronize your Smartsheets 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: Export Data from Smartsheet
Log in to your Smartsheet account and open the sheet you wish to export. Click on "File" in the menu, then select "Export" and choose "Export to Excel." This will download the sheet as an Excel file (.xlsx) to your local machine.
Step 2: Prepare Data for Teradata Import
Open the downloaded Excel file and review the data to ensure it is clean and properly formatted. Remove any unnecessary columns or rows, and ensure that the column names are suitable for a database (e.g., no spaces or special characters). Save the cleaned data in a CSV format, which is compatible with Teradata.
Step 3: Access Teradata SQL Assistant
Launch Teradata SQL Assistant (or another Teradata client like BTEQ) on your computer. If you haven't installed it, you can download it from the Teradata website. Connect to your Teradata database using your credentials and database connection details.
Step 4: Create a Teradata Table
In Teradata SQL Assistant, write a SQL statement to create a table that matches the structure of your CSV data. Define the appropriate data types for each column to ensure that the data will load correctly. Execute the SQL statement to create the table in your Teradata database.
Step 5: Load Data into Teradata
Use the Teradata FastLoad utility to load the CSV file into the newly created table. Open the command line interface on your computer, navigate to the directory containing your CSV file, and enter a FastLoad script similar to the following:
```
.LOGON your_teradata_server/username,password;
DATABASE your_database;
BEGIN LOADING your_table;
DEFINE
column1 (VARCHAR(100)),
column2 (INTEGER),
column3 (DATE)
FILE=your_file.csv;
INSERT INTO your_table VALUES
(:column1, :column2, :column3);
END LOADING;
.LOGOFF;
```
Replace placeholders with actual values corresponding to your data and environment.
Step 6: Verify Data Integrity
Once the data is loaded, write and execute SQL queries in Teradata SQL Assistant to verify that the data has been imported correctly. Check for any discrepancies or errors by comparing sample data from the Teradata table with the original data in the CSV file.
Step 7: Document the Process
Document the entire process, including any SQL scripts used and any issues encountered during the data transfer. This documentation will be helpful for future data migrations and for training others. Ensure that you save the scripts and documentation in a secure location for future reference.