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Start by exporting the data you need from Confluence. Navigate to the space or page you want to export. Use the built-in export functionality to export the data in a compatible format such as XML or PDF. If you're exporting an entire space, use the "Space Tools" menu and select "Export Space" to choose your desired format.
After exporting the data from Confluence, you will need to prepare it for import into Starburst Galaxy. Convert the exported file into a structured format like CSV or JSON, which can be easily handled by Starburst Galaxy. Use a script or data transformation tool to convert the XML or PDF content into CSV/JSON, ensuring the data fields are correctly mapped.
Log into your Starburst Galaxy account and set up a new workspace if necessary. Starburst Galaxy uses Trino (formerly Presto) for querying, so ensure you have the correct permissions to create tables and load data. Familiarize yourself with the interface and ensure you have access to the database where you intend to import the data.
Create the target schema in Starburst Galaxy where the data will reside. Use the SQL editor to define the structure of your target tables. Ensure that the data types and structure match the format of your prepared data. For example, use `CREATE TABLE` statements to define columns that correspond to those in your CSV or JSON file.
Use the Starburst Galaxy interface to upload the CSV or JSON file. Depending on the size of your data, you may need to split large files into smaller chunks for easier handling. Use the data upload functionality to place the files into a location accessible by Starburst Galaxy, such as an Amazon S3 bucket or Google Cloud Storage.
Execute SQL commands within Starburst Galaxy to load the data into your created tables. Use the `COPY` command or equivalent SQL insert operations to import the data. Ensure that data mapping is correct and that all rows are successfully inserted. You may need to reference the external storage location where your files are stored.
Once the data is loaded, perform checks to verify and validate the data integrity. Run queries to check for data completeness and accuracy. Compare a sample of records in Starburst Galaxy against the original data from Confluence to ensure that the data has been accurately transferred. Address any discrepancies or errors in the data import process.
By following these steps, you can successfully move data from Confluence to Starburst Galaxy without relying on third-party connectors or integrations.
FAQs
What is ETL?
ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.
Confluence defines your reason for being so you can form actionable business strategies and it can share performance results and customer insights with stakeholders. Confluence presents your business vision and help your team understand your strategic plan. It is your remote-friendly team workspace where knowledge and collaboration meet. Confluence is purpose-built for teams which requires a secure and reliable way to collaborate on mission-critical projects. Confluence sites are entirely protected by privacy controls and data encryption, and meet industry-verified compliance standards.
Confluence's API provides access to a wide range of data, including:
1. Pages: Confluence pages are the primary unit of content in the platform, and the API allows developers to create, read, update, and delete pages.
2. Spaces: Spaces are containers for pages and other content, and the API provides access to space metadata, permissions, and other settings.
3. Users and groups: The API allows developers to manage users and groups, including creating, updating, and deleting them.
4. Comments: Confluence pages can have comments, and the API provides access to comment metadata and content.
5. Attachments: Pages can have attachments, such as images or documents, and the API allows developers to manage attachments.
6. Labels: Labels are used to categorize content in Confluence, and the API provides access to label metadata and allows developers to add or remove labels from pages.
7. Search: The API provides a search endpoint that allows developers to search for pages, spaces, and other content in Confluence.
Overall, Confluence's API provides access to a wide range of data that developers can use to build custom integrations and applications that extend the functionality of the platform.
What is ELT?
ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.
Difference between ETL and ELT?
ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:
