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Start by logging into your Workable account and navigating to the section containing the data you wish to export (e.g., candidate profiles, job listings, etc.). Use Workable's built-in export feature to download the data as a CSV or Excel file. Ensure all necessary fields are included in your export for a complete data set.
Open the exported file using spreadsheet software like Microsoft Excel or Google Sheets. Review the data to ensure it's complete and organized. Remove any unnecessary columns and clean up any data inconsistencies or errors to make the transformation process smoother.
Depending on the structure required by Starburst Galaxy, you may need to transform the data format. This might involve renaming columns, changing data types, or splitting/merging fields. Use spreadsheet functions to perform these transformations. Save the transformed data in a suitable format, such as CSV, which is commonly supported for data import operations.
Log into your Starburst Galaxy account. Ensure you have the necessary permissions to create schemas and tables. Create a new schema or select an existing one where the data will be stored. This step involves configuring the environment to accommodate the incoming data structure.
Use the Starburst Galaxy interface or SQL commands to define a new table that matches the structure of your transformed data. Specify column names, data types, and any constraints to ensure data integrity. This step is crucial to ensure the data imports correctly and aligns with Starburst Galaxy's schema requirements.
Utilize Starburst Galaxy's import functionalities to load your data file into the newly created table. You may use SQL commands for bulk loading if available, ensuring that the file path and access permissions are correctly set. Monitor the import process to handle any errors or issues that might arise.
After the import is complete, run queries on the Starburst Galaxy platform to verify that the data has been imported correctly. Check for data integrity by cross-referencing a sample of records with the original data from Workable. Ensure all records are accounted for and the data types and values are accurate.
By following these steps, you can successfully move data from Workable 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.
Workable is a cloud-based recruitment software that helps businesses streamline their hiring process. It offers a range of tools to help companies manage job postings, applicant tracking, candidate communication, and interview scheduling. Workable also provides features such as resume parsing, candidate scoring, and background checks to help businesses make informed hiring decisions. The platform integrates with popular job boards and social media sites, making it easy for companies to reach a wider pool of candidates. Workable is designed to be user-friendly and customizable, allowing businesses to tailor the software to their specific needs.
Workable's API provides access to a wide range of data related to recruitment and hiring processes. The following are the categories of data that can be accessed through Workable's API:
1. Candidates: Information about candidates who have applied for a job, including their name, contact details, resume, cover letter, and application status.
2. Jobs: Details about the job openings, including the job title, description, location, salary, and hiring manager.
3. Hiring pipeline: Information about the hiring process, including the stages of the pipeline, the number of candidates in each stage, and the time spent in each stage.
4. Interviews: Details about the interviews conducted with candidates, including the date, time, location, interviewer, and feedback.
5. Reports: Analytics and insights related to recruitment and hiring processes, including the number of applications, the time to hire, and the cost per hire.
6. Integrations: Information about the third-party tools and services integrated with Workable, including the ATS, HRIS, and job boards.
Overall, Workable's API provides a comprehensive set of data that can help organizations streamline their recruitment and hiring processes and make data-driven decisions.
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?
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