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Begin by exporting the necessary data from Lever Hiring. Navigate to the Lever Hiring platform's export feature, typically found in the analytics or data section. Choose the data you need, such as candidate profiles or job listings, and export it in a CSV or JSON format. Ensure that you have the required permissions and access rights to perform this export.
Once the data is exported, review and clean it to ensure accuracy and consistency. Check for any missing or null values, and determine if any additional data fields are needed for your Typesense index. Use tools like Excel or a text editor to modify and format the data as needed.
Typesense requires data to be in JSON format for indexing. If your exported data is in CSV format, convert it to JSON. Write a simple script in a programming language such as Python to read the CSV file and transform each record into a JSON object. Ensure that the JSON structure aligns with the schema you plan to use in Typesense.
Before importing data into Typesense, define the schema for your Typesense collection. This includes specifying fields, data types, and any indexing options. Decide on the fields that will be searchable and those that will be used for faceting. This schema will guide how your data is stored and searched in Typesense.
Install and set up a Typesense server if you haven't already. You can run Typesense locally or on a cloud server. Follow the official Typesense installation guide to get your server up and running. Ensure that your server is configured to accept API requests and that you have the necessary API keys for authentication.
Use the Typesense API to import your transformed JSON data into the defined collection. Write a script in Python or another programming language to send HTTP POST requests to the Typesense server, using the `/collections/{collection_name}/documents/import` endpoint. Handle any errors or conflicts that arise during the import process and verify that all data is correctly indexed.
After importing the data, verify that it has been successfully indexed in Typesense. Use the Typesense dashboard or API to perform test searches and ensure that the data is accessible and searchable as expected. Check for any discrepancies or missing data and re-import if necessary. Conduct searches to confirm that the schema is functioning properly and adjust configurations if needed.
By following these steps, you can effectively move data from Lever Hiring to Typesense 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.
The Lever Hire and Lever Nurture features allow leaders to scale and grow their people pipeline and build authentic and long-lasting relationships. The lever is a leading Talent Acquisition Suite that makes it easy for talent teams to reach their hiring goals and to connect companies with top talent. Lever hire is a complete talent acquisition suite that provides all the tools needed for businesses to discover and hire the best talents.
Lever Hiring's API provides access to a wide range of data related to the hiring process. The following are the categories of data that can be accessed through the API:
1. Candidates: Information about candidates who have applied for a job, including their name, contact details, resume, and application status.
2. Jobs: Details about the job openings, including the job title, location, description, and requirements.
3. Interviews: Information about the interviews scheduled for the candidates, including the date, time, location, and interviewer details.
4. Offers: Details about the job offers made to the candidates, including the salary, benefits, and start date.
5. Users: Information about the users who have access to the Lever Hiring platform, including their name, email address, and role.
6. Teams: Details about the teams within the organization, including the team name, members, and roles.
7. Stages: Information about the different stages of the hiring process, including the names and descriptions of each stage.
8. Sources: Details about the sources from which the candidates have applied, including job boards, social media, and referrals.
Overall, Lever Hiring's API provides a comprehensive set of data that can be used to streamline the hiring process and improve the overall efficiency of the recruitment process.
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:
