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Start by obtaining access to the Lever Hiring API. You need to generate an API key by logging into your Lever account, navigating to the settings, and creating a new API key with the necessary permissions to access the data you need, such as candidates, opportunities, and jobs.
Use the API key to make HTTP GET requests to the Lever API endpoints. For example, to retrieve candidate data, use the `/candidates` endpoint. Utilize tools like cURL, Postman, or a scripting language like Python with `requests` library to fetch data. Ensure you handle pagination as the data might be paged.
Once the data is retrieved in JSON format, parse it to extract relevant information. This can be done using JSON parsing libraries available in most programming languages. For example, in Python, you can use the `json` library to load and process this data.
Elasticsearch requires data to be in a specific format. Transform the parsed data into a format suitable for Elasticsearch indexing. This may involve restructuring the JSON objects, renaming fields, or flattening nested structures to match the Elasticsearch schema.
Before importing data, set up an index in Elasticsearch where the data will be stored. Define the mappings for the data types you plan to store, ensuring that the field types match those of the transformed data. Use the Elasticsearch API or Kibana to create and configure the index.
Use the Elasticsearch Bulk API to import the transformed data. Prepare bulk JSON actions by combining multiple operations into a single request. This involves creating a bulk payload where each line contains a meta-data action line followed by the data line. Execute this using HTTP POST requests to the `_bulk` endpoint.
After importing the data, verify that it has been correctly indexed in Elasticsearch. Use the Elasticsearch API to perform search queries, ensuring that the data is accessible and correctly structured. Check for any errors during the bulk import process and resolve them by adjusting the data format or index mappings.
By following these steps, you can effectively move data from Lever Hiring to Elasticsearch 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?
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