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Begin by exporting the data from Lever Hiring. Navigate to the Lever Hiring platform, and utilize its built-in export functionality. Typically, Lever allows you to export data in CSV or JSON formats. Choose the format that best suits your needs and download the data files to your local system.
After exporting the data, inspect the files to ensure they are complete and structured correctly. Open the CSV or JSON files using a text editor or spreadsheet software, and perform any necessary data cleaning, such as removing unnecessary columns, correcting data types, or fixing any formatting issues.
Log in to your Snowflake account and set up the necessary environment. This includes creating a new database and schema to store the Lever data. Use the Snowflake web interface or the SnowSQL command line tool to execute commands for creating your database objects.
Based on the structure of your Lever data files, define the schema for your Snowflake tables. Use SQL commands to create tables that match the structure of your data, ensuring the data types align with those in your CSV or JSON files. Pay attention to primary keys and any indexes that might be necessary for efficient querying.
Use Snowflake's file staging feature to upload your data files. First, create a stage within Snowflake using the `CREATE STAGE` command. Then, use the Snowflake web interface or the SnowSQL command line tool to upload your CSV or JSON files to this stage. This step prepares the files for loading into your tables.
With your data files staged, use the `COPY INTO` command to load the data into your Snowflake tables. Ensure you specify the correct file format (CSV or JSON) and include any necessary options such as field delimiters or headers. Monitor the load process for any errors and verify that all data is loaded correctly.
Finally, conduct a thorough review of the data within Snowflake to ensure integrity and accuracy. Perform sample queries to check that the data matches what was exported from Lever. Validate data types, relationships, and counts. Once confirmed, your data migration process is complete, and the data is now available for analysis within Snowflake.
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:
