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Begin by exporting the required data from Lever Hiring. Log into your Lever account, navigate to the data export section, and select the specific datasets you wish to export. Lever typically allows you to export data in CSV format, which is suitable for further processing.
Before you can manipulate and upload your data, ensure your local environment is set up correctly. Install any necessary software tools such as a text editor or spreadsheet application to inspect and clean your CSV files. Additionally, ensure you have command-line tools like `curl` or `wget` for data transfer and a working installation of Python or another scripting language for data processing.
Open your exported CSV files and inspect them for any inconsistencies or unnecessary columns. You may need to clean the data by removing invalid entries or normalizing values. Use a scripting language like Python with libraries such as pandas to automate cleaning and transforming processes, ensuring the data formats align with the schema in your ClickHouse database.
Ensure your ClickHouse database is ready to receive the data. Log into your ClickHouse server through an SSH terminal or a database management tool. Create the necessary tables and define the schema that matches the structure of your cleaned CSV files. Use SQL commands like `CREATE TABLE` to set up your database tables.
Use the ClickHouse native client or HTTP interface to load the data. Assuming you have CSV files, you can use the `clickhouse-client` command-line tool. For example:
```
clickhouse-client --query="INSERT INTO your_table FORMAT CSV" < /path/to/yourfile.csv
```
This command reads the CSV file and inserts data into the specified table, handling bulk data efficiently.
After loading the data, perform checks to ensure that the data has been transferred correctly. Use SQL queries to count rows, check for duplicates, and verify key metrics against the original data from Lever. This step is crucial to ensure data accuracy and consistency in the new environment.
To streamline future data transfers, create scripts or cron jobs that automate the export, transformation, and loading processes. Python scripts or shell scripts can be used to automate these tasks, reducing the need for manual intervention and minimizing the risk of human error in periodic data transfers.
By following these steps, you can effectively transfer data from Lever Hiring to ClickHouse without relying on third-party connectors or integrations, maintaining full control over the data migration process.
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:
