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Begin by accessing Lever Hiring's user interface to export the required data. Lever Hiring allows users to export data in CSV format. Navigate to the reports section or use the export function to download the data you need, such as candidate information, job postings, and application statuses. Save these CSV files securely on your local system.
Open the exported CSV files using a spreadsheet application like Microsoft Excel or Google Sheets. Review the data to ensure it is complete and clean. Remove any unnecessary columns or rows, and make sure the data types (e.g., dates, numbers) are consistent and correctly formatted. This step is crucial for avoiding errors during the import into Teradata.
Teradata requires data to be in a specific format for successful loading. Convert the CSV data into a format suitable for Teradata, such as ensuring date formats are compatible (e.g., YYYY-MM-DD). You may also need to create a schema file if you intend to use Teradata's bulk load utility, specifying column names, data types, and any additional details required for each field.
Ensure that you have the necessary access rights and credentials to the Teradata database where you intend to load the data. Verify that your Teradata account has sufficient permissions to create tables and insert data. Install Teradata SQL Assistant or any command-line utilities like BTEQ (Basic Teradata Query) provided by Teradata on your local environment for data loading.
Use Teradata SQL Assistant or a command-line interface to create tables that match the structure of your prepared data. Write SQL commands to define each table's schema, ensuring that the data types and lengths match those of the transformed data. Execute these SQL commands to create the tables in your Teradata database.
Use Teradata's loading utilities like BTEQ or Teradata SQL Assistant to upload the CSV files into the newly created tables. You can use the `IMPORT` command in BTEQ or the import function in SQL Assistant. Ensure that the CSV file path and the delimiter used are correctly specified. Execute the loading command while monitoring for any errors or issues that may arise.
After loading the data, perform a series of checks to ensure the data has been transferred accurately. Run SQL queries to count records and perform spot checks against your original CSV files to verify data integrity. Check for any discrepancies or errors and make necessary corrections. Document the process and confirm that all data requirements have been met.
This guide outlines a manual approach to data migration between Lever Hiring and Teradata, focusing on ensuring data integrity and compatibility throughout the 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?
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