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Begin by exploring the data export capabilities provided by Qualaroo. Qualaroo typically allows you to export survey data in formats such as CSV or Excel. Access your Qualaroo account and navigate to the data export section. Ensure you have the necessary permissions to export the data you need.
Once you are in the export section of Qualaroo, select the surveys and data points you wish to export. Choose a suitable format (CSV is recommended for simplicity and compatibility). Initiate the export process and download the file to your local system.
Access your Oracle Database using a tool like SQL*Plus or SQL Developer. Ensure you have the correct permissions to create tables and insert data. Create a table structure in Oracle that matches the schema of the data exported from Qualaroo. Use the SQL `CREATE TABLE` command to define the table columns and data types.
Open the exported CSV file using a text editor or spreadsheet application. Review the data for consistency and correctness. Remove any unnecessary columns or rows. Ensure that the data types align with those defined in your Oracle Database table. Save the cleaned data in CSV format.
Utilize SQL*Loader, a utility provided by Oracle, to load the data from the CSV file into your Oracle Database. Create a control file that describes how to load the data, specifying the data file location, table name, and data field mappings. Execute the SQL*Loader command from the command line to initiate the data load process.
After the data load is complete, verify that the data in Oracle matches the source data from Qualaroo. Use SQL queries to check for data consistency, completeness, and accuracy. Validate that all records have been transferred correctly and that no data is missing or corrupted.
To streamline future data transfers, consider writing scripts that automate the export from Qualaroo, data cleaning, and loading processes. Use shell scripts or batch files to automate the execution of SQL*Loader and other necessary steps. Schedule these scripts using cron jobs (on Unix-based systems) or Task Scheduler (on Windows) to run at regular intervals, ensuring data is regularly updated in the Oracle Database.
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.
Qualaroo is a SaaS product that helps companies gather customer insights to grow their business. Koala's mission is to help companies understand the reasons behind their customers' and prospects' decisions. Understanding why leads to better business results like increasing sales, improving web conversion rates and experience, increasing product engagement, reducing churn, and more. Qualaroo makes it possible to intelligently target interactions by time on page, pages visited, number of site visits, source citations, or any internal data.
Qualaroo's API provides access to various types of data related to user feedback and behavior. The categories of data that can be accessed through Qualaroo's API are:
1. Survey data: This includes data related to the surveys created using Qualaroo, such as survey responses, completion rates, and survey questions.
2. User behavior data: This includes data related to user behavior on a website or application, such as page views, clicks, and time spent on a page.
3. User feedback data: This includes data related to user feedback, such as comments, ratings, and suggestions.
4. Demographic data: This includes data related to user demographics, such as age, gender, location, and occupation.
5. Conversion data: This includes data related to user conversions, such as conversion rates, conversion funnels, and revenue generated.
6. A/B testing data: This includes data related to A/B testing, such as test results, variations, and statistical significance.
Overall, Qualaroo's API provides access to a wide range of data that can help businesses better understand their users and improve their products and services.
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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