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Begin by exporting your data from Delighted. Log into your Delighted account, navigate to the data or survey responses you wish to export. Use the built-in export feature to download the data in a CSV format, which is the most common and compatible format for moving data.
Open the exported CSV file in a spreadsheet application like Microsoft Excel or Google Sheets. Inspect the data for any inconsistencies or errors that need correction. Ensure the data is clean and formatted correctly, with consistent column headers and no missing values that could cause issues during import.
If you haven’t already installed DuckDB, download and install it from the official DuckDB website. DuckDB is an in-process SQL OLAP database management system, and you can install it on your local machine. Follow the installation instructions specific to your operating system.
Open your terminal or command line interface, and create a new DuckDB database. You can do this by running the command `duckdb your_database_name.db` where `your_database_name.db` is your desired database file name. This command initializes a new database file which will store your data.
With the DuckDB database initialized, create a table that matches the structure of your CSV file. You can do this by using SQL commands in the DuckDB shell. For example, if your CSV has columns `id`, `name`, and `score`, you would run `CREATE TABLE my_table (id INTEGER, name VARCHAR, score DOUBLE);` to define a table with the necessary columns and data types.
Use DuckDB’s built-in CSV reading capabilities to import your data. In the DuckDB shell, execute the command `COPY my_table FROM 'path/to/your/exported_data.csv' (HEADER, DELIMITER ',');`. Replace `'path/to/your/exported_data.csv'` with the actual path to your CSV file. Ensure your file path and column definitions match to avoid errors during import.
Once the import process is complete, verify that the data in DuckDB matches your expectations. Run SQL queries to check the row count and sample records, such as `SELECT * FROM my_table LIMIT 10;`, to ensure that the data has been correctly imported and that there are no discrepancies between the original CSV file and the database table. Make any necessary adjustments if issues are found.
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.
Delighted assists businesses connect with their customers learning, improving, and delighting.It is well known for delivering some of the most innovative functionality for customer experience management. Delighted is completely the self-serve experience management platform of choice for the worldwide top brands. It helps to collect and analyze survey feedback through Delighted. Get set up in minutes, no technical knowledge needed. Delight helps to build long-lasting relationships and deliver great service experience.
Delighted's API provides access to various types of data related to customer feedback and satisfaction. The categories of data that can be accessed through Delighted's API are:
1. Survey Responses: This includes all the responses received from customers through Delighted's surveys. It includes both quantitative and qualitative data.
2. Metrics: This includes various metrics related to customer satisfaction, such as Net Promoter Score (NPS), Customer Satisfaction Score (CSAT), and Customer Effort Score (CES).
3. Trends: This includes trends related to customer feedback and satisfaction over time. It helps businesses to identify patterns and make data-driven decisions.
4. Segmentation: This includes data related to customer segments, such as demographics, location, and behavior. It helps businesses to understand their customers better and tailor their offerings accordingly.
5. Integrations: Delighted's API also provides access to data from various integrations, such as Salesforce, HubSpot, and Slack. It helps businesses to streamline their workflows and improve their customer experience. Overall, Delighted's API provides a comprehensive set of data that businesses can use to measure and improve their customer satisfaction.
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:
