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To begin, log in to your Zenloop account and navigate to the data or reports section. Use the export function to download your data in a CSV or Excel format. Make sure the file includes all necessary fields that you need to import into the Oracle Database.
Open the exported file using a spreadsheet application like Microsoft Excel or Google Sheets. Clean the data by ensuring that there are no empty fields, duplicates, or inconsistencies. Save the cleaned data in CSV format, as this is widely supported for importing into databases.
Access your Oracle Database using an SQL client like SQL*Plus or SQL Developer. Use the following SQL command to create a table structure that matches the data fields in your CSV file:
```sql
CREATE TABLE zenloop_data (
field1 VARCHAR2(255),
field2 NUMBER,
field3 DATE,
...
);
```
Adjust the field names and data types to match your CSV data structure.
Use a secure method to transfer your CSV file to the server where your Oracle Database resides. You can use SCP (Secure Copy Protocol) or SFTP (SSH File Transfer Protocol) for this purpose. Ensure you have the necessary permissions and network access to upload the file to the server.
Once the CSV file is on the Oracle server, use the Oracle SQL*Loader utility to import the data into the database table. Create a control file `load_data.ctl` with the following content:
```plaintext
LOAD DATA
INFILE 'your_data.csv'
INTO TABLE zenloop_data
FIELDS TERMINATED BY ',' OPTIONALLY ENCLOSED BY '"'
(field1, field2, field3, ...)
```
Execute the SQL*Loader command:
```bash
sqlldr userid=your_username/your_password@your_database control=load_data.ctl
```
After loading the data, verify the import by running a SELECT query:
```sql
SELECT * FROM zenloop_data;
```
Check for data integrity and ensure that the records in the table match your original data set. Look out for any errors or missing data points.
Finally, optimize the table by creating indexes on frequently queried columns to improve performance:
```sql
CREATE INDEX idx_field1 ON zenloop_data(field1);
```
Ensure data security by setting appropriate user permissions and roles in Oracle to restrict access to only authorized personnel.
By following these steps, you successfully move data from Zenloop to an Oracle Database without relying on third-party connectors or integrations, ensuring a smooth and secure 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.
To sync data the Zenloop API can assist both full refresh and incremental for both answer endpoints. One can select this connector that will copy only the new or updated data, or all rows in the tables and columns you establish for replication, a sync is always run. Zenloop combines perfect customer relationships and it is an integrated experience management floor which based on the Net Promoter Score. The Zenloop API contributes programmatic entry and integration to a customer feeback platform.
Zenloop's API provides access to various types of data related to customer feedback and satisfaction. The categories of data that can be accessed through Zenloop's API are:
1. Feedback data: This includes all the feedback received from customers through various channels such as email, web forms, and social media.
2. Customer data: This includes information about customers such as their name, email address, phone number, and other contact details.
3. Survey data: This includes data related to surveys conducted by the company to gather feedback from customers.
4. Net Promoter Score (NPS) data: This includes data related to the NPS score of the company, which is a measure of customer satisfaction and loyalty.
5. Sentiment analysis data: This includes data related to the sentiment of customer feedback, which can help companies understand the overall sentiment of their customers towards their products or services.
6. Analytics data: This includes data related to customer behavior, such as the number of visits to the company's website, the time spent on the website, and the pages visited.
Overall, Zenloop's API provides access to a wide range of data that can help companies gain insights into customer feedback and satisfaction, and make data-driven decisions to 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?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:





