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Course wrap up

1. Course wrap up

Congratulations on finishing the course, let's do a quick recap on the key points.

2. Data transformation process

The course teaches learners how to start with raw data, use different techniques to transform it, and finally organize it to gain insights.

3. Online orders data

Together, we started with the online furniture orders data, which contains information on orders, customers and products.

4. Conditional statements

Next, we talked about conditional statements and how to use the "if" statement to assign a value based on a specific condition.

5. Operators

Further, we learned about various operators and their meaning. We used these operators to create conditional statements.

6. Discount%

Further, we used the Expression node in KNIME to frame conditional statements over the quantity column to create a discount percentage column.

7. Expression-based transformation

Next, we learned how to perform expression-based transformations. We can transform strings using string functions and perform math transformations using formulas and operators. We can also combine both string and math transformations in mixed expressions.

8. Compute the profit

We created the Profit column using mix of math and string expressions.

9. Data integration

Later, we learned the phases of data integration and then applied them to the furniture orders data.

10. Most profitable orders

After sorting the orders data by profit value, we gained insights into the orders that were most profitable for the company.

11. Component creation

In the last chapter, we learned how to encapsulate repeated segments into a component. Additionally, we can add configuration dialogs and interactive views to the component to bundle functionality.

12. Add details & share

Once the workflows and components were ready, we added details to it and shared them with the community via the KNIME Community Hub.

13. Get started

Now that we've learned data transformation, start building workflows to transform data and uncover insights.

14. Get started

If you need any reference, feel free to visit the KNIME Community Hub and look for relevant workflows or components.

15. Start sharing!

And then, start sharing your workflows with other users to begin collaboration!

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