Date & time operations

<p><strong>Date&amp;Time Operations: Customer Purchase Analysis</strong></p><p>Working with date &amp; time values can be tricky. KNIME offers a variety of nodes for date-&amp; time-related operations. To make use of these nodes, it is crucial to transform the relevant columns into <em>Date&amp;Time</em> cells.</p><p>Based on a customer purchase analysis use case, this example workflow demonstrates how to how to convert a date &amp; time value from <em>String </em>into <em>Date&amp;Time</em> and illustrates how different date &amp; time operations can be performed. After processing the transaction data, the workflow identifies each customer's potential churn risk based on a their inactivity.</p><p>The sample data has 5 columns:</p><ul><li><p>Customer ID: Each customer's identification number</p></li><li><p>Purchase Date: The date and timestamp when each purchase was made</p></li><li><p>Purchase Amount: The purchase amount</p></li><li><p>Store Location: The location of the store where the purchase was made</p></li><li><p>Product Category: The product category</p></li></ul>