<h3 id="heading-scenario">Scenario:</h3>
Given meta data:
<pre><code class="lang-plaintext">column_name, data_example, valid_profile

IoT GUID, 48196321-3809-EC11-883D-0022489A2..., 100%

IoT DateTime, 21/05/2022 18:59:25, 100%

IoT ID, 10000010000, 100%
</code></pre>
The IoT GUID and IoT ID columns are unique to each row in query. You need to analyze IoT events by the hour and day of the year. The solution must improve dataset performance.
Solution: You remove the loT GUID column and retain the loT ID column. Does this meet the goal?
Answer: In summary, yes, this solution meets the goal of improving dataset performance by reducing unnecessary data.
Removing the IoT GUID column and retaining the IoT ID column can indeed help improve dataset performance, especially if the GUID is not necessary for your analysis. Since both columns are unique identifiers, keeping just one (IoT ID) reduces the dataset size and complexity without losing the ability to uniquely identify each row.
However, it's important to ensure that the IoT ID column alone is sufficient for all your analytical needs. If the GUID is not used in any joins, relationships, or specific analyses, then removing it should be fine.

### **Scenario:**

Given meta data:

```plaintext
column_name, data_example, valid_profile

IoT GUID, 48196321-3809-EC11-883D-0022489A2..., 100%

IoT DateTime, 21/05/2022 18:59:25, 100%

IoT ID, 10000010000, 100%
```

The IoT GUID and IoT ID columns are unique to each row in query. You need to analyze IoT events by the hour and day of the year. The solution must improve dataset performance.

Solution: You remove the loT GUID column and retain the loT ID column. Does this meet the goal?

Answer: In summary, yes, this solution meets the goal of improving dataset performance by reducing unnecessary data.

Removing the IoT GUID column and retaining the IoT ID column can indeed help improve dataset performance, especially if the GUID is not necessary for your analysis. Since both columns are unique identifiers, keeping just one (IoT ID) reduces the dataset size and complexity without losing the ability to uniquely identify each row.

However, it's important to ensure that the IoT ID column alone is sufficient for all your analytical needs. If the GUID is not used in any joins, relationships, or specific analyses, then removing it should be fine.

Power BI Practice: Optimize Power BI Datasets, Remove Irrelevant Fields

Scenario: