Power BI - Hypothetical Viewpoints

1. Power Bi - theoretical aspects A Power BI report is nothing more than a multi-perspective view of a data set, complete with visualisations that illustrate various discoveries and insights from that data set. A report might be a single visualisation or a collection of visualisations across multiple pages.

2. 1 • Dashboards can have visualisations pinned to them, and selecting the pinned visualisation will open the report from where it was pinned. One thing to keep in mind is that reports are based on a particular set of data.

3. 2 • In a report, the visuals reflect a nugget of data. In your quest to uncover insights and find solutions, you can add and remove data, alter visualisation types, and apply filters to these visualisations. A report is extremely interactive, very customisable, and the visuals update as the underlying data changes, much like a dashboard.

4. 3 • Tiles are the visuals that appear on the dashboard. These tiles come from reports and are pinned to the dashboard. The dashboard's visuals are derived from reports, and each report is based on a single data source. In fact, one way to think of a dashboard is as an entrance point into the reports and data sets behind it. When you select a visualisation, you'll be taken to the report (and data set) for that visualisation.

5. 4 • Dashboards ( are a great way to keep track of your business, find solutions, and see your most essential KPIs all in one place. A google analytic power bi dashboard visualisations can derive from one or more underlying data sets, as well as one or more underlying reports. A dashboard brings together data from both on-premises and the cloud, offering a consolidated view regardless of where the data is stored.

6. 5 • Using Power BI to Create a Dashboard • The easiest way to understand how to use a Power BI dashboard is to consider a data set with various data kinds, each of which has the potential to disclose useful business insights. Consider the instance of a retail superstore where data on regional sales, individual shop transactions, product categories, consumer segments, and sales is analysed.

7. 6 • What insights can we glean from the superstore data set? • Overall superstore sales and performance: The first natural step is to acquire a sense of the superstore's performance throughout time. We'll need sales data from various regions on a quarterly basis for this. In addition, we must determine which region is more profitable or loss-making than others.

8. 7 • Revenue generation by category: We can acquire statistics on specific product categories and how they compare (in terms of sales and profits) within specified geographies and client segments. If kitchen appliances make more money than cleaning equipment, this is important information that can impact future plans.

9. 8 • Different customer segments' performance: It's also critical for the company to understand which client segments are generating sales and profitability in different locations.