Model Data In Power BI

 Modeling Data In Power BI:-

Modeling data is nothing but connected data within each other so after that, we can use that data for our needs.

How to manage your data relationships:-

Relationship means we can connect one or more tables together because they had related data in respected tables. So we can able to perform queries on the linked table according to our needs. The Model view in Power BI Desktop allows you to visually set the relationship between tables or elements. In the Model view, we can see that table with the respected relationships. Adding and removing relationships is straightforward. To remove a relationship, right-click the relationship and select Delete. To create a relationship, drag and drop the fields that you want to link between tables.

A data relationship’s cardinality describes the l relationship between rows of one table and the rows of the other. 

one-to-one: one-to-one cardinality indicates that each row of a table maps to a single row of another table

one-to-many or many-to-one: one-to-many relationships are very frequent in traditional star-schemas. One-to-many relationships occur when a single row of a table maps to more than one row in another table. This is the case of the example relationship studied above

many-to-many: many-to-many relationships are very tricky to deal with. They occur when multiple rows in one table link to multiple rows in another.

Create calculated columns:-

data that you're analyzing doesn't contain a field that you need. so we need an answer for that is the calculated column. So for the created a calculated column, we can transfer two or more elements of existing data in a new column. The main reason for created a calculated column is that when tables don't have unique fields between them so creating a relationship we need unique fields in tables. for creating a calculated column we need to go Table Tool in Power BI Desktop, select a new column that we open a formula bar so in the formula bar you will be able to write an expression. once you enter a formula by giving the column name Power BI Desktop creates a new column in a particular table.

Optimize data models:-

Imported data often contains fields that you don't need for your reporting and visualization tasks. Data might contain unnecessary information or it might be available in another column. Power BI Desktop has tools to optimize your data and make it more usable for building reports and visuals.

Hide table-

For the hiding field in the Fields pane of Power BI Desktop, right-click the column & select hide. Your hidden fields are not deleted it is just not able to see on Fields Pane.

Sort visualization data by another field-The Sort by Column tool, available on the Table tools tab, is useful to help ensure that your data is displayed in the order that you intended.

Create measures:-

In Power BI, measures are defined calculations on your data that are performed at the time of your query. Measures are calculated as you interact with your reports and aren't stored in your database.

To create a measure, in Report view, select New Measure from the Modeling tab. From the Formula bar, you can enter the DAX expression that defines your measure. As you enter your calculation, Power BI suggests relevant DAX functions and data fields. You'll also receive a tooltip that explains some of the syntax and function parameters.

Explore time-based data:-

Analyzing time-based data with Power BI is a simple process. The modeling tools in Power BI Desktop automatically generate fields that let you drill down through time periods. When you create a table visualization in your report by using a date field, Power BI Desktop automatically includes breakdowns by time period. For example, the single date field in the Date table was automatically separated into Year, Quarter, Month, and Day by Power BI.