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Learn the fundamentals of Microsoft Dynamics 365 Marketing

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Customer Engagement Dynamics 365’s Customer engagement applications are Microsoft’s first party applications built on the Microsoft Power Platform. Organizations can leverage these applications individually or together to create powerful end-to-end relationships with their customers. While each application provides a specific solution, they share common elements that are the same regardless of the application you are using. This module focuses on the common elements that are used across all the Dynamics 365 customer engagement applications. Microsoft dataverse  Benefits of Dataverse: Easy to manage : Both the metadata and data are stored in the cloud. You don't need to worry about the details of how they are stored. Easy to secure:  Data is securely stored so users can only access what they need to. Role-based security allows you to control access to tables for different users within your organization. Rich metadata : Data types and relationships are used directly within Power...
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Use DAX time intelligence functions in Power BI Desktop models

 DAX Functions which summarize over a time One group of DAX time intelligence functions is concerned with summarizations over time: DATESYTD  DAX function  -  Returns a single-column table that contains dates for the year-to-date (YTD) in the current filter context. This group also includes the  DATESMTD  and  DATESQTD  DAX functions for month-to-date (MTD) and quarter-to-date (QTD). You can pass these functions as filters into the  CALCULATE  DAX function. TOTALYTD  DAX function  -  Evaluates an expression for YTD in the current filter context. The equivalent QTD and MTD DAX functions of  TOTALQTD  and  TOTALMTD  are also included. DATESBETWEEN  DAX function  - Returns a table that contains a column of dates that begins with a given start date and continues until a given end date. DATESINPERIOD  DAX function  -  Returns a table that contains a column of dates that begins with a...
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Modify DAX filter context in Power BI Desktop models

Summary CALCULATE  DAX function to modify filter context in the formulas. The syntax for the CALCULATE function is as follows: CALCULATE (<expression>, [[<filter1>], <filter2>]…) I learned about filter context. And also learned why and how to work with the CALCULATE function to modify filter context by passing in filters. These filters can add or overwrite the filter context, and they can modify filter context when we are passing in special functions like REMOVEFILTERS or KEEPFILTERS. Additionally, I learned that the CALCULATE function can transition row context to filter context, which can be required when we are using measure expressions in calculated columns or iterator functions.
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Use DAX iterator functions in Power BI Desktop models

Data Analysis Expressions (DAX) include a set of functions known as  iterator functions . Iterator functions enumerate all rows of a given table and evaluate a given expression for each row. They provide you with flexibility and control over how your model calculations will summarize data. Some DAX Functions are Complex summarization 1. SUMX e.g. : 1.  Revenue = SUMX (Sales, Sales[Sales Amount]) 2. Revenue = SUMX (Sales, Sales[Order Quantity] * Sales[Unit Price] * ( 1 - Sales[Unit Price Discount Pct.])) 3. Discount = SUMX ( Sales, Sales[Order Quantity] *( RELATED ('Product'[List Price]) - Sales[Unit Price] ) ) 2. AVERAGEX e.g :1. Revenue Avg = AVERAGEX ( Sales, Sales[Order Quantity] * Sales[Unit Price] * ( 1 - Sales[Unit Price Discount Pct.]) ) 2. Revenue Avg Order = AVERAGEX ( VALUES ('Sales Order'[Sales Order]), [Revenue] ) 3. RANKX The  RANKX  DAX function is a special iterator function you can use to calculate ranks. Its syntax is as follows: RANKX (<...
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Add calculated tables and columns to Power BI Desktop models

We  can write a Data Analysis Expressions (DAX) formula to add a  calculated table  to our model. The formula can duplicate or transform existing model data to produce a new table. A calculated table formula must return a table object. The simplest formula can duplicate an existing model table. Calculated tables have a cost: They increase the model storage size and they can prolong the data refresh time. The reason is because calculated tables recalculate when they have formula dependencies to refreshed tables. Create calculated table and Column By clicking on modeling tab and selecting new table we can write the DAX function in order to create new table and for the calculated  column also we can write DAX function in order to get new column to the existing table. How to Create data table? Date =      CALENDARAUTO(6) The CALENDARAUTO function takes a single optional argument, which is the last month number of the year, and returns a single-column table...
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Add Measures to Power BI Desktop Model

 There are two types of measures one is  Implicit  and another is  explicit 1. Implicit Measures Implicit measures are automatic behaviors that allow visuals to summarize model column data. The following sections focus on how you can use implicit measures. In the  Fields  pane, a column that's shown with the sigma symbol ( ∑ ) indicates two facts: It's a numeric column. It will summarize column values when it is used in a visual (when added to a field well that supports summarization). Implicit measures allow the report author to start with a default summarization technique and lets them modify it to suit their visual requirements.      Numeric columns support the greatest range of aggregation functions: Sum Average Minimum Maximum Count (Distinct) Count Standard deviation Variance Median      Summarize non-numeric columns Non-numeric columns can be summarized. However, the sigma symbol does not show next to non-numeric columns...
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Implement Raw Level Security

Microsoft Power BI can help us to secure reports and workspaces by allowing us to share them to active directory users and groups. We can also share a single report but have users see different data according to their job role. We can configure raw level security by two method  1. Static Method 2. Dynamic Method 1.  Configure row-level security with the static method The static method in row-level security (RLS) uses a fixed value in the DAX filter, while the dynamic method uses a DAX function. RLS involves several configuration steps, which should be completed in the following order: Create a report in Microsoft Power BI Desktop. Import the data. Confirm the data model between both tables. Create the report visuals. Create RLS roles in Power BI Desktop by using DAX. Test the roles in Power BI Desktop. Deploy the report to Microsoft Power BI service. Add members to the role in Power BI service. Test the roles in Power BI service. 2.  Configure row-level security with the ...
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