We finished the major part of the application by completing data modeling. Now it is time to start visualization.

We will start with creating Master Items and then we will be designing the charts and graphs. To begin, we will define Dimensions in the list. For this, we will click on the Master Items button available on the left hand side and click on Dimensions, as shown in the following screenshot:

Once you click on the Create New button, a new window will open which will allow you to define a field as dimension from all the available fields in data model, as shown in the following screenshot:

As shown in the preceding screenshot, you get two options: one is to define a single field as dimension or create a drill down dimension. Once you select any one option, you can select the field from the list and give a name to that field. You can also define the label expression, if you want to change the label dynamically. You can assign color to your dimension if you want.

Once all the settings are done, you can simply click on Add Dimension to create a new dimension in the master list. In previous example, we have chosen EmployeeName as the dimension. Similarly, you can add as many dimensions as you need.

Now you can select the Measures option and click on Create New to create a measure. Once you click on it, the following window will open:

As you can see in the preceding window, you can define the desired calculation in the Expression box. Give a proper name to your expression and Description if required. You can give a small description about the expression, like the working of the expression or the output generated by the expression. The option to give a specific color to the measure is also available. You can also give a tag to your expression, so that it can be easily searched.

The previous screenshot shows the sample expression to calculate the Month Till Date sales amount. Similarly, you can create as many measures as you need.

Following is the list of expressions which you can create:

Given here are some KPI calculations out of the entire list; for exhaustive list, you can refer to the code bundle.

Now that we have created all the KPI calculations in the master list, we are ready to start with the designing of the dashboard.

It is good practice to include an introduction page in your application. The introduction page gives information about the application and the users know exactly what to expect from the it. A good introduction page should give an overview of the application, including what data it contains and what kind of analysis is available in it. The sample introduction page created for Adventure Work Sales application is shown in the following screenshot:

Let us see OmniChannel Sales Dashboard:

You can see in the preceding screenshot that it gives the following insights into the data.

• YTD (year till date) growth percentage: This KPI helps the users to compare the business of this year versus last year
• QTD (quarter till date) growth percentage:  This KPI helps in finding the QTD growth as compared to the same quarter last year
• MTD (month till date) growth percentage: This KPI helps compare the current month business with that of last year same month
• Trend: This trend gives a clear bifurcation about the sales between two channels and shows which channel is performing well over a period of time
  
• Bar chart: It shows the channel wise sales by product category, to understand which channel is performing well in what product category

Let us have a look at the Reseller Dashboard:

This dashboard shows the sales analysis for the reseller channel. It gives the following insight into data:

• MTD sales quota achievement percent: This KPI shows how much quota has been achieved for the month
• QTD sales quota achievement percent: It tells how much quota has been achieved for the quarter
• YTD sales quota achievement percent: It shows how much quota has been achieved for the year

All the preceding KPIs also had color coding, which gives a clear indication if the percentage achievement is within the expected range or not.

Some of the other KPIs as as follows:-

• MTD sales amount: This KPI shows the current month and the previous month sales amount
• QTD sales amount: This KPI shows the current quarter and the previous quarter sales amount
• YTD sales amount: This KPI shows the current year and the previous year sales amount
• Trend: This trend is for rolling 12 months and it shows the sales versus quota

Now let us see the Sales Analysis sheet:

This visualization shows the following analysis:

• Sales trend: It shows the total sales over a period. This helps to find the sales trend for any dimension value which can be selected from the filters given at the bottom of the visualization. This chart can be drilled down to week and further to day level.

• Sales by product dimension: It gives a drill down from product category to product sub category to individual product. This chart helps in finding which product category is doing good business.
• Sales by country: This chart shows the contribution of each country toward total sales. It also gives insights about which country has maximum sales by looking at donut chart
  
• Top 10 selling products: It shows the best performing products.
• Bottom 10 selling products: It shows the worst performing products. Looking at this chart, the users can decide whether to continue this product in future or not.

Let us have a look at the Employee Performance sheet:

This visualization helps the users to know the following things:

• Quota achievement percent: This chart shows the quota achieved by all the employees and finds which employee is working hard. It also gives insight that there is something wrong with one of the employees, namely Syed Abbas. It seems his quota has not been assigned properly and that needs attention.
• Trend: This chart shows the year on year monthly sales. So if a user wants to know about the performance over time of any one or a group of employees, this chart can give a good picture.
• Quota trend: This chart shows quota achievement over time.
• Treemap: This chart shows which employee has sold which product sub category most.

Now let us see Product Analysis sheet:

This visualization on the sheets help us with following analysis:

• Bar chart: This chart shows the number of products that are not sold in one of the regions. By default, the selection is for United Kingdom, but it can be changed to other regions using filters at the bottom of the sheet. This gives an insight about which product should be focused on in which region.
• Pivot chart: It gives a clear idea about sales of each product sub category in each region.

Let us see what will be included in Reporting sheet:

Reporting shows the transaction data at various dimension levels. Like in the preceding screenshot, we have region wise sales, month on month sales, and employee wise sales.