Sales Dashboard Example with Microsoft SQL Server Database Using Bold BI

Sales Dashboard Example with Microsoft SQL Server Database Using Bold BI

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    Sales Dashboard Example With Microsoft SQL Server Database Using Bold BI

    Microsoft SQL Server is a relational database management system widely used by top industries. It has a large user base across different industries such as IT, healthcare, retail, insurance, finance, education, management, sales, and marketing for their storage and data processing operations. In this article, we learn how to prepare a dashboard to analyze product sales and prioritize products in production with the Contoso BI demo database using Bold BI Dashboards.

    If you are new to the Bold BI Dashboards, sign up for a free 30-day trial on our website. At the end of the registration process, you will reach the following page view.

    Homepage view in Bold BI Dashboards
    Homepage view in Bold BI Dashboards

    Defining metrics to analyze product sales

    Let’s consider the following metrics to analyze product sales:

    • The total sales and total return amounts.
    • Difference in return amounts among product categories.
    • Return quantities by product category during each sales year.
    • Top 10 products with lowest production cost.
    • Top 10 products with good returns.
    • Distribution of return amount by year and month.

    Installing Microsoft SQL Server and configuring Contoso BI demo database

    Install the SQL Server in your local machine or in a remote accessible server by referring to the Microsoft documentation.

    Furthermore, Download, extract, and restore the Contoso BI demo database by referring to the Install Instructions.

    Creating a dashboard and data source

    Firstly, select the New Dashboard tile in the homepage and click Start from Scratch of the Bold BI Dashboard Platform. The Dashboard Designer page will open with a new blank dashboard created like in the following.

    A blank dashboard design view
    A blank dashboard design view

    Connecting to Microsoft SQL Server database

    1. Select the data source icon on the right. The data source panel will expand as shown in the following.
      An empty data sources panel
      An empty data sources panel
    2. Similarly, select CREATE NEW in the previous panel.
    3. Furthermore, choose the category SQL in the Categories drop-down list. As a result, this list shows the data connectors available under this category like in the following.
      Choosing MS SQL Server
      Choosing MS SQL Server
    4. Finally, choose the Microsoft SQL connector. The Microsoft SQL data connection window will display in the DATA SOURCES panel like in the following.
      SQL Server Data Source Configuration Window
      SQL Server Data Source Configuration Window

    Creating a data source

    1. Firstly, name the data source as ContosoBIDataSource at Name field in the NEW DATA SOURCE window.
    2. Furthermore, fill the SQL Server name where your database resides in Server name field. For example, remotemachine(or)ipaddress,1433 where, 1433 is the port number. In addition, the SQL Server running at remote machine should be reachable for Bold BI Dashboard’s site. 
    3. Likewise, fill the login details at User name and Password fields.
    4. Finally, choose the database in Database field for Contoso BI demo data. For example, the database name is ContosoRetailDW.

    Editing the data source

    1. Firstly, navigate to the dashboard design page and expand the DATA SOURCES panel on the right.
    2. Furthermore, click the Edit icon near the ContosoBIDataSource data source. As a result, the data source window will open like in the following.
      Editing SQL Server Data Source
      Editing SQL Server Data Source
    3. Likewise, drag and drop the FactSales table and related dimension tables such as DimProductDimProductSubcategory, and DimProductCategory by using INNER JOIN with their respective keys.
      Join Editor
      Join Editor
      Most importantly, the actual relationship among these tables is like in the following image.
      Relationship Diagram
      Relationship Diagram
    4. As a result, the data source editing view is like in the following image.
      Editing view of a data source
      Editing view of a data source
    5. Finally, save the data source.

    Configuring widgets in dashboard

    Select the widget to configure and click the Widget Settings icon at the top-right corner of the focused border like in the following.

    Focused view of widget in dashboard
    Focused view of widget in dashboard

    As a result, the panel on the right side expands toward the left. Choose the ASSIGN DATA tab and start configuring the mentioned fields in corresponding sections as described in the following table.

    Widget TitleWidget TypeData Configuration
    Sales yearCombo Box
    • Column(s): DateKey
      • Format: Year
    Return amount comparison among product subcategoriesDoughnut Chart
    • Value(s): ReturnAmount
      • Aggregation: Sum
      • Format:
        • Type: Currency
        • Representation: Millions
    • Column: ProductSubcategoryName
    Total sales amountCard
    • Actual Value: SalesAmount
      • Aggregation: Sum
      • Format:
        • Type: Currency
        • Representation: Millions
    Total return amountCard
    • Actual Value: ReturnAmount
      • Aggregation: Sum
      • Format:
        • Type: Currency
        • Representation: Millions
    Return quantity comparison by product category level in each sales yearColumn Chart
    • Value(s): ReturnQuantity
      • Aggregation: Sum
      • Format:
        • Type: Number
        • Representation: Thousands
    • Column(s): ProductCategoryName and ProductSubcategoryName
    • Row: DateKey
      • Format: Year
    Top 10 products with lowest production costBar Chart
    • Value(s): TotalCost
      • Aggregation: Sum
      • Format:
        • Type: Currency
        • Representation: Thousands
    • Column(s): ProductName
      • Filter: Rank Bottom 10 based on Sum(TotalCost)
    Top 10 products based on return amountBar Chart
    • Value(s): ReturnAmount
      • Aggregation: Sum
      • Format:
        • Type: Currency
        • Representation: Thousands
    • Column(s): ProductName
      • Filter: Rank Top 10 based on Sum(ReturnAmount)
    Return amount comparison for each month of sales yearHeatmap
    • Value: ReturnAmount
      • Aggregation: Sum
    • X-Axis: DateKey
      • Format: Year
    • Y-Axis: DateKey
      • Format: Month

    Finally, the sales dashboard is ready.

    Sales Dashboard
    Sales Dashboard

    Sharing dashboard

    Now, share this dashboard with your sales team to analyze the sales and make wise decisions about product(s) to improve them.

    Conclusion

    We hope this article helps you build a sales analysis dashboard with Microsoft SQL Server data using the Bold BI Dashboards. If you have any questions on this blog, please feel free to post them in the following comment section. Get started with Bold BI by signing up for a free 30-day trial and create more interactive business intelligence dashboards. You can also contact us by submitting your questions through the Bold BI website or, if you already have an account, you can log in to submit your support question.

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