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Project Report Video shown below:
Project Report and Dashboard Sreenshot shown below:
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Loaded Files from Excel Worksheet, Excel CSV
Distinct v/s Unique
Data Set : 1 2 3 3 4 4
Distinct Value : 4
Unique Value : 2 -
Power Query : Transform Data are done in Power Query.
- All trasformation data are recorded in APPLIED STEPS section like remove add column & rows etc.
- M Code : Whatever the changes made on data, those action are done by M code Language in Backend.
- Create MasterDate Table with Date Format
DateMaster = CALENDAR(FIRSTDATE(Bank_Churn[Bank DOJ]), LASTDATE(Bank_Churn[Bank DOJ]))Year = YEAR(DateMaster[Date])Month = FORMAT(DateMaster[Date], "MMM")
- Data Modeling in Power Pivot : Dealing with the cardinality between the tables.
Creating Relationship between the tables. Fact Tables & Dimension Tables.
- One to One Relationship & One to Many Relationship
- Star Schema : All the Dimension tables are connected to the main Fact table.
- Snowflake schema : Dimension tables may or maybe indirectly connected to the main Fact table through another Dimension table.
- Galaxy Schema or Bridge Schema : Multiple Fact tables and Dimension tables involves.
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Created Seperate Table for Measure.
Total Customers = COUNT(Bank_Churn[CustomerId])Active Customers = CALCULATE(COUNT(Bank_Churn[IsActiveMember]), ActiveCustomer[ActiveID]=1)Inactive Customers = CALCULATE(COUNT(Bank_Churn[IsActiveMember]), ActiveCustomer[ActiveID]=0)Credit Card Holders = CALCULATE(COUNT(Bank_Churn[CustomerId]), CreditCard[Category]="Credit card holder")Non Credit Card Holders = CALCULATE(COUNT(Bank_Churn[CustomerId]), CreditCard[Category]="Non Credit card holder")Exit Customer = CALCULATE([Total Customers], ExitCustomer[ExitCategory]="Exit")Retain Customers = CALCULATE([Total Customers], ExitCustomer[ExitCategory]="Retain") -
Displayed all Measures in Card Visual.
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Created Slicer to filter the Visual data by Year, Month, Location, Gender
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Created Column for Customers with Credit Score remark.
Credit Type = SWITCH(TRUE(), Bank_Churn[CreditScore]>=800 && Bank_Churn[CreditScore]<=850,"Excellent", Bank_Churn[CreditScore]>=740 && Bank_Churn[CreditScore]<=799, "Very Good", Bank_Churn[CreditScore]>=670 && Bank_Churn[CreditScore]<=739,"Good", Bank_Churn[CreditScore]>=580&&Bank_Churn[CreditScore]<=699,"Fair", Bank_Churn[CreditScore]>=300&&Bank_Churn[CreditScore]<=579,"Poor") -
Clustered Column Chart visual. Active & Inactive members. Year and Month Wise. With some formatting. Note : Drill Up, Drill Down Concept.
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Time Intelligence Functions. How to get previous months Exit customers.New Measure created.
Previous Month Exit Customers = CALCULATE([Exit Customer],PREVIOUSMONTH(DateMaster[Date])) -
Line Chart. It shows Month wise Exit Customer and Secondary Y axis as Previous month Exit Customer.
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Donut Chart to show in percentage. Exit Customer by Gender Category.
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Bar Chart Exit Customer by Credit Type data.
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Go to Insert > Q&A > Ask questions like Exit Customer by Category in Pie Chart. It will provide the ready output.
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Try Smart Narative tool to get summary of any visual reports
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Create new Measurement to get Churn percentage of customers.
Churn % = var EC = [Exit Customer] var TC = [Total Customers] var ChurnPercentage = DIVIDE(EC,TC) return ChurnPercentage -
Create Matrix visual table to showcase the Churn percentage report.
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Create Button to Navigate in next page of dashboard.
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RLS ( Row Level Security ): -Moedeling -> Manage Roles -> Create -RoleName -> Tables (Geography) -> Add Filters -> Geography Location. -After creating RLS you can click View As roles to select the filter.
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Now in Power BI service create Workspaces. -My Work space is for internal purpose only you can see the report. -Workspace is to share across larger audience.
- Give Access to Group Member by Manage access button.
- Access role Admin, Member, Contributor, Viewer
- Now Publish the darsboard report from Desktop PowerBI to Power Bi Services
- Home -> Publish -> Select Workspace -> Submit.
- Add Members to Security :
- More option in Dataset -> Security -> People or Group who belong to this role.
- This is Static RLS. Dataset -> Schedule Refresh ->
- Refresh the Data :
- On Demand Refresh in Desktop Power BI. Home -> Refresh.
- Schedule Refresh in Power BI Service. Gateways are required if the data is On Premise or in local machine.
- If the data is in cloud then no need Gateway connection.
- Install Gateway in PowerBi Service : Settings -> Manage Connections & Gateway -> click to Learn More About. Follow the page instruction.
- After installation done Add to Gateway and Map to the connection.
- Now schedule the Refresh with Frequency and Time.
- Create New Dashboard in Power BI Service and Pin the visuals from Report.
- Report is ynamic and Dashboard is Static. It is single page data story. We cannot add/Pin Slicers to Dashboard.
- Subscribe to Dashboard : To send report by email.
Credits :- Thanks to KSR Datavizon