Cumulative to Monthly Data Reprocessing

This implementation guide shall provide you with steps on how to reprocess cumulative Profit & Loss (P&L) data into monthly figures with Power BI and DAX, a data modeling and reporting tool and data analysis expression language respectively.

Pre-requisites:

Make sure you have access to Power BI Desktop and the raw cumulative P&L data files or databases.

Remember! We are working directly in Power BI. If your data resides in a different place, make sure to import it correctly.

Here is a step-by-step approach to achieve this:

I. Import your cumulative data

The first step is getting your data into Power BI. This might be a centralized database, a file on your computer, or something else. To import your cumulative P&L data into Power BI:

1. Open Power BI Desktop
2. Click on the "Home" tab, and then click on "Get Data"
3. Choose the appropriate import method based on your data location

Upon successfully importing your data, you should see it displayed within Power BI's data view.

II. Creating 'Date' Table

Create a Dates table which will have all dates for a range you need (for example, from 2010 to now). If there is not an existing "Date" column with distinct dates in your dataset needed for accurate time analysis, this creation process is crucial.

Date = 
ADDCOLUMNS (
CALENDAR (DATE(2010,1,1), TODAY()),
"DateAsInteger", FORMAT ( [Date], "YYYYMMDD" ),
"Year", YEAR ( [Date] ),
"Monthnumber", FORMAT ( [Date], "MM" ),
"YearMonthnumber", FORMAT ( [Date], "YYYY/MM" ),
"YearMonthShort", FORMAT ( [Date], "YYYY/mmm" ),
"MonthNameShort", FORMAT ( [Date], "mmm" ),
"MonthNameLong", FORMAT ( [Date], "mmmm" ),
"DayOfWeekNumber", WEEKDAY ( [Date] ),
"DayOfWeek", FORMAT ( [Date], "dddd" ),
"DayOfWeekShort", FORMAT ( [Date], "ddd" ),
"Quarter", "Q" & FORMAT ( [Date], "Q" ),
"YearQuarter", FORMAT ( [Date], "YYYY" ) & "/Q" & FORMAT ( [Date], "Q" )
)

This technique generates a single column table, filled with sequential dates from 2010 to present day (You can modify as per your needs), along with related attributes like Year, Month, Quarter, and Day of the Week.

III. Binding 'Date' to cumulative P&L Data

Use Power BI's modeling view and create a relationship between your Date table and your cumulative P&L data.

• Your 'Date' table should be tied to the 'Date' field in your dataset.

IV. Creating the Monthly Data Measure

The primary task at hand involves writing a DAX measure that will transform your cumulative data into monthly data.

The difference formula, DIFFERENCE = [Cumulative P&L] - [Cumulative P&L](PREVIOUSMONTH([Date])), would return the difference in the cumulative total from the current month to previous month.

First, we should establish the 'Cumulative P&L' measure:

Cumulative P&L = SUM(YOURDATATABLE[YourP&Lcolumn])

YOURDATATABLE refers to the table that contains your data, YourP&Lcolumn refers to the name of the column that holds the cumulative P&L figures in your data.

Once we get 'Cumulative P&L' measure, then we can calculate the monthly difference.

Monthly P&L = 
[Cumulative P&L] - CALCULATE([Cumulative P&L], PREVIOUSMONTH('Date'[Date]))

V. Visualizing the Monthly P&L Data

To visualize this data:

1. Click on the 'Report' view in Power BI.
2. Drag and drop your 'Date'[Date] field onto the axis of the visualization and the 'Monthly P&L' measure as the value.

'This is your monthly P&L data derived from your original set of cumulative data.

Note: NULL values might appear for months where there was no activity. You can filter them out directly from your visual if needed.

This concludes the reprocessing of cumulative data to monthly figures. As you progress in your data analysis venture, I am sure you will appreciate Power BI and DAX's capability to simplify and solve complex problems. For the successive parts of your project, you can rely on similar strategies of data manipulation with DAX and build upon it as per your needs.

Monthly Delta Calculation and Visualization using Power BI and DAX

Once you've broken down your cumulative P&L into monthly figures, the next step is to calculate the monthly delta and visualize it in Power BI. Delta here refers to the month-on-month changes in your P&L figures.

The following DAX and Power BI implementation will help you achieve this task.

1. DAX Syntax For Monthly Delta Calculation

In Power BI, using DAX (Data Analysis Expressions), you can create a new calculated column (or measure) in your table to track the monthly delta for the P&L. Use the following DAX expressions:

1. Create a new calculated column "MonthYear" to combine Year and Month. This column will help in ordering data in the correct timeline.

MonthYear = [Year] & [Month]

2. Create a new calculated column for "Monthly Delta". The delta is calculated as the difference between this month's P&L and the previous month's P&L.

Monthly Delta = 
  VAR ThisMonthP_and_L = SUM([P&L])
  VAR LastMonthP_and_L = 
    CALCULATE (
      SUM([P&L]),
      FILTER (
        ALL(Table),
        Table[MonthYear] = EARLIER(Table[MonthYear]) - 1
      )
    )
RETURN 
  ThisMonthP_and_L - LastMonthP_and_L

This code will calculate the difference between the present month's P&L and the previous month's P&L, populating a new column "Monthly Delta" in the table.

2. Visualization in Power BI

After creating our calculated column for "Monthly Delta" in the data model in Power BI, visualizing this data becomes straightforward.

Let's create a Line Chart to track the monthly fluctuations (delta) in the P&L:

1. Click on the "Line chart" visualization in the 'Visualizations' pane in Power BI.
2. For 'Axis', use the 'MonthYear' field from your table.
3. For 'Values', drag and drop the 'Monthly Delta' calculated column.
4. Configure 'X-Axis' and 'Y-Axis' from the 'Format' option as per your preference.
5. Save the dashboard.

The line chart will allow you to effectively track the trends and fluctuations in the monthly deltas of your P&L.

Data-driven Financial Performance Appraisal

One of the main objectives of financial performance appraisal is to effectively track and observe changes over time in order to manage risk and understand the health of an organization. Leveraging Power BI and DAX, we can create an interactive and visual experience that allows for improved decision-making processes.

This guide will walk through the process of implementing data-driven financial performance appraisal using DAX calculations and Power BI visualizations.

Prerequisites

Before starting with performance appraisal, your dataset must have a column with monthly figures that can illustrate your company's financial performance.

Make sure you have done these steps:

1. Cumulative to Monthly Data Reprocessing
2. Monthly Delta Calculation

Step 1: Setting Up the Performance Appraisal Measures

Now that monthly deltas are available, we can utilize DAX to calculate useful measures like Running Total, Month over Month Growth %, and Year over Year Growth % which help understand performance.

1. Running Total

Running_Total = 
CALCULATE(
    SUM('Financial_Data'[Monthly_Delta]),
    FILTER(
        ALLSELECTED('Financial_Data'[Date]),
        'Financial_Data'[Date] <= MAX('Financial_Data'[Date])
    )
)

2. Month over Month Growth %

MoM_Growth = 
DIVIDE(
    [Monthly_Delta] - CALCULATE(
        [Monthly_Delta],
        DATEADD('Financial_Data'[Date], -1, MONTH)
    ),
    CALCULATE(
        [Monthly_Delta],
        DATEADD('Financial_Data'[Date], -1, MONTH)
    ),
    BLANK()
) * 100

3. Year over Year Growth %

YoY_Growth = 
DIVIDE(
    [Monthly_Delta] - CALCULATE(
        [Monthly_Delta],
        DATEADD('Financial_Data'[Date], -1, YEAR)
    ),
    CALCULATE(
        [Monthly_Delta],
        DATEADD('Financial_Data'[Date], -1, YEAR)
    ),
    BLANK()
) * 100

Step 2: Visualizing the Performance Appraisal

After setting up the DAX measures, we can visualize this data in a simple line chart.

1. Drag the Date field into the Axis field box, and the measures into the Value field box of the line chart visual. One line chart for each measure is recommended for visual clarity.

2. In the Format pane for each visual, adjust line size, color, and other aesthetic options according to your preferences.

Step 3: Set Up Interactivity and Filters

1. Interactivity: For effective decision making, select the visuals and go to Format > Edit Interactions > Highlight.

2. Filters: Add the slicer visual for Filters, Modes, Date, and other relevant fields.

Power BI provides an effective way to visually manage the performance of your financial figures. Performance assessment becomes much more feasible, interactive, and simple with these visuals in place. Utilize these steps to incorporate this strategy into your financial decision-making process.