RPA with Dynamics 365 Finance & Supply Chain

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Are you looking for ways to automate some of your routine accounting functions, like reconciling sub ledgers to the general ledger?   Microsoft has recently created some examples using Power Automate Desktop (think of it like Task Recording on steroids). It can not only automate steps through Dynamics 365, but it can also automate Excel and other applications. In one example from Microsoft they automate the AR to GL reconciliation: Automatic running of the AR aging and the customer/ledger reconciliation reports. Power Automate then extracts data from both reports in Excel and compares the balances. Power Automate then posts a Team message letting you know the subledger is in balance. Power Automate saves the reports with the date in the file name, so there is backup. Microsoft Directions & Example   I working with the example, I needed to make a couple of adjustments to the sample flow that was provided but I was able to get it to work. Here is a video of the flow running in
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COVID 19 Dashboard – Article 2 - Transforming the Data – Calculating between rows in Power Query

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I will continue to build on my earlier posts about my COVID19 Dashboard.  In this series, I am writing a few different blog articles describing not only how I built it, but some things I learned in the process.

The current list of planned topics include:
  •  Working with growing CSV files
  •  Using index and merge when transforming data
  •  Using time functions to calculate the daily change
  •  Reporting based on the population
  •  Working with maps, setting data types correctly
  •  Possibly more to come depending on how long this all goes….


PART 2 – Continuing to transform the data
In my first post, I explained how I brought in data from a CSV file and used “Unpivot Columns” to transform the data into a format that works much better for reporting.  Once the data was in this format, I quickly noticed that the values (Cases, Deaths and Recoveries) were cumulative.  In other words, these amounts were ending balances not daily transactions, if I look at it as an accountant.  These balances were going to make my ideas for reports more difficult, since I wanted to see the change day over day, net change over day, etc.

Sample File
County-State
Date
Confirmed Cases
Orange, California
3/15/2020
14
Orange, California
3/16/2020
17
Orange, California
3/17/2020
22
Orange, California
3/18/2020
29
Orange, California
3/19/2020
53

Desired File
County-State
Date
Confirmed Cases
Daily Cases
Orange, California
3/15/2020
14
14
Orange, California
3/16/2020
17
3
Orange, California
3/17/2020
22
5
Orange, California
3/18/2020
29
7
Orange, California
3/19/2020
53
24

So, I started my normal approach to problem solving for Power BI, I did an internet search.  I was looking for “combining rows in Power Query” or “add column power bi from previous row”.  I found a tutorial on ExcelTown that helped me solve the problem.
Step by step solution

Step 1 – Add an index column to my data





Step 2 - Add an additional column add 1 to the index column


Step 3 – Since my data has repeated dates (one date for each county and state combination (my Combined_Key column), I needed to add some additional keys for the future merge that I was going to do, because I only want to look at the prior row, if it is the same county and state combination.  To do this, I simply added to new columns.  The first one combined Combined_Key with Index and the second one combined Combined_Key with Addition.
·         Merged column = Table.AddColumn(#"Inserted Addition", "Merged", each Text.Combine({[Combined_Key], "-", Text.From([Index], "en-US")}), type text)
·         Merged column2 = Table.AddColumn(#"Inserted Merged Column", "Merged.1", each Text.Combine({[Combined_Key], "-", Text.From([Addition], "en-US")}), type text)








Step 4 - Once the keys were in place, I used Merge to merge the table with itself.


Step 5 – Now I can bring in the Confirmed Cases from the prior row by clicking on the doublesided arrow at the header and show the value from the connected query.

Step 6 – I removed all the index and key columns that are no longer needed and renamed my new column from the prior day to Prior Confirmed Cases.


Step 7 – I added a new column to calculate net change (Confirmed Cases – Prior Confirmed Cases) Table.AddColumn(#"Renamed Columns2", "New Cases", each [Confirmed Cases]-[Prior Confirmed Cases])


I repeated these steps with other tables, so I had net change in every table.  I also used merge to combine Cases data with Death data, so I had a simpler data model when I work with visualizations.

In my next article, I will move away from Power Query and into DAX to discuss some of the measures I created in the report.


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