Configure PowerBI on Dynamics 365 FO developer VM

I’ve created a video tutorial how to configure PowerBI on a stand alone Dynamics 365 Finance and Operations developer VM

PowerBI finance report grouped by main accounts and cost center

A customer recently asked to create a PowerBI report in order to group and compare ledger postings. The report had to meet the following requirements:

  • Compare two time periods
  • Group postings by account and type (e.g. Assets)
  • Postings on a certain cost center need to be shown separately
  • Grouping of accounts and cost centers are defined by a key user in Excel
    e.g. 1001 – 1104 and 5001 – 5002 are “Assets”
  • Cost center groups are defined by using wildcard style
    e.g. 601500 – 61500 and Costcenter ?6?? is Development/Compliance

Dynamics AX ledger postings grouped by account and cost center

Report Data from Dynamics AX

First, we loaded the report data from Dynamics AX into PowerBI. The data contained the LedgerJournalTrans joined with the LedgerAccountView. The Dimenions were renamed to Department, CostCenter and CostUnit.

from LedgerJournalTrans as T
where ACCOUNTTYPE <= 2

Report Definition Data

Next we defined and loaded the report definition from Excel. We used to sheets, one for the definition of the two time frames and one for the group definition

date range for ledger postings

grouping definition for ledger postings

Like initially described the Accounts sheet defines the grouping of postings regarding their account number. For example in line 2 and 3 postings on  accounts 1101 .. 1104 and 5001 .. 5002 shall be grouped as “Assets”. Postings on accounts 601500 .. 606300 with a cost center where the 2nd character is 6 shall be grouped separately as “Development/Compliance” regardless if they are also part of the group “Expenses”.

Both Excel worksheets were loaded into PowerBI. The Accounts was modifed to replace an empty value in the Costcenter column with the text “%”. This was done to use the Costcenter value in a SQL statement with a Like clause (see section “Calling function from the account definition”).

Query Parameter

We added 3 parameters to the PowerBI called FromAccountNum, ToAccountNum and CostCenter. The default values are the smallest account number for the FromAccountNum, the largest account number for the ToAccountNum and the text % for the CostCenter.

PowerBI parameters

Next we changed the query of LedgerJournalTrans and added the parameter to the query. This can be done used “Edit query” on the data set and opening “Advanced Editor”

Parameters in PowerBI query

The new query text in the advanced editor looked like this

Source = Sql.Database(„localhost“, „DynamicsAx“, [Query=“select T.TRANSDATE, T.AMOUNTCURCREDIT,T.AMOUNTCURDEBIT, T.ACCOUNTNUM,V.ACCOUNTNAME,DIMENSION as DEPARTMENT,DIMENSION2_ as COSTCENTER,DIMENSION3_ as COSTUNIT #(lf)from LedgerJournalTrans as T#(lf)join LEDGERACCOUNTVIEW as V on T.ACCOUNTNUM = V.ACCOUNTNUM #(lf)where ACCOUNTTYPE <= 2 AND T.ACCOUNTNUM >= „&FromAccountNum&“ AND T.ACCOUNTNUM <= „&ToAccountNum&“ AND T.DIMENSION2_ like ‚“&CostCenter&“‚ #(lf)order by T.ACCOUNTNUM,T.TRANSDATE#(lf)“, CreateNavigationProperties=false])

With the parameter in the query and the default values set to the parameters the dataset did not change. Next we added a new function to the LedgerJournalTrans. This can be done from the context menu of the query “Create Function”. PowerBI inspects the query statement and creates function parameter for each parameter in the query. In this case FromAccountNum, ToAccountNum and CostCenter.

Calling function from the Account Definitions

In PowerBI a function call can be used like a row wise join. A function can be added by using the used defined function button in the query editor. So we added the function call to the Accounts dataset, i.e. each account definition row fetches all postings from the LedgerJournalTrans with the corresponding accounts and costcenter.

PowerBI calling user defined function

The query parameter are mapped to the fields in the Accounts table.

Parameter values for used defined function

PowerBI will popup a warning that function calls can have a security impact. In the actual version (Mai 2018) PowerBI was quite annoying with security warnings and required a restart (close&open) to stop asking again and again. Finally, expand the Accounts table and the function call results by clicking on the Arrow Right-Left Button next to “GetPostings”. Per default PowerBI adds the fields from the function call result with the function name prefix e.g. GetPostings.Transdate, GetPostings.AmountCurCredit, etc.

As you can see below the Account definition 1101 – 1104 was expanded with all resulting rows from the LedgerJournalTrans that have an account between 1101 and 1104 and any Costcenter (%)

Expanding used defined function call results

Calculate Period Amounts

To get the amount values for each of the two periods, defined in the Daterange Excel sheet, we added 4 additional columns to the Accounts. A debit and credit column for period 1 and period 2.

Ledger postings in period

The code looks like this

CreditDate1 = IF(Accounts[GetPostings.TRANSDATE]>=FIRSTDATE(Daterange[FromDate1]);IF(Accounts[GetPostings.TRANSDATE]<=FIRSTDATE(Daterange[ToDate1]);Accounts[GetPostings.AMOUNTCURCREDIT];0);0)


DebitDate1 = IF(Accounts[GetPostings.TRANSDATE]>=FIRSTDATE(Daterange[FromDate1]);IF(Accounts[GetPostings.TRANSDATE]<=FIRSTDATE(Daterange[ToDate1]);Accounts[GetPostings.AMOUNTCURDEBIT];0);0)


CreditDate2 = IF(Accounts[GetPostings.TRANSDATE]>=FIRSTDATE(Daterange[FromDate2]);IF(Accounts[GetPostings.TRANSDATE]<=FIRSTDATE(Daterange[ToDate2]);Accounts[GetPostings.AMOUNTCURCREDIT];0);0)


DebitDate2 = IF(Accounts[GetPostings.TRANSDATE]>=FIRSTDATE(Daterange[FromDate2]);IF(Accounts[GetPostings.TRANSDATE]<=FIRSTDATE(Daterange[ToDate2]);Accounts[GetPostings.AMOUNTCURDEBIT];0);0)

Display results in matrix

Finally we used a matrix to display the values from the Accounts dataset and grouped it by Name and Accounts.

PowerBI matrix for ledger postings

Security considerations

Injecting range values in a query is not the best way to do this. A better way would be to refactor the LedgerJournalTrans query into a stored procedure and provide the FromAccountNum, ToAccountNum and Costcenter as parameter to the SP.

Calculate and Visualize the Lorenz Curve in Power BI

The Lorenz curve (1) is tool in statistics to visualize the concentration of values within a dataset. A typical well known example is the concentration of wealth within the population. For example in 2017 the top 1% of the US population controls 36,8% of wealth (2). However, the Lorenz curve can also be utilized to visualize the product groups share on revenue.

Demo Data

There are 5 product groups (A,B,C,D,E,F) and multiple sales. The data is stored in the table “Sales” including three columns ProductGroup, Product and Qty. For demonstration purpose, each product group has the same share on total sold products: 20%




A A123 2
A A234 2
B B123 4
C C123 1
C C123 1
C C123 1
C C234 1
D D123 4
E E123 2
E E234 2

The invoices are stored in a separate table called Invoice, it contains three columns: The ProductGroup, SalesId and InvoiceAmount.




A S-0001 5000
A S-0002 6000
E S-0003 1000
E S-0004 10000
D S-0005 11000
B S-0006 4000
B S-0007 4000
B S-0008 5000
C S-0009 5000
C S-0010 5000
C S-0011 4000

In order to visualize the lorenz curve, a data set is required that holds the cumulated frequency of Qty and InvoiceAmount, in ascending order based on the InvoiceAmount. . The first simple SQL Statements and results look like this

select ProductGroup, sum(Qty) as QtySum 
from Sales
group by ProductGroup



A 4
B 4
C 4
D 4
E 4

select ProductGroup, sum(InvoiceAmount) as InvoiceAmountSum
from Invoice
group by ProductGroup
order by InvoiceAmountSum asc



A 11000
D 11000
E 11000
B 13000
C 14000

Now comes the tricky part. A SQL statement is required which creates the cumulated sums. To do this the SQL function row_number is used to create a line number in the result set. Then the same result set is joined with all records smaller or equal the current row number and the InvoiceAmount is summed up. The SQL Statement looks like this.

select temp1.idx, temp1.ProductGroup, temp1.InvoiceAmountSum,
sum(temp2.InvoiceAmountSum) as CumulateSum

select ROW_NUMBER() over (order by InvoiceAmountSum asc) as idx, ProductGroup, InvoiceAmountSum
from (
    select ProductGroup, sum(InvoiceAmount) as InvoiceAmountSum
    from Invoice
    Group by ProductGroup)

as temp1
inner join
    select ROW_NUMBER() over (order by InvoiceAmountSum asc) as idx, ProductGroup, InvoiceAmountSUm
    from (
        select ProductGroup, sum(InvoiceAmount) as InvoiceAmountSum
        from Invoice
        Group by ProductGroup)
as temp2 on temp1.idx >= temp2.idx
group by temp1.idx, temp1.ProductGroup, temp1.InvoiceAmountSum

The result looks like this





1 A 11000 11000
2 D 11000 22000
3 E 11000 33000
4 B 13000 46000
5 C 14000 60000

Finally  the SQL query needs to bee extended to include also the cumulated sales qty. Moreover, a line starting with 0 values is required to make the Lorenz cure look correct. This is done by adding a row using UNIOIN. Here is the complete SQL statement and the result set:

select temp1.idx, temp1.ProductGroup, temp1.InvoiceAmountSum,
sum(temp2.InvoiceAmountSum) as CumulatedSum, s.SalesQty,
sum(s.SalesQty) as CumulatedSales

select ROW_NUMBER() over (order by InvoiceAmountSum asc) as idx, ProductGroup, InvoiceAmountSum
from (
    select ProductGroup, sum(InvoiceAmount) as InvoiceAmountSum
    from Invoice
    Group by ProductGroup

as temp1
inner join
    select ROW_NUMBER() over (order by InvoiceAmountSum asc) as idx,   
    ProductGroup, InvoiceAmountSUm
    from (
        select ProductGroup, sum(InvoiceAmount) as InvoiceAmountSum
        from Invoice
        group by ProductGroup
as temp2 on temp1.idx >= temp2.idx

inner join
    Select ProductGroup, sum(Qty) as SalesQty
    from Sales as s 
    group by ProductGroup
as s on s.ProductGroup = temp1.ProductGroup

group by temp1.idx, temp1.ProductGroup, temp1.InvoiceAmountSum, s.SalesQty


select 0 as idx,“ as ProductGroup, 0 as InvoiceAmountSum,0 as CumulatedSum,
0 as SalesQty,0 as CumulatedSales







0   0 0 0 0
1 A 11000 11000 4 4
2 D 11000 22000 4 8
3 E 11000 33000 4 12
4 B 13000 46000 4 16
5 C 14000 60000 4 20


Power BI

The next step is load the data into Power BI and calculate the relative cumulated frequency  for Sales and Invoice. The is done by diving the cumulated frequency by the total numbers.

  1. Open a new Power BI report
  2. Select Get Data from SQL Server and provide the connection information
    In the details copy & paste the SQL Statement from above
  3. Rename the data set to SalesInvoice

After this there should be a dataset with the values from the table above in Power BI. Add two additional calculate the relative cumulated frequency. Format the columns as percentage.

RelativeFreqInvoice = SalesInvoice[CumulatedSum] / 


RelativeFreqSales = SalesInvoice[CumulatedSales] / sum

The dataset in Power BI should look like this






Cumulated Qty


Relative FreqSales

0   0 0 0 0 0% 0%
1 A 11000 11000 4 4 18% 20%
2 D 11000 22000 4 8 37% 40%
3 E 11000 33000 4 12 55% 60%
4 B 13000 46000 4 16 77% 80%
5 C 14000 60000 4 20 100% 100%

Go to the report designer and add a new line chart. Set as Axis the RelativeFreqSales. To get the diagonal line for the Lorenz curve add the RelativeFreqSales again as Value. Then also add the RelativeFreqInvoice as Value in the diagram properties. Now there are two lines, the 45° line and the lorenz curve underneath. In this example it should look like this:

Lorenz Curve in Power BI


Visualize the firms contribution to total revenue in Power BI

We recently discussed at work how to display the contribution of multiple firms to the total revenue in Power BI, in a way that the firms can be filtered but the total revenue stays constant. We came up with a very simple no-code solution.

Data from Dynamics AX 2012 R3

All the required data can be fetched from the CustInvoiceJour table in Dynamics AX. There are three datasets in the Power BI data model. First, the invoices including the InvoiceAmountMST, InvoiceYear and DataAreaId. Second the sum of InvoiceAmountMST grouped by Year and DataAreaId. Finally, a table that contains the years. Here are the SQL statements to load the data.

InvoiceId, InvoiceAmountMST, InvoiceDate, DataAreaId,
year(InvoiceDate) as InvoiceYear
from CustInvoiceJour

Total Revenue:

sum(InvoiceAmountMST) as InvoiceAmountTotal,
year(InvoiceDate) as InvoiceYear, DATAAREAID
from CustInvoiceJour
group by year(InvoiceDate),DATAAREAID

In Power BI create a new dataset and enter the years manually, like 2010, 2011, 2012, etc.

Power BI Years Table

In Power BI go to the data model an connect the Invoices and Total Revenue with the dataset that contains the years


Line and stacked Column

Add a new Line and stacked Column chart to the Power BI Report. Set the field Year from the Year table as shared axis. From the CustInvoiceJour set the DataAreaId as Colum Series and the InvoiceAmountMST as Column  values. Set the InvoiceAmountTotal from the Totals table as line values. In the format tab disable the Y-Axis property Show Secondary.

Diagram settings 

Your diagram should look like this. Filtering the companies does not effect the total revenue line.


SQL Server 2016 SP1 and Dynamics AX 2012 R3

Here are some ideas on SQL Server 2016 SP1 and Dynamics AX 2012 R3

Enterprise Features in Standard Edition since Service Pack 1

There was a major change in Service Pack 1 for SQL Server 2016. While most cool features were Enterprise-Edition-Only for a very long time, many features like Column Store Index and Compression are now available for Standard Edition too. Have a detailed look at this Blog. SQL 2016 also introduces new features like the Query Store and Power BI Integration with Reporting Services

Reporting Services

SQL Server 2016 Reporting Services require Dynamics AX R3 CU12 and an additional KB3184496 hotfix. Otherwise the installation will fail. The typical AX user won’t see the difference between SSRS 2016 and older versions. However, there are some features that might be interesting for us AX folks too, namely Power BI Integration.

Right now (January 2017) Power BI Integration is not so useful. You can place your Power BI files at the SSRS, which is actually only a better alternative to place the .PBIX file on a file share. However, it is said SSRS will be able not only to store but also to render Power BI files On Premises. This might be interesting for customers who are not willing to use Power BI in the cloud.

Host Power BI files in SSRS 2016

Right now in SSRS 2016 SP1 you can pin SSRS reports to your Power BI (Online) dashboard. This means, you can integrate your SSRS reports in Power BI. This might not sound very useful for Dynamics AX users. Why should I pin an invoice to a Power BI dashboard? But if a customer is already using SSRS for reporting, this might be a good option to start with Power BI and reuse the existing reports. Some Dynamics AX reports with OLAP data source can also be pinned to the Dashboard.

There is a Power BI Button in the SSRS report portal


This will pin your report to one of your Power BI (Online) dashboards



Query Store

This is a very useful feature. All of us are familiar with performance problems reported by some users. The problem is to identify and reproduce the query which performed badly and find the reason. Query Store can be used to store information about such problem-queries, like the SQL statement executed, the used execution plan, etc. In SQL Server Management Studio you can view reports based on execution time, logical and physical write/reads, memory usage, etc.Query Store therefore is a very useful feature in SQL 2016 to identify performance issues.

SQL 2016 Query Store

Column Store Index

Column Store Indices were introduced in SQL Server 2012 too speed up aggregation queries (e.g. sum). However, CSI hat a lot of limitations and  was an Enterprise Edition features till 2016 (non SP). In SQL 2016 SP1 we can now use CSI in combination with Dynamics AX at our customers who have licensed Standard Edition of SQL Server.

In contrast to traditional Row Store Indices where records stored in 8 KB pages (e.g. CustInvoiceJour records), CSI store column values (e.g. LineAmountMST) together in 8 KB pages. Therefore aggregation functions can perform faster because less pages have to be read.

Here is an example:

select CustGroup, year(InvoiceDate) as YR, sum(LineAmountMST) as Amount
from CustInvoiceJour
group by CustGroup, year(InvoiceDate)

When executing this query against a Dynamics AX Contoso Demo database, 2158 logical reads were required.

Query Dynamics AX 2012 R3 database without Column Store Index

Next, create a non-clustered Column Store Index on the fields CustGroup, InvoiceDate and InvoiceAmountMST which are used in the query

Create a Column Store Index in Dynamics AX 2012 R3 database

The same query now utilizes the Column Store Index to fetch and aggregate the data. The IO statistics show that less reads were required to get the result. The query performs faster than with the traditional Row-Store index.

Colum Store Index with Dynamics AX 2012 R3

Be aware that Dynamics AX removes the Column Store Index from the database when you synchronize the data dictionary. This might not be such an issues in a production environment. When you deploy a new application version from Test to Live, make sure to recreate all lost CSI.

Stretch Database

With stretch database you can migrate cold data (aka. existing but hardly not used) from your on premises expensive high performance storage to the cloud. This means you can split the data in large table and move old records in SQL azure. The application doesn’t recognize this split. Only if you query cold data, it will take longer to fetch the result. This sounds good. however there are some very crucial show stoppers.

  • You can’t UPDATE or DELETE rows that have been migrated, or rows that are eligible for migration, in a Stretch-enabled table or in a view that includes Stretch-enabled tables.
  • You can’t INSERT rows into a Stretch-enabled table on a linked server.

So right now, this feature is not useful for Dynamics AX on premises installation

Dynamic colored R Diagram in Power BI using Earthtone

Power BI integrates R to perform complex analysis and sophisticated visualization. Earthtones is an R library which takes a screenshot from Google Maps of certain geo coordinate and extracts the landscape colors. Earthtones can be used to color diagrams based on the local color schema.


The package can be found on github. There is also a description how to donwload and install the package. Using earthtones is easy. The function get_earththones takes the parameters longitude and latitude, zoom and the number of colors to extract. The earthtones for Steyr look like this:


Steyr Earthtones

Power BI Data Model

The data model in this example is very simple. There are two excel sheets, one for the revenue by city and item group, another for the geo coordinates (longitude / latitude) and optimal zoom level per city.

Excel Sheet Revenue per City and Item Group

City Geo Coordinates

The Power BI model is very simple, both data sources are linked by the city name

Power BI Data Model

R Boxplot diagram in Power BI

In this example a simple boxplot is used to visualize the revenue by item group. A data slicer for the column city is used to filter the data. The R diagram takes the following columns as input:

  • Longitude
  • Latitude
  • Zoom
  • City
  • Price
  • Group

If only one city is selected, the R script shall gather the cities earthtone colors and format the diagram. If more than one city is selected, the diagram shall be formatted in red, blue and green. The following script loads the earthtone library and gets the distinct number of city names from the dataset. If there is more than 1 distinct name in the dataset the color variable is set to red,blue,green. Otherwise, earthtone is used to get the city typical color schema.


numCities <- length(unique(dataset$Stadt))
if(numCities > 1) {
color <- c(„red“,“blue“,“green“)
} else {
color <- get_earthtones(latitude = dataset$Lat[1],
zoom= dataset$Zoom[1],

boxplot(Preis~Gruppe,dataset,col=(color),ylab=“Revenue“,xlab = „Item Group“)

The R script in Power BI looks like this:

R Script and Boxplot in Power BI

If a city is selected, for example San Francisco, the diagram is formatted in the colors blue, gray and brown.

R Diagram in Power BI with dynamic color

The colors fit the blue sea, the bay and the city seen from space.

R Earthtone for San Francisco

If another city, for example Cairo, is selected the diagram gets formatted in dark green, dark- and light brown.

R Diagram in Power BI with dynamic color

That fits the cities local color schema, the brown buildings, the green plants along the Nile and the desert sand.

R Earthtone for Cairo

Create a Power BI Dashboard for Dynamics AX 2012 Sales

This is an update to the previous published articles on Data Visualization, OData Feeds, Power Map, Power Pivot in Office 2013 and Power Pivot in Office 2010. It shows how to use Power BI for Desktop to create a Sales Dashboard for Dynamics AX 2012 (R2).

Power BI Dashboard

Get Data

Start Power BI for Desktop and start with an empty report. From the ribbon on top click “Get Data”, choose SQ Server and provide your server and database. In this example I’m using a single server installation. However, in a production environment you might need to provide <SERVERNAME> \ <INSTANCENAME> , <PORT> e.g. SRVSQL\PROD,2303.

Get data into Power BI

In the next step you have to provide credentials. In my case I’m allowed to access the server with my domain account. In a production environment it is recommended to create a separate Login which is only used for BI Purpose. Don’t get confused if you get a warning that your SQL does not support encryption. If the connection was established successfully, the data wizard presents you a list of tables. Select the following tables:

  • CustInvoiceJour
  • CustInvoiceTrans
  • CustTable
  • InventTable
  • LogisticsPostalAddress

Select tables for Power BI

Click Load, and choose “Import” to load the data in Power BI for Desktop.

Transform Data

In Power BI for Desktop, at the Ribbon click “Edit Queries”. This will open the query editor. We don’t need all columns for this Demo. For each table click the “Choose Columns” button and the select only the following columns:

Choose columns for Power BI

CustInvoiceJour CustInvoiceTrans CustTable
  • InvoiceAccount
  • InvoiceDate
  • InvoiceId
  • NumberSequenceGroup
  • SalesId
  • InvoicePostalAddress
  • DataAreaId
  • InvoiceId
  • InvoiceDate
  • NumberSequenceGroup
  • ItemId
  • LineAmountMST
  • SumLineDiscMST
  • DataAreaId
  • AccountNum
  • CustGroup
  • DataAreaId
InventTable LogisticsPostalAddress
  • ItemId
  • ItemType
  • DataAreaId
  • Address
  • CountryRegionId
  • ZipCode
  • City
  • RecId

Click “Close & Apply” to finish this task.

Choose columns for Power BI


Create Relations

In Power BI for Desktop switch to the Data View (with the table symbol on the left pane). It is required to create primary keys and foreign keys before linking the tables. From the list of tables (on the right) select the CustTable and at the Ribbon click “New Column”. Type the following definition:


Create Foreign Keys in Power BI

This will create a new column with a customer account which is unique for all company accounts. Repeat this step for the following tables and columns:











Save, and open the relations by clicking on the relations item in the navigation pane on the left. You can drag&drop columns from one table to another table to create relations. Link the following columns:

  • CustInvoiceTrans,FK_Item > InventTable.PK_Item
  • CustInvoiceTrans.FK_Invoice > CustInvoiceJour.PK_Invoice
  • CustInvoiceJour.FK_Cust > CustTable.PK_Cust
  • CustInvoiceJour.InvoicePostalAddress > LogisticsPostalAddress.RecId

Your data model should look like this:

Create relations in Power BI data model

Name the ItemType

In the data view, select the InventTable. From the ribbon create a new column and name it “TypeName”. Add the following code to translate the Enum based ItemType Integer Value to a meaningful name.

TypeName = IF(INVENTTABLE[ITEMTYPE] = 0; „Item“; IF(INVENTTABLE[ITEMTYPE] = 2; „Service“; „Not an Item“))

The InventTable should look like this:

Name item type column

Create a Discount measure

Next we will create a measure which calculates the given discounts as the percentage of the total price. Open the data view using the second button on the left navigation pane. Select the CustInvoiceTrans. From the ribbon, click “New Measure” button in the “Modelling” tab. Provide the following code:


For example:

Qty = 1 € , Unit Price = 1000 €     –> Price = 1000 €
Discount = 100 €                    –> Price = 900
Discount Percentage 3 %             –> Price = 873 €

CustInvoiceTrans.LineAmountMST = 873
CustInvoiceTrans.Discount = 100
CustInvoiceTrans.LinePercent = 3.0
CustInvoiceTrans.SumLineDiscMST = 127

M_DiscPerc = 127 * 100 / (873 + 127) = 12,7


Switch to the empty report view using the first button on the left navigation pane. From the Visualization toolbox click the “Card”. This will place an empty card on the report. Drag&Drop the LineAmountMst from the CustInvoiceTrans on the empty card. It should look like this:

Power BI card chart

Next, place a map from the toolbox on the report. Drag&Drop the fields CountryRegionId, City and ZipCode from the LogisticsPostalAddress table on the Location. Drag&Drop the LineAmountMST from the CustInvoiceTrans on the Values Field. The map should look like this:

Power BI map chart

Add a new Gauge to the report and use the Measure M_DiscPerc as value. You cannot set a hardcoded Min. and Max. value in the data properties. Switch to the Format view using the pencil icon.  In the group Gauge Axis, set the Min. Value 0, the target value to 3 and Max. Value 100. Depending on your data, the gauge may look like this:

Power BI gauge control

Next a donut chart to visualize the revenue per item type. Drag&drop the LineAmountMST from the CustInvoiceJour on the value property of the donut chart and drag the TypeName from the InventTable.

Power BI donut chart

Place a column chart on the report to visualize the revenue per customer group. Place the LineAmountMST in the Value field. Use the CustGroup from the CustTable as Axis. Change the sort order to LineAmountMST by using the […] Dropdown Menu in the upper right corner of the chart.

Power BI column chart

Finally, add a line chart on the report to visualize the revenue per year. Place the LineAmountMST from the CustInvoiceTrans on the charts value field and put the InvoiceDate from the CustInvoiceTrans on the Axis field.

Power BI line chart


Give each chart a meaningful name. Change the size for the text to fit your report style. Switch to the data view. Change the column names into something more meaningful for an end user e.g. LineAmountMST to Amount. Change the columns formats e.g. Currency for LineAmountMST, date format for the InvoiceDate.