DAX queries in Power BI

The acronym DAX stands for Data Analysis Expressions. DAX is a set of functions, operators, and constants which can be used to construct formulas from existing information in your data store. if you are familiar with creating functions in Excel that knowledge comes in handy to create DAX functions.

An example for DAX function format would be like:

<MEASURE_NAME> = <DAX FUNCTION>(<TABLE_NAME>[<COLUMN_NAME>])
Eg:
Total sales = SUM(financials[sales])

Lets check out some of the DAX functions

DISTINCT
Distinct Cities = DISTINCT(Portfolio[City])

SUM
Total Sales = SUM(financials[sales])

SUMX
Allows to get the sum of an expression evaluated for each row in the table.
SUMX(<table>, <expression>)

FILTER
Filtered sales = FILTER(financials, financials[ Sales] > 100000)
Here you can create a new table to filter and get rows where sales are greater than 100000. The base table is 'financials'. The new table created is 'Filtered sales'.

CALCULATE
For this example you can refer to a sample table which I created. Refer the code in Annex for table creation.

total online sales = CALCULATE(SUM('Sales Types'[Amount]),FILTER('Sales Types','Sales Types'[Mode]="ONLINE"))

online sales 2010 = CALCULATE(SUM('Sales Types'[Amount]),FILTER('Sales Types','Sales Types'[Mode]="ONLINE"), 'Sales Types'[Year]="2010")

The total online sales put into a table would look like below

SUMMARIZE

Sales Summary = SUMMARIZE('Sales Types', 'Sales Types'[Region], "Sales per region", COUNT('Sales Types'[Amount]), "online sales count", CALCULATE(COUNT('Sales Types'[Mode]), FILTER('Sales Types','Sales Types'[Mode]="ONLINE")), "total online sales", 'Sales Types'[total online sales], "total store sales", 'Sales Types'[total store sales], "store sales count", CALCULATE(COUNT('Sales Types'[Mode]), FILTER('Sales Types','Sales Types'[Mode]="STORE")))

UNION
Union Test = UNION(SELECTCOLUMNS(Employees, "Lat", Employees[Lat], "Lon", Employees[Lon], "Type", "Employee"), SELECTCOLUMNS(Portfolio, "Lat", Portfolio[LAT], "Lon", Portfolio[LONG], "Type", "Office"))

In the last example above, I have used the UNION and SELECTCOLUMN function to get both office and employee locations in a hypothetical organization.

In order to visualize this sample you can create a new table and provide the function as shown below

Annex

Sales Figures =
DATATABLE (
    "Year", STRING,
    "Asia", DOUBLE,
    "Europe", DOUBLE, "Australia", DOUBLE,
    "America", DOUBLE,
    {
        { "2010", 100000, 200000,80000, 100000 },
        { "2011", 400000, 250000,100000, 100000 },
        { "2012", 600000, 350000,150000, 100000 }
    }
)

Sales Types =
DATATABLE (
    "Year", STRING,
    "Region", STRING,
    "Amount", DOUBLE,
    "Mode", STRING,
    {
        { "2010", "Asia", 80000, "STORE"}, { "2010", "Asia", 25000, "ONLINE"}, { "2010", "Europe", 180000, "STORE"}, { "2010", "Europe", 125000, "ONLINE"}, { "2010", "Australia", 180000, "STORE"}, { "2010", "Australia", 125000, "ONLINE"},
        { "2011", "Asia", 80400, "STORE"}, { "2011", "Asia", 35000, "ONLINE"}, { "2011", "Europe", 185000, "STORE"}, { "2011", "Europe", 145000, "ONLINE"}, { "2011", "Australia", 175000, "STORE"}, { "2011", "Australia", 227500, "ONLINE"},
{ "2012", "Asia", 90000, "STORE"}, { "2012", "Asia", 45000, "ONLINE"}, { "2012", "Europe", 190500, "STORE"}, { "2012", "Europe", 115000, "ONLINE"}, { "2012", "Australia", 180000, "STORE"}, { "2012", "Australia", 145000, "ONLINE"},
{ "2013", "Asia", 94500, "STORE"}, { "2013", "Asia", 15000, "ONLINE"}, { "2013", "Europe", 194000, "STORE"}, { "2013", "Europe", 95000, "ONLINE"}, { "2013", "Australia", 200000, "STORE"}, { "2013", "Australia", 195000, "ONLINE"},
{ "2014", "Asia", 110000, "STORE"}, { "2014", "Asia", 225000, "ONLINE"}, { "2014", "Europe", 185000, "STORE"}, { "2014", "Europe", 120000, "ONLINE"}, { "2014", "Australia", 205000, "STORE"}, { "2014", "Australia", 225000, "ONLINE"}
    }
)

Understanding Measures in Power BI

Measures are numbers created to create graphs. Power BI calculates and returns values according to the types of aggregation we choose for the measure. We can also create our own measures to perform complex or specific calculations.

You can create your own measures with the Data Analysis Expressions (DAX) formula language. DAX formulas are similar to Excel formulas.

In the below sample I created a new measure as 'Gross Profit'

Click on the table which you intend to create a measure, and select 'New measure'

Define the formula on the newly created measure. Note that you get IntelliSense to assist you with the formula creation.

Now you can create a graph for the 'gross Profit' by location using the created measure. Drag and drop the two related columns to the reports page

An Introduction to Power BI

Power BI software has a Desktop application, a web application and a mobile version. First il give an intro on the Desktop version, then will publish whats created using the desktop to the web app.

For data import you have many options. Excel and SQL data sources are mainly used by businesses.

If you choose SQL Server, then you will have to provide server details and authentication parameters. Also there are two data connectivity modes. They are Direct & Import. If you choose import the copy of the data source will be stored at Power BI, else it will directly query from db as the name implies.

The panes
In the Reports view there are two panes, namely Visualization & Fields pane. The fields pane shows the table and colum details associated with the Power BI project. So when you import from a data source the table information will be visible there. You can use the visualization pane to showcase the information in your table in chart formats and etc..

Views
There are three main views. They are Report, Data & Relationships. You can use each view update the data set. The relationship view allows you to add relationships between the data tables.

Once you are done doing the visualizations hit Publish button in the Home tabs menu. Then the project gets published to the web.

In the web site you can generate quick insights for the project. Click on the three dots which appear on your data set (in this example it's 'Sales by country'). then Power BI starts generating the insights. The result will be something similar to below.