How Analysts Translate Messy Data, DAX and Dashboard into Action using Power BI

Power BI makes raw data meaningful. This is achieved through visualization like charts and graphs. Data cleaning is done using the Power query which cleans and combines data from various sources

Data Cleaning in Power BI

Some of the basic tasks include:

.Removing duplicates

.Handling missing values

.Data type conversation

.Replace values

DAX - Data Analysis Expressions

DAX is a set of functions for calculations.

After cleaning your data, you can now perform your calculations.

You can use your formulas to calculate tables, calculations will add a table or calculate columns, calculations will add a column.

Common DAX functions

.Simple calculations like COUNT, SUM, AVERAGE, MIN, MAX

.IF, this returns a different value whether true or false

.DATEDDIFF, gives difference between two dates in days, months, years

.SUMX,AVERAGEX,COUNTX

Row context and Filter context in DAX

Row context

Operates on row to row basis. Examples of calculations include SUMX, AVERAGEX

Filter context

Filter Context refers to the set of filters applied to the data model before calculations.

Example is a function like CALCULATE

Dashboards

This is a page that tells a story through visuals. It provides the highlights just with a look of it. You get a general view of the output without delving so much into it which can be used in decision making.

Power BI is key when it comes to decision making. It assists businesses make sense of data at hand and give them a leverage. It answers what and why questions and gets you thinking of the next thing to do.