What is Query Editor?Query Editor is an interface for Query transformation in Power BI. It allows you to seamlessly prepare data for BI tasks. Microsoft Power BI is software as a service (Saas) platform which consists of:
A new window opens showing the interface for Microsoft Power BI Query Editor.
Index columns can be created inside Power BI’s Query Editor. Index columns serve as Row Counter for your data.
To create an index column:
1.Select the Sales Table from the Queries Pane.
2.Click on the Add Column in the Ribbon Menu.
3.Click on the arrow next to Index Column in the General Section and a drop-down menu appears.
4. Click on From 0.
You can create index column using three options:
If you select this option, an index column staring from 0 as the initial index is created.
If you select this option, an index column staring from 1 as the initial index is created.
If you select this option, a pop-up menu appears where you can select the value for your first index and the increment that you want on each step.
In Microsoft Power BI, Date columns are created to assign date value to each row entry. Date calculations can be done on daily, weekly, monthly, quarter or yearly basis.
To create a date column:
1.Click on the Sales Table in the Queries Pane on the left.
2.Click on the Trans Date column.
3.Click on Add Column tab in the Ribbon Menu.
4.From the From Date and Time section, click on Date.
5.Now click on Year.
A selection list appears.
6.Click on Year.
A new column containing the year of the date vales in the Trans Date column appears at the end of canvas.
A pop-up menu appears.
1.In the section for New Column name, type “Priority”.
2.From the drop-down menu under the Column Name select “Urgent”.
3.In the section for Value, type “YES”
4.In the section for Output type “1”
5.In the section for Else type “2”.
A new column is created. This column assigns priority for each sales transaction based its urgency status.
Data Transformation is a process in which raw data is Transformed into a format that is suitable for fast and precise data processing and for efficient reporting. Data Transformation involves a wide range of operations such as identifying data sources and data types, cleaning data by removing errors and duplicates along with enriching data and performing aggregations. Data transformation also involves creating columns to bridge the missing information gap. In this blog post, a step by step guide to create index, date and conditional columns has been discussed.
Are you a data analyst and want to learn more about Power BI? Why not sign up for Power BI training in Australia. We provide our services in the following regions
- Power BI Training in Sydney
- Power BI Training in Melbourne
- Power BI Training in Brisbane
- Power BI Training in Canberra