Learn and Practice Power BI Desktop

Learn and practice connecting to a csv file

Learn to perform visualization on a csv file

Learn how to connect to the hidden sheets in an excel file.

Learn how to connect to a file containing blank columns

How to read a password protected file?

Learn to upload and use data from excel files

Practice visualization using excel data

Learn to connect to a folder location and read all the files from that folder

Learn to load and transform multiple files and folder from a folder location. Download the dataset from the resources for this excercise

Learn to connect to github and download data into Power BI

Lets connect to multiple websites and create visualization by creating relationship between different tables. We use data from following sources:

•GITHUB: https://github.com/swapnilsaurav/Dataset

Websites:

•https://www.currency-converter.org.uk/currency-exchange-rates.html

•https://www.sport-histoire.fr/en/Geography/Currencies_countries_of_the_world.php

Learn to connect to SQL Server and access data from the SQL Server database

Lets connect to SQL Server and look at the sample database. We will explore the tables that we need to connect from Power BI. We will also learn how to create database diagram.

This video will show how to read data from a database using SQL query

Data visualization refers to the graphical representation of data in order to present complex information in a visual and easily understandable format. It involves the use of charts, graphs, maps, and other visual tools to present patterns, trends, and relationships within data sets. Data visualization is widely used in various fields such as business, science, finance, and journalism to explore data, identify insights, and communicate findings effectively.

In this video, we are going to perform following steps:

Creating a complete dashboard in Power BI involves the following steps:

1. Data import: Start by importing the necessary data into Power BI. This can be done by connecting to various data sources such as Excel spreadsheets, databases, or cloud services. Ensure that the data is clean, organized, and formatted correctly.

2. Data modeling: Once the data is imported, create relationships between the different tables if required. Define measures, calculations, and hierarchies based on the business requirements. This step is crucial for data analysis and visualization.

3. Visualization design: Choose appropriate visualizations to represent the data in a meaningful and intuitive way. Power BI offers a wide range of visualizations such as charts, graphs, maps, and tables. Customize these visualizations by adding titles, formatting options, and tooltips to enhance the overall design.

4. Dashboard layout: Arrange the visualizations on a canvas to create a visually appealing and logical layout. Consider the story you want to tell with the data and place the visuals strategically to convey that story effectively. Use containers, grids, and layers to organize the different elements on the dashboard.

5. Interactivity and filtering: Enable interactive features like slicers, filters, and drill-through actions to allow users to explore the data further. This helps in focusing on specific data subsets or analyzing trends across different dimensions. Create interactivity between different visualizations to facilitate data exploration.

6. Dashboard navigation: Create a navigation structure within the dashboard to help users move between different pages or sections smoothly. Use buttons, bookmarks, or drill-through actions to link related visuals or to provide additional context to the data.

Time series and Anomaly detection in Power BI

Load the HR analytics