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Data Visualization techniques using Power BI
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Course Title:

Data Visualization techniques using Power BI



Course Description:

This course offers a comprehensive introduction and covers essential to develop their skills in Data Pre-processing, Visualization and Analysis using Microsoft Power BI. Introduction to Power BI, GUI of Power BI, Features of Power BI., Building blocks of power BI, connecting to data sources, getting data from excel files, using power BI desktop. Multiple data sources in Power BI, Multivariate displays, Geospatial display Dashboards, interactive and animated displays, building dashboards, creating reports.



Course instructional level:


Intermediate

Course Duration:


3 Month/6 Month
Hours: 45/60/75

Course coordinator:


Dr. Mahendra M. Gupta

Course coordinator's profile(s):


Dr. Mahendra M. Gupta, Director School of Engineering Sciences and has 30 years of experience in Teaching courses specially related to Industrial Engineering, Power BI and Tableau. His areas of interest are modeling and simulation, Human factors in Engineering. He is also actively involved in research and has several papers and patents in her credits.

Course Contents:



Module/Topic name Sub-topic Duration
1. This module provides a comprehensive introduction to Power BI and data visualizations. 5 Hours
2. Getting started with Power BI, various chart types, Power BI interface overview, comparison of reports and dashboards, and building a basic Power BI report. 15 Hours
3. Introduction to data display and visualization design principles 20 Hours
4. Set up data sources and explore the different data source capabilities in Power BI. Gain an understanding of the load portion of the ETL process and practice data profiling. 20 Hours
5. Creating dashboards and stories with available data sources on web 30 Hours


Course Outcomes:


At the end of this course the student will demonstrate ability to
  1. Understand advanced features for data visualization.
  2. Connect Microsoft Power BI to multiple data sources, process and transform data to prepare it for reporting and visualization.
  3. Draw insights from data dashboards and visualizations that allows understanding and help a business make critical decisions.