Data Visualization with PowerBI
In this data age, the ability to extract value from data is a highly sought after by both individuals and organizations. It takes hard technical skills to manage the large datasets and to extract insights from the data, but it eventually comes to naught unless the insights can be clearly and quickly communicated to the intended audience. Data visualization provides a graphical representation of the data to communicate key insights quickly and effectively; even to those who are less numerically inclined. To this end, data visualization has become an indispensable part of the analytics toolkit. PowerBI was cited one of the top data visualization tools in 2019 and 2020; being a product of Microsoft, it offers interoperability with their range of software, making PowerBI skills indispensable as well.
About the workshop
This 1 Day workshop aims to provide a broad but practical overview of the analytics value chain; with a focus on data visualization and role that it plays in it. The workshop will also provide an introduction to PowerBI; from which delegates will apply data visualization concepts using the software to explore large data sets, assemble data visualizations and build interactive dashboards. Delegates will also be exposed to other PowerBI resources available in the market.
Appreciate the impact that data visualization has on the realization of value in analytics; particularly in today’s data driven world
Understand the key principles and elements of building an impactful data visual
Understand the basics of PowerBI navigation
Gain practical experience in creating key features of PowerBI functionality such as charts, timelines and maps
Develop an interactive dashboard and learn to gain insights from it
Who should attend
Analysts or Professionals with Analytics responsibilities, who are looking to be more effective in presenting complex data to audiences
Managers responsible for managing and supervising a team of analysts
All other professionals with a keen interest in developing strong foundations in data analytics
Some prior knowledge in MS Excel and analytics could be helpful, but not required