Basic Data Analytics and Visualization for International
This training course will teach participants how to implement descriptive and basic predictive analytics tools and techniques on various types of data (sales and marketing, customers, operations, finance, and human resources). Using open-source software, participants will learn how to process and mine their data in order to generate powerful actionable insights that impact business outcomes. Even without any technical background on statistics, but with the aid of user-friendly tools and software, participants will be able to process data, run basic descriptive and predictive analytics, and generate powerful visualizations and dashboards.
At the end of the training course, participants should be able to:
Understand the process and outcomes of descriptive and predictive analytics;
Learn the core concepts of analytics and how it applies in the context of business intelligence;
Determine the appropriate analytics tool for any given business question to be addressed;
Run the analytics tools and techniques using an open-source statistical software --- Jamovi and Power BI;
Accurately interpret results of the analysis and generate insights;
Create functional data dashboards
WHO SHOULD JOIN?
Employees who have the responsibility and the need to transform business data into critical business decision insights
Employees who want to acquire or upgrade their data analytics and data visualization competencies
Data analysts from any business unit that generates, processes, and analyzes quantitative data
Note: No prior statistical or programming knowledge is required. This is designed for learners with any background.
Introduction to Data Analytics
Data, Variables, and Measurements
Data Cleaning and Structuring
Basic Tools and Techniques for Descriptive and Predictive Analytics
Key Drivers Analysis
Analysis of Group Differences
Tools and Techniques for Predictive Analytics
Data visualization and Insight Extraction using Power BI
Transforming data into dashboards
Dr. Marshall Valencia