Marketing & Business /Marketing
Business Analytics: Driving Data-Driven Decisions
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I am a seasoned HR professional with over 15 years of experience in developing and implementing strategic HR initiatives for medium and large companies worldwide.
With a strong background in organizational development, talent management, and change leadership, I am passionate about empowering HR professionals to drive positive change and achieve business objectives through strategic HR planning.
My teaching approach is interactive and practical, combining theoretical concepts with hands-on activities, case studies, and group discussions. My goal is to equip participants with the tools, strategies, and confidence needed to excel in their roles and make a meaningful impact within their organizations.
Skills you will gain
Mastery of business analytics concepts, tools, and techniques.
Skills in data collection, preprocessing, visualization, and predictive modeling.
Insights into data-driven decision-making and business strategy.
Hands-on experience with analytics tools and real-world data projects.
Certificate of Completion from Peter Strom in Business Analytics.
Course description
Welcome to the "Business Analytics: Driving Data-Driven Decisions" course! In this course, you will embark on a journey to unlock the power of data analytics and harness it to drive strategic business decisions. Led by analytics expert Peter Strom, you will delve into key concepts, tools, and techniques essential for business analytics success.
Course content
Section 1.Introduction to Business Analytics
10mImportance of Business Analytics in Decision-Making
Types of Business Analytics (Descriptive, Predictive, Prescriptive)
Business Analytics Tools and Technologies
Section 2.Data Visualization and Storytelling
2h 7mVisualizing Data with Charts, Graphs, and Dashboards
Storytelling with Data and Effective Data Communication
Interactive Data Visualization Tools (Tableau, Power BI)
Test book
2h 0m
Section 3.Predictive Modeling and Forecasting
5h 14mIntroduction to Predictive Analytics
Regression Analysis and Time Series Forecasting
Machine Learning for Predictive Modeling
Student book
5h 0m
Section 4.Advanced Analytics Techniques
17mText Analytics and Sentiment Analysis
Customer Segmentation and Behavioral Analytics
Data Mining and Pattern Recognition
Requirements
Basic understanding of business concepts and terminology.
Familiarity with data analysis tools (e.g., Microsoft Excel) is recommended.
Access to a computer with internet connectivity for online learning and data analytics exercises.
Openness to learning and applying business analytics techniques in real-world scenarios.
No prior experience in data analytics or programming is required.
All levels
7h 49m
English
Video lectures
Study materials
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