Business Intelligence and Data Analytics using R
Business Intelligence and Data Analytics using R
Published 7/2025
Duration: 4h 17m | .MP4 1280x720 30 fps(r) | AAC, 44100 Hz, 2ch | 1.95 GB
Genre: eLearning | Language: English
Published 7/2025
Duration: 4h 17m | .MP4 1280x720 30 fps(r) | AAC, 44100 Hz, 2ch | 1.95 GB
Genre: eLearning | Language: English
Transforming Raw Data into Actionable Insights with R – A Practical Approach to Business Intelligence and Analytics
What you'll learn
- Explain the concept of Business Intelligence (BI) and describe its historical evolution, key milestones, and the technological advancements
- Demonstrate understanding of data preprocessing techniques using R by identifying, cleaning, transforming, and preparing raw business data for analysis
- Apply supervised learning techniques to build predictive models with R using labeled business data, and evaluate model performance
- Utilize unsupervised learning techniques such as clustering using R to uncover hidden patterns, groupings, and insights from unlabeled business data
- Create and interpret a variety of data visualizations using R to effectively communicate business insights and support data-driven decision-making.
Requirements
- basic programming knowledge
Description
Welcome to the courseBusiness Intelligence and Data Analytics using R !
This course provides a thorough introduction to the key concepts and techniques of Business Intelligence (BI) and Data Analytics using the R programming language. Aimed at learners from both technical and non-technical backgrounds, the course guides participants through the entire data analytics workflow—from data collection and preprocessing to modeling and visualization.
Learners will begin by exploring data cleaning and transformation methods, essential for ensuring high-quality input for analysis. The course then introduces supervised and unsupervised learning techniques, enabling participants to build predictive models and uncover hidden patterns in business data. Special emphasis is placed on practical, hands-on application of R to perform exploratory data analysis (EDA), create interactive dashboards, and generate compelling visualizations.
Participants will gain valuable insights into how data can be used to solve business problems, identify trends, and support strategic decision-making. By working with real-world datasets and business scenarios, learners will develop confidence in applying data-driven approaches to complex challenges.
By the end of the course, students will have the skills to process, analyze, and present data effectively, making them well-prepared to contribute to BI and analytics initiatives in any organizational setting.
Wish you a happy learning…
Who this course is for:
- Beginners to data analytics, business people
More Info