Business Intelligence Automation with R Programming: Driving Smarter Decisions Training Course

Introduction

R programming has become one of the most powerful tools for data analytics, statistical modeling, and automation in Business Intelligence (BI). With its extensive ecosystem of libraries and packages, R enables professionals to automate BI workflows, streamline reporting, and generate actionable insights quickly and efficiently. Organizations leveraging R for BI automation gain competitive advantages by reducing manual tasks, improving accuracy, and accelerating data-driven decision-making.

This training course is designed to help professionals unlock the potential of R programming for BI automation. Through a combination of practical exercises and real-world examples, participants will learn how to build automated data pipelines, perform advanced analytics, and deliver interactive BI reports with minimal effort. The course emphasizes hands-on learning to ensure learners can directly apply their skills in automating business intelligence tasks.

Duration: 10 Days

Target Audience

  • Business intelligence analysts and developers
  • Data scientists and R programmers
  • IT and BI project managers
  • Business managers and strategists
  • Professionals seeking to automate BI processes

10 Objectives

  1. Understand the role of R programming in BI automation
  2. Learn to clean, transform, and prepare data using R
  3. Automate BI workflows with R scripts and packages
  4. Develop advanced visualizations and dashboards in R
  5. Apply statistical and predictive models for BI insights
  6. Integrate R with databases and BI platforms
  7. Automate reporting and distribution of BI insights
  8. Ensure data governance and reproducibility in BI automation
  9. Explore real-world use cases of BI automation with R
  10. Complete a capstone project showcasing BI automation skills

15 Course Modules

Module 1: Introduction to R for BI Automation

  • Overview of R programming in BI
  • Installing R and RStudio
  • Key packages for BI automation
  • R scripts vs. R Markdown
  • Case studies of BI with R

Module 2: Data Import and Management in R

  • Reading data from multiple sources
  • Importing CSV, Excel, and database files
  • Handling large datasets
  • Cleaning and organizing data
  • Automating import workflows

Module 3: Data Cleaning and Transformation

  • Handling missing values
  • Data type conversions
  • Filtering and aggregating data
  • Reshaping datasets
  • Automating transformations

Module 4: Exploratory Data Analysis (EDA) in R

  • Descriptive statistics with R
  • Data distributions and patterns
  • Correlation and covariance analysis
  • Outlier detection
  • Automating EDA workflows

Module 5: Data Visualization with ggplot2

  • Introduction to ggplot2 syntax
  • Building bar, line, and scatter plots
  • Customizing plots for BI reporting
  • Interactive visuals with plotly
  • Automating visual generation

Module 6: BI Dashboards in R

  • Introduction to Shiny dashboards
  • Creating interactive visualizations
  • Customizing layouts and themes
  • Connecting dashboards to live data
  • Automating dashboard updates

Module 7: Automating BI Workflows with R

  • Writing reusable R scripts
  • Scheduling R tasks
  • Automating ETL with R
  • Automating data validation
  • Workflow optimization

Module 8: Reporting Automation with R Markdown

  • Introduction to R Markdown reports
  • Creating automated reports
  • Exporting reports to PDF, Word, and HTML
  • Customizing templates
  • Automating report delivery

Module 9: Advanced Analytics in R

  • Statistical models for BI
  • Regression and classification techniques
  • Clustering and segmentation
  • Forecasting with time series
  • Automating predictive models

Module 10: Time Series Analysis for BI

  • Working with time-based data
  • Smoothing and decomposition methods
  • Trend and seasonality detection
  • Forecasting with ARIMA models
  • Automating time series workflows

Module 11: R Integration with Databases

  • Connecting R to SQL databases
  • Querying databases with R
  • Automating data extraction from databases
  • Writing back to databases
  • Best practices for integration

Module 12: R and Cloud BI Platforms

  • Using R with Power BI
  • Integrating R with Tableau
  • R scripts for cloud BI solutions
  • Automating updates in cloud BI platforms
  • Case studies of R-cloud BI integration

Module 13: BI Automation Case Studies with R

  • Automating financial reporting
  • Customer segmentation analysis
  • Marketing campaign optimization
  • Supply chain analytics
  • Risk and fraud detection

Module 14: Ensuring Governance and Reproducibility

  • Version control with Git
  • Documenting BI workflows in R
  • Testing and validation of scripts
  • Ensuring compliance in BI automation
  • Reproducible research principles

CERTIFICATION

  • Upon successful completion of this training, participants will be issued with Macskills Training and Development Institute Certificate

TRAINING VENUE

  • Training will be held at Macskills Training Centre. We also tailor make the training upon request at different locations across the world.

AIRPORT PICK UP AND ACCOMMODATION

  • Airport Pick Up is provided by the institute. Accommodation is arranged upon request

TERMS OF PAYMENT

Payment should be made to Macskills Development Institute bank account before the start of the training and receipts sent to info@macskillsdevelopment.com

For More Details call: +254-114-087-180

 

 

Business Intelligence Automation With R Programming: Driving Smarter Decisions Training Course in Viet Nam
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