Training on Data Manipulation with R and Visualization with Power BI

It has been said that 80% of data analysis is spent on the process of cleaning and preparing the data. In this course we introduce some relatively-new additions to the R programming language; dplyr and ggplot2. In combination these provide a powerful toolkit to make the process of manipulating and visualizing data easy and intuitive. Further Microsoft Power BI is a business intelligence technology from Microsoft that gathers and processes your data, analyzes and provides data driven insights that enables managers, business analysts and key decision makers to make informed decisions real time. It allows one to ask questions and get answers about their data. Users of Power BI are able to create interactive dashboards and insights by self-interacting with the technology. 

Duration

10 Days

Who Should Attend

• Data analysts and monitoring officers

• Business intelligence professionals

• Researchers and statisticians

• Anyone interested in integrating R with Power BI for analysis and reporting

Organizational Impact

• Improve data handling and visualization capabilities within the organization
• Enhance decision-making through advanced analytics and reporting
• Streamline data management and reporting processes

Personal Impact

• Master advanced data manipulation techniques using R
• Develop skills to create publication-ready graphics with ggplot2
• Gain expertise in Power BI for data transformation and visualization

By the end of the course, participants will be able to:

• Import, clean, and manipulate datasets using R

• Transform and prepare data for visualization

• Integrate R outputs into Power BI

• Design and publish dynamic dashboards in Power BI

• Present analytical results in a clear and interactive format

Module 1: Introduction to Data Manipulation Using R

• Overview of R for data manipulation
• Basics of tidy datasets
• Introduction to dplyr for data manipulation
• Case Study: Manipulate a real-world dataset to clean and prepare it for analysis using dplyr.

Module 2: Advanced Data Manipulation in R

• Subsetting and filtering datasets using dplyr
• Joining datasets with dplyr
• Producing summary statistics
• Case Study: Perform advanced data manipulation on a complex dataset, including joining multiple datasets and generating summary statistics.

Module 3: Data Visualization with ggplot2

• Introduction to ggplot2 and the grammar of graphics
• Creating basic plots: bar, pie, scatter
• Producing publication-ready graphics
• Case Study: Develop a set of visualizations for a dataset to present findings in a professional report.

Module 4: Introduction to Power BI

• Overview of Power BI components and features
• Power BI workflow and setup
• Connecting to various data sources (Excel, online sources, SQL)
• Case Study: Set up a Power BI workspace and connect it to a dataset from multiple sources to prepare for analysis.

Module 5: Data Transformation in Power BI (Power Query)

• Data management and cleaning techniques
• Using Power Query for data transformation
• Adding new columns, filtering, and parameter settings
• Case Study: Transform and clean a raw dataset using Power Query, including adding calculated columns and filtering data.

Module 6: Data Modeling in Power BI

• Creating table relationships (one-to-one, one-to-many)
• Introduction to Data Analysis Expressions (DAX)
• Measures and calculated columns
• Case Study: Build a data model for a sales dataset, including creating relationships and DAX measures to analyze sales performance.

Module 7: Visualization and Charts in Power BI

• Creating various charts: bar, line, pie, waterfall
• Using slicers, gauges, and KPIs
• Advanced visualizations: maps, tree maps, and ArcGIS
• Case Study: Develop a set of interactive visualizations and dashboards to analyze and present sales data with advanced visual elements.

Module 8: Building and Sharing Dashboards in Power BI

• Creating and modifying dashboards
• Sharing dashboards with stakeholders
• Using Power Q&A and insights for interactive reporting
• Case Study: Build a comprehensive dashboard for a business unit, share it with stakeholders, and set up interactive Q&A features.

Module 9: Data Security and Refresh in Power BI

• Configuring row-level security and user roles
• Types of data refresh and configuration
• Managing data refresh and data management gateways
• Case Study: Implement row-level security for a Power BI report and set up a data refresh schedule to ensure up-to-date information.

Module 10: Power BI for Mobile and Integration with Excel

• Configuring Power BI for mobile devices
• Visualizing and commenting on reports via Power BI Mobile
• Using Excel Power Query and Power Pivot with Power BI
• Case Study: Configure a Power BI report for mobile access, and integrate it with Excel for additional data analysis and reporting.