Advanced Guide To Data Analytics
Master advanced data analytics with predictive modeling, machine learning basics, and real-world case studies for professional growth.
Pre-requisite Program(s)
The following program(s) are pre-requisite to taking this program:
RWL Code
BLP-6270HSO0944
Category
Data Analytics
Program Type
Paid Program
Program Fee
₦45,000.00 (Preoder)
Publish Date
26/04/2025
Language
7 Lessons |
48hrs:45min
1
This introductory lesson establishes Power BI as a comprehensive business intelligence tool and outlines the complete data analysis workflow. It covers the installation process and navigation of Power BI Desktop, teaching students how to connect to various data sources including Excel, CSV, web-based data, and SQL databases. The lesson provides a thorough exploration of the Power BI interface, explaining the distinct purposes of Report, Data, and Model views, and concludes with basic data loading procedures and an overview of the field pane functionality.
This lesson focuses on data preparation techniques using Power BI's Power Query Editor for ensuring data quality and usability. It covers fundamental data cleaning operations including row removal, data type conversion, and column renaming for better organization. The lesson teaches column manipulation techniques such as splitting and merging, value replacement methods, and strategies for handling missing data. It concludes with advanced column creation techniques including conditional columns and custom columns for enhanced data analysis capabilities.
This lesson introduces the critical concepts of data modeling within Power BI, covering the fundamental understanding of tables, relationships, and cardinality principles. It teaches the creation and management of relationships between tables for integrated analysis, introduces the Star Schema concept and data modeling best practices for optimal performance. The lesson covers model optimization techniques including field hiding, folder organization, and performance enhancement strategies, and concludes with effective use of the "Manage Relationships" feature and diagram view for relationship visualization.
This lesson introduces DAX (Data Analysis Expressions) as Power BI's formula language, explaining its differences from traditional Excel formulas and its specific applications in business intelligence contexts. It covers the creation of calculated columns and measures for custom analytics, teaches basic DAX functions including SUM, COUNTROWS, and DISTINCTCOUNT for fundamental calculations, and introduces the crucial concepts of row context versus filter context that govern how DAX calculations behave in different scenarios.
This advanced lesson explores sophisticated DAX techniques for complex analytical scenarios, focusing on the CALCULATE function for modifying filter contexts and advanced filtering functions like FILTER, ALL, and VALUES. It introduces time intelligence functions including YTD, MTD, and SAMEPERIODLASTYEAR for temporal analysis, covers conditional logic implementation using SWITCH and IF statements, and teaches the creation of dynamic measures using SELECTEDVALUE for interactive analytics that respond to user selections.
This lesson focuses on creating compelling and interactive data visualizations within Power BI, covering the selection of appropriate chart types including bar charts, line graphs, maps, and cards based on data characteristics and analytical objectives. It teaches the implementation of interactive features such as slicers, filters, and drill-through pages for enhanced user engagement, explores data organization techniques including grouping, binning, and hierarchies for better visual representation, covers visual customization options including themes, tooltips, and formatting for professional presentation, and introduces storytelling techniques using bookmarks and buttons for guided analytical narratives.
This capstone lesson covers the deployment and sharing aspects of Power BI analytics, introducing the Power BI Service as a cloud-based platform for report distribution and collaboration. It teaches the process of publishing reports from Power BI Desktop to the Service, covers dashboard creation and sharing mechanisms for stakeholder access, explores automated data refresh setup and gateway management for maintaining current information, explains access control through workspaces and role-based permissions for secure collaboration, and concludes with a comprehensive recap of the complete workflow from initial data source connection to final published report.