This module introduces the foundational concepts of big data, including the differences between data and information, the three Vs of big data, and the critical role data plays in business decision-making and strategy. Learners will explore various data types, sources, and best practices for leveraging data insights in a rapidly evolving digital landscape.

This module introduces the foundational concepts of data lakes, including their purpose in centralized data management and their ability to handle diverse data types. Learners will explore the scalability of data lakes and understand how they accommodate structured, semi-structured, and unstructured data. By the end, participants will be able to distinguish data lakes from other data storage solutions and appreciate their flexibility.

This module introduces foundational concepts in data science, including data collection, mathematical modeling, and essential tools like SQL and Excel. Learners will explore database design, normalization, and practical techniques for analyzing and visualizing data to support informed decision-making.

This module guides learners through the process of crafting effective data visualizations tailored to specific audiences. You will discover how to select the most suitable chart types, design with audience needs in mind, and use storytelling techniques to communicate insights clearly and persuasively.

This module introduces the essential features and terminology of Power BI, guiding learners through the differences between desktop and online versions, and the fundamentals of data interpretation. Learners will also explore collaborative workspaces and the creation of visually compelling dashboards to effectively communicate data insights.

This module introduces learners to the core features of Power BI, including data ingestion, modeling, and visualization using Power BI Desktop, as well as sharing and collaboration through Power BI Services. Learners will explore how to work with different data sources, perform basic data analysis, and create interactive dashboards for effective data presentation. By the end, participants will understand how to leverage Power BI for both individual and team-based business intelligence tasks.

This module guides learners through the essential steps of preparing data for visualization in Power BI Desktop. You will explore connecting to various data sources, managing data settings, and performing data cleansing and transformation to ensure high-quality, reliable datasets for analysis.

This module guides learners through the process of detecting and correcting data inconsistencies, transforming column data types, and optimizing queries for efficient data loading in Power BI. Participants will gain practical skills in preparing raw data for analysis and visualization using Power Query tools.

This module guides learners through the process of building and refining data models in Power BI Desktop, including importing data, managing tables, and preparing models for deployment. Learners will gain hands-on experience with different data import methods, table management, and modifying data within various model types. By the end, participants will be equipped to optimize data models for effective use in Power BI Services.

This module introduces the fundamentals of creating and customizing visualizations in Power BI, including how to select appropriate chart types, filter data, and use indicators for effective data analysis. Learners will gain practical skills in presenting and interpreting data trends and relationships using various visualization tools.

This module guides learners through configuring advanced Power BI visualizations, integrating AI-driven Q&A features, and designing real-time dashboards for effective data monitoring. Participants will also learn how to export reports for sharing insights outside of Power BI Services. By the end, learners will be equipped to create interactive, insightful, and shareable data reports.

This module guides learners through effective collaboration using Power BI Services, including workspace management, secure data sharing, and monitoring user engagement with reports and dashboards. Participants will also learn to troubleshoot data lineage in complex business intelligence projects.