Master Course in Data Visualization & Data Warehousing (101)

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COURSE AUTHOR –
Dr. José Prabhu J

Last Updated on July 4, 2024 by GeeksGod

Course : Master Course in Data Visualization & Data Warehousing (101)

Master Course in Data Visualization & Data Warehousing 2.0

This comprehensive master course delves into the advanced realms of data visualization and data warehousing, equipping participants with the skills and knowledge necessary to harness the power of data for informed decision-making and strategic insights. The course is structured into five modules, each focusing on essential aspects of data visualization and data warehousing, supplemented with practical exercises and real-world case studies.

In the first module, “Foundations of Data Visualization,” participants will explore the fundamental principles and best practices of data visualization, mastering various visualization techniques and understanding the importance of storytelling through data. They will also gain hands-on experience with popular visualization tools and technologies.

The second module, “Advanced Data Visualization Techniques,” delves deeper into interactive and geospatial visualizations, as well as techniques for visualizing time series data. Participants will learn to create engaging, interactive dashboards and effectively communicate insights derived from temporal and spatial data.

Moving on to the third module, “Data Warehousing Fundamentals,” participants will gain a comprehensive understanding of data warehousing concepts, data modeling techniques, and ETL processes. They will learn to design efficient data models and implement robust ETL processes using industry-standard tools and methodologies.

The fourth module, “Advanced Data Warehousing Techniques,” explores topics such as data quality management, big data integration, and real-time data warehousing. Participants will delve into strategies for ensuring data quality, integrating big data with traditional data warehousing solutions, and implementing real-time data processing for timely insights.

Finally, the fifth module, “Advanced Topics in Data Visualization & Data Warehousing,” covers advanced applications of data visualization in machine learning, business intelligence, and cloud-based data warehousing. Participants will learn to visualize machine learning results, leverage visual analytics for business decision-making, and explore the benefits and challenges of cloud data warehousing solutions.

By the end of this master course, participants will have acquired the skills and expertise to effectively visualize data, design and implement robust data warehousing solutions, and leverage advanced techniques to extract actionable insights from complex datasets, thereby driving informed decision-making and strategic initiatives within their organizations.

In this master course, I would like to teach the 5 major topics:

Module 1: Foundations of Data Visualization

Module 2: Advanced Data Visualization Techniques

Module 3: Data Warehousing Fundamentals

Module 4: Advanced Data Warehousing Techniques

Module 5: Advanced Topics in Data Visualization & Data Warehousing

Enroll now and learn today !

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What you will learn :

1. Participants will demonstrate proficiency in creating various types of data visualizations using industry-standard tools and technologies.
2. Participants will apply principles of effective storytelling through data visualization to communicate insights and drive decision-making.
3. Participants will design and implement efficient data models for data warehousing using dimensional and normalized modeling techniques.
4. Participants will demonstrate competency in conducting ETL processes to extract, transform, and load data into data warehousing environments.
5. Participants will analyze and interpret temporal and geospatial patterns in data through advanced visualization techniques.
6. Participants will integrate big data with traditional data warehousing solutions to effectively manage and analyze large datasets.
7. Participants will evaluate and implement real-time data processing techniques for timely insights and decision-making.
8. Participants will assess and address data quality issues within data warehousing environments using governance frameworks and management techniques.
9. Participants will apply advanced data visualization techniques to analyze machine learning results and support AI-driven insights.
10. Participants will evaluate the benefits and challenges of cloud-based data warehousing solutions and implement best practices for migration and management.