INT-2580 Big Data Analytics and Modeling

Credits: 4
In this course, students gain in-depth knowledge of the methods, tools, and applications necessary for extracting, analyzing, and modeling big data to solve real-world problems. The course covers the complete data pipeline, encompassing data ingestion, cleaning, processing, modeling, and visualization. Students primarily utilize Microsoft and Azure Data services to learn how to interactively explore data, implement ingestion techniques, perform data transformations, and ensure data security. By the end of the course, students are proficient in building and deploying batch and real-time analytical solutions, as well as modeling, visualizing, and analyzing data with Power BI while adhering to industry-standard security standards and policies.

This course helps students prepare for the Microsoft Power BI Data Analyst certification exam (PL-300) and the Data Engineering on Microsoft Azure certification exam (DP-203). Students will have to study beyond this course to adequately prepare the Microsoft Power BI Data Analyst certification exam (PL-300) and the Data Engineering on Microsoft Azure certification exam (DP-203).

Prerequisite(s): INT-2180 and INT-2280 .

Course Outcomes

Determine appropriate compute and storage options in Azure for different data engineering workloads.
Apply data exploration techniques to uncover patterns, correlations, and insightful relationships within big data.
Employ data cleaning and transformation methodologies using Azure Databricks to ensure data quality and usability.
Utilize Azure Data services to load, transform, and optimize data for efficient storage and retrieval in the Data Warehouse.
Create visually compelling and informative reports for data analysis using relevant tools and techniques.
Apply advanced analytics techniques, such as predictive modeling and text and sentiment analysis, to gain deeper insights from data.
Implement comprehensive security measures to protect data at rest and in transit within Azure Synapse Analytics.
Develop real-time stream processing solutions using Azure Databricks to process and analyze data as it arrives.
Design data models to improve query performance and scalability in data analytics scenarios.
Demonstrate effective collaboration and communication skills in managing and sharing report assets with stakeholders.