BI 348 - Big Data Business Analytics with Microsoft Power Tools

5 Credits

Students will use Microsoft’s new Power Tools (Excel Power Pivot, Power Query and Power BI Desktop) to convert real world large data sets into useful information for business decision making. In addition to learning some standard Excel features, students will learn, in depth, how to use the computer languages DAX and M Code to clean, transform and load data, as well as how to convert the loaded data into useful information for reporting, visualizing, analytics and dashboarding.

Pre-requisite(s) BUSN 210 min 2.0 (or MATH& 146) and BUSN 218 min 2.0
Program Admission Required Yes Admitted Program BAS - BUSN
Course Note Acceptance to BAS in Applied Management required.
FeesCF

Quarters Typically Offered
Spring Evening, Online

Designed to Serve Students pursuing the BAS in Global Trade & Logistics
Active Date 20220308T16:47:31

Grading Basis Decimal Grade
Class Limit 24
Contact Hours: Lecture 55
Total Contact Hours 55
Degree Distributions:
ProfTech Course Yes
Restricted Elective Yes
Course Outline

Overview of all tools and concepts in the class.
Define Data Analysis and Business Intelligence.
Define Data Analysis, Business Intelligence and Data Warehousing Terms and concepts.
Use Excel Spreadsheet Formulas and Functions for ETL and creating information solutions.
Use Standard PivotTables for creating information solutions.
Use Power Query to extract, transform and load data to the Excel Worksheet, PowerPivot Data Model and Power BI Desktop Data Model.
Learn to write M Code to extract, transform and load data.
Learn about how to build efficient and effective Data Models for both Excel Power Pivot and Power BI Desktop using Power Query and M Code.
Use Excel Power Pivot for creating information solutions.
Use Power BI Desktop for creating information solutions.
Learn about how the Columnar Database compacts and stores data for a Data Model.
Learn to write basic to advanced DAX code to create business calculations using calculated columns, queries and measures.
Build efficient and effective dashboards that contain refreshable and sharable reports, visualizations and analytics.
Build complete Data Analysis and Business Intelligence solutions from beginning to end using case studies.

Student Learning Outcomes
Convert unorganized raw big data sets into useful information (reports, visualizations and analytics) for business decision making, providing data driven insights.

Use analysis and visualization tools (such as Excel Power Pivot, Power Query and Power BI Desktop) and computer languages (DAX and M Code) to create useful information solutions from large data sets.

Create efficient and effective data models and business-related measures by ETL (extract, transform and load data) to build refreshable useful information solutions.

Efficiently and effectively construct reports, visualizations and dashboards for business decision makers.

Create Excel worksheet formula solutions for linear programming, simulations, and other analytic goals.