Data Analytics for Business, Accounting and Finance (STAT 411)

OVERVIEW

1. COURSE DESCRIPTION

The course covers the main topics in data analytics such as data extraction, transformation,  reporting and visualization. The course also provides insights on how cloud computing, big data are impacting the world of data analytics and data driven decision making.

2. REASON FOR THE COURSE

Technology has become an integral part of all businesses. With the evolution of cloud computing, and reduction in computing and storage costs, businesses are relying more and more on data-driven decision making. Globalization further increases the need for all organizations to use data to make decisions. Data Analytics for Business, Accounting and Finance course enables students to have a strong foundation in data-driven decision making and become an effective business leader.  

This course aims to provide students with an understanding of data analytic approaches, covering both data analysis and data visualization. This course will enable students to obtain the knowledge of data analytics, big data analytics and develop skills for data analysis and data visualization. This course has an extensive hands-on activity focus and thus students will be able to apply the knowledge and skills on real life case studies using tools such as Excel, Power Query, SQL and Tableau, and practice data driven decision making.

3. STUDY HOURS

 

4. ROLE IN CURRICULUM

 

Prerequisites:
Students must have completed Introduction to Data Analysis in Business (STAT 111).

SKILLS

  • COURSE LEARNING OUTCOMES (CLO)
  • ASSESSMENT AND GRADING
  • TEACHING METHODS
  • STUDY PLAN
  • TEXTBOOKS AND REFERENCES

5. COURSE LEARNING OUTCOMES (CLO)

On successful completion of this course students should be able to:

Knowledge Level of Learning

Related   PLO
Explain Emerging Technologies Concepts (CK1)
Explain the concepts in emerging technologies (cloud computing, big data, data analytics, and artificial intelligence and machine learning)		 Understand PCIT1
Cognitive Skills Level of Learning

Related   PLO

Design Business Dashboards, Reports, and Performance (CC1)
Design business metrics dashboards and reports to reflect business strategy and performance indicators.

 Create PK2
Communication, Information Technology, and Numerical Skills Level of Learning

Related   PLO
Create Business Performance Dashboards (CCIT1)
Create engaging business performance dashboards using data analytics tools such as Tableau, Power Query, SQL.		 Create  PCIT1
Interpersonal Skills and Responsibilities Level of Learning

Related   PLO
Work individually and in a team (CIPI)
Work individually and in a team to support data-driven business decisions utilizing the dashboards and reports from Tableau, Power Query, SQL		 Characterize PIP1

6. ASSESSMENT AND GRADING

Grades will be determined based on the following assessments and score allocations:

SKILL Assessment Skill Weighting for Grade
Participation In-class test Project Final Exam
Explain Emerging Technologies Concepts (CK1)   100%     10%
Design Business Dashboards, Reports, and Performance (CC1)     50% 50% 30%
Create Business Performance Dashboards (CCIT1)     100%   50%
Work both in team and individually to assist data-driven in
Business Decision (CIPI)		 100%       10%

7. TEACHING METHODS

This course is taught with a variety of teaching methods such as lecture, demonstration, questioning and discussion, and significant hands-on practice. Students will be assigned readings, homeworks, projects, and in-class tests.

There will be two assignments; one is the individual project and another is the group

Assignment 1:

Create Business Performance Reports using SQL
Work Group: Individual
Output format: System/Tool Generated Reports (Template to be provided)
Language: English

Description:

Students individually will create business performance reports using SQL. Data for a sample company will be provided. Assignment Rubric.

Assignment 2:

Create Business Performance Dashboards using Tableau
Work Group: Group of two to four students [No more than 4 members in the group]
Output format: System/Tool Generated Reports (Template to be provided)
Language: English

Description:

Students, in their assignment group, will create business performance dashboards using Tableau. Each group will need to do a presentation of their report in the class. Data for a sample company will be provided. Assignment Rubric.

8. STUDY PLAN

The course targets the 50 lessons in the study plan below. Each lesson is 1.5 class hours  each; there are a total of 75 class hours. The study plan below describes the learning outcome for each lesson, described in terms of what the student should be doing during the session and would be able to do at the end of the lesson. Readings & hands-on practice, wherever applicable, should be done by students as preparation before the start of each class. Implementation of this study plan may vary somewhat depending on the progress and needs of the students.

   Lesson Learning Outcomes Teaching and Learning Activities, Assessment
1

Data Analytics & Business Intelligence 

  1. Explain Data Science, Data Analytics & Business Intelligence
 Lecture (T)
Group Discussion (T,A)
2

Explain Data Analytics & Business Intelligence, continued (CK1)

  1. Biases
  2. Analytical Mindset
  3. Data analysis process
  4. Roles and stakeholders
 Lecture (T)
Group Discussion (T,A)
3

Explain evolution of computing & evolving role of big data and AMIL – Part 1 (CK1)

  1. Systems of Records
  2. Systems of Insights
  3. Evolution of computing – mainframes to distributed to cloud computing
  4. Shift from Industry 3.0 to Industry 4.0 and role data analytics & AIML
 Lecture (T)
Group Discussion (T,A)
4

Explain evolution of computing & evolving role of big data and AMIL – Part 2 (CK1)

Big Data

 – The changing paradigm 

  1. Overview of big data (including 3V to 5V shift)
  2. Opportunities created by big data

Lecture (T)
Group Discussion (T,A)
5

Explain evolution of computing & evolving role of big data and AMIL – Part3 (CK1)

Artificial intelligence & machine learning (AIML)

  1. Overview of artificial intelligence
  2. Machine learning and deep learning
  3. Opportunities created by AIML
 Lecture (T)
Group Discussion (T,A)
6

Analyze data science, data analytics, and artificial intelligence relationship (CK1)

  1. Overlap between data science, data analytics, and artificial intelligence
  2. Data driven decision making
 Lecture (T)
Group Discussion (T,A)
7

Explain data analytics tools landscape (CK1, CC1)

  1. Tools for data analysis
  2. Tools for data visualization
  3. Tools for data engineering
 Lecture (T)
Group Discussion (T,A)
  Data Analysis Section  
8

Assess data analysis toolset (CC1, CCIT1)

  1. Introduction to data analysis tool sets
  2. Key features and comparisons of multiple tools

Lecture (T)
Group Discussion (T,A)
9

Explain data transformation and normalization (CC1, CCIT1)

  1. Data transformation concepts
  2. Data normalization concepts
  3. Data transformation hands-on
 Lecture (T)
Discussion (T,A)
Hands-on practice (A)
10

Use Power Query to transform the data (CC1, CCIT1)

Data transformation hands-on

 Lecture (T)
Discussion (T,A)
Hands-on practice (A)
11

Use Power Query to extract information (CC1, CCIT1)

  1. Extracting information concepts
  2. Extracting information hands-on
 Lecture (T)
Discussion (T,A)
Hands-on practice (A)
 12

Use Power Query for data consolidation & reporting (CC1, CCIT1)

  1. Consolidating data concepts
  2. Consolidating data hands-on
 Lecture (T)
Discussion (T,A)
Hands-on practice (A)
 13

Use Power Query for debugging  (CC1, CCIT1)

  1. Debugging concepts
  2. Debugging hands-on
 Lecture (T)
Discussion (T,A)
Hands-on practice (A)
14

Use multiple features of Power Query (CC1, CIP1)

Recap Power Query

 Lecture (T)
Group Discussion (T,A)
 15

Create performance reports and dashboards using Power Query (CCIT1, CIP1)

Practice Session with Learning Assessment

 Hands-On Activity (A)
 16

Create performance reports and dashboards using Power Query  (CCIT1, CIP1)

Practice Session with Learning Assessment, continued

 Hands-On Activity (A)
17 Quiz 1 (CK1, CC1, CCIT1)  
18

Configure SQL (Structured Query Language) (CC1, CCIT1)

  1. Introduction
  2. Set up the environment for SQL
  3. Introduction to sample database for hands-on activities
 Lecture (T)
Discussion (T,A)
Hands-on practice (A)
 19

Use SQL (Structured Query Language) to write basic queries (CC1, CCIT1)

Writing SQL queries hands-on

 Lecture (T)
Discussion (T,A)
Hands-on practice (A)
 20

Explain data manipulation in SQL (Structured Query Language) (CC1, CCIT1)

  1. Data manipulation concepts
  2. Data manipulation hands-on
 Lecture (T)
Discussion (T,A)
Hands-on practice (A)
21

Use SQL (Structured Query Language) to manipulate data (CC1, CCIT1)

Data manipulation hands-on

 Lecture (T)
Discussion (T,A)
Hands-on practice (A)
 22

Explain database management system concepts – Part 1 (CC1, CCIT1)

  1. Introduction to database systems
  2. OLTP and data warehouse
  3. Data normalization and denormalization
  4. Concepts in structuring the data warehouse
 Lecture (T)
Group Discussion (T,A)
 23

Explain database management system concepts – Part 2 (CC1, CCIT1)

  1. ERD Concepts
  2. Joins and unions
  3. Hands-on
 Lecture (T)
Discussion (T,A)
Hands-on practice (A)
 24

Use SQL (Structured Query Language) to create views and dynamic results (CC1, CCIT1)

  1. Creating views
  2. Using subqueries for dynamic results
  3. Hands-on

Lecture (T)
Discussion (T,A)
Hands-on practice (A)
 25

Create reports using SQL (Structured Query Language) (CC1, CCIT1)

  1. SQL for reporting concepts
  2. Query SQL in Excel
  3. Create reports using CUBE
  4. Create reports using ROLLUP
  5. Hands-on
 Lecture (T)
Discussion (T,A)
Hands-on practice (A)
26

Use multiple features of SQL (Structured Query Language) – Part 1 (CC1, CIP1)

Recap SQL 1

 Lecture (T)
Discussion (T,A)
27

Use multiple features of SQL (Structured Query Language) – Part 2  (CC1, CIP1)

Recap SQL 2

 Lecture (T)
Discussion (T,A)
28

Create business performance reports using SQL (Structured Query Language) – Part 1 (CCIT1, CIP1)

Practice Session with Learning Assessment

 Hands-on practice (A)
29

Create business performance reports using SQL (Structured Query Language) – Part 1  (CCIT1, CIP1)

Practice Session with Learning Assessment, continued

 Hands-on practice (A)
 30 Quiz 2  (CK1, CC1, CCIT1)  
   Data Visualization  
 31

Explain Data Visualization (CC1, CCIT1)

  1. Concepts in data visualization
  2. Scenario Analysis (class discussion & presentation)
 Lecture (T)
Group Discussion (T,A)
 32

Configure Tableau (CC1, CCIT1)

  1. Tableau overview
  2. Set up the environment
 Lecture (T)
Discussion (T,A)
Hands-on practice (A)
 33

Design performance dashboard using case scenario (CC1, CCIT1)

  1. Introduction to case study data
  2. Design dashboard to reflect business performance
  3. Import common data files
  4. Hands-on
 Lecture (T)
Discussion (T,A)
Hands-on practice (A)
 34

Use Tableau for data transformation (CC1, CCIT1)

  1. Transform the data
  2. Create the dataset
  3. Hands-on
 Lecture (T)
Discussion (T,A)
Hands-on practice (A)
 35

Use functions & tables in Tableau – Part 1  (CC1, CCIT1)

  1. Calculate business metrics using functions
  2. Hands-on
 Lecture (T)
Discussion (T,A)
Hands-on practice (A)
 36

Use functions & tables in Tableau – Part 2 (CC1, CCIT1)

  1. Calculate business metrics using functions, continued
  2. Table calculations
  3. Hands-on

Lecture (T)
Discussion (T,A)
Hands-on practice (A)
 37

Use data visualization components in Tableau – Part 1 (CC1, CCIT1)

  1. Visuals in Tableau
  2. Tables & heatmaps
  3. Hands-on
 Lecture (T)
Discussion (T,A)
Hands-on practice (A)
 38

Use data visualization components in Tableau – Part 2 (CC1, CCIT1)

  1. Interactive line charts
  2. Dynamic titles
  3. Hands-on
 Lecture (T)
Discussion (T,A)
Hands-on practice (A)
 39

Use data visualization components in Tableau – Part 3 (CC1, CCIT1)

  1. Lollipop, scatter charts
  2. Tree maps
  3. Hands-on
 Lecture (T)
Discussion (T,A)
Hands-on practice (A)
 40

Design business metrics dashboards in Tableau – Part 1(CC1, CCIT1)

Creating Visuals Activity – Hands-on

 Hands-on Activity (A)
 41

Design business metrics dashboards in Tableau – Part 2 (CC1, CCIT1)

  1. Tiled vs floating dashboards
  2. Dashboard sizing
  3. hands-on

Lecture (T)
Discussion (T,A)
 42

Design business metrics dashboards in Tableau – Part 3 (CC1, CCIT1)

  1. Placing & formatting of visuals
  2. Create collapsible containers
  3. hands-on
 Lecture (T)
Discussion (T,A)
 43

Design business metrics dashboards in Tableau – Part 4 (CC1, CCIT1)

  1. Making dashboards interactive
  2. hands-on
 Lecture (T)
Discussion (T,A)
 44

Use multiple features of Tableau – Part 1 (CC1, CIP1)

Recap 1

 Lecture (T)
Discussion (T,A)
45

Use multiple features of Tableau – Part 2 (CC1, CIP1)

Recap 2

 Lecture (T)
Discussion (T,A)
46

Create business performance dashboards using Tableau – Part 1 (CCIT1, CIP1)

Practice Session with Learning Assessment

 Hands-on Activity (A)
47

Create business performance dashboards using Tableau – Part 2 (CCIT1, CIP1)

Practice Session with Learning Assessment, continued

 Hands-on Activity (A)
48 Quiz 3 (CK1, CC1, CCIT1)  
49

Analyze multiple features of Power Query, SQL and Tableau (CK1, CC1, CCIT1, CIP1)

Overall Recap Session 1

Lecture (T)
Discussion (T,A)
50

Create performance dashboards using  Power Query, SQL and Tableau (CK1, CC1, CCIT1, CIP1)

Overall Recap Session 2

 Lecture (T)
Discussion (T,A)

9. TEXTBOOKS AND REFERENCES

Textbooks

  1. Visualization Analysis and Design (AK Peters Visualization Series) by Tamara Munzner:.

References

  1. Storytelling with Data: A Data Visualization Guide for Business Professionals by Cole Nussbaumer Knaflic: Wiley.
  2. M Is for (Data) Monkey: A Guide to the M Language in Excel Power Query by Ken Puls & Miguel Escobar. 
  3. Collect, Combine, and Transform Data Using Power Query in Excel and Power BI (Business Skills) 1st Edition by Gil Raviv: Pearson Education.
  4. The Developer’s Guide to Azure. E-book series: Microsoft Azure.
  5. The Applied SQL Data Analytics Workshop: Develop your practical skills and prepare to become a professional data analyst, 2nd Edition by Matt Goldwasser, Upom Malik, Benjamin Johnston: Packt.
  6. Visual Analytics with Tableau 1st Edition by Alexander Loth: Wiley.

Education Resources