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Credit- Degree applicable
Effective Quarter: Fall 2020

I. Catalog Information


CIS 64G
Data Visualization Methodology and Tools
4 1/2 Unit(s)
 

Advisory: EWRT 211 and READ 211 (or LART 211), or ESL 272 and 273.

Lec Hrs: 48.00
Lab Hrs: 18.00
Out of Class Hrs: 96.00
Total Student Learning Hrs: 162.00

This course is an introduction to the strategies and technologies used in business intelligence reporting and dashboards for making data-driven decisions.


Student Learning Outcome Statements (SLO)

 

Design and implement reports and dashboards for data and trends analysis using technologies like Tableau, PowerBI, BIRT or Pentaho.


II. Course Objectives

A.Exhibit understanding of Business Intelligence (BI) technologies as means to solving business problems.
B.Demonstrate connecting to disparate data sources for creating reports.
C.Analyze data and perform calculations to derive results.
D.Design visualizations to enable quick decision making for key objectives.
E.Identify ways to publish and share reports, dashboards and other key analytics information with stakeholders.

III. Essential Student Materials

 None

IV. Essential College Facilities

 Access to a computer lab with Microsoft Office, Adobe Acrobat and any one of Tableau, PowerBI, BIRT or Pentaho

V. Expanded Description: Content and Form

A.Exhibit understanding of Business Intelligence (BI) technologies as means to solving business problems.
1.Understanding key concepts of Business Intelligence (BI).
2.Review the landscape of BI tools.
B.Demonstrate connecting to disparate data sources for creating reports.
1.Structured and unstructured data Sources.
2.Extracting Data.
3.Data transformation, cleaning or blending.
a.Join types with Union.
b.Cross database joins.
c.Swapping primary and secondary data sources.
d.Data query syntax (SQL, JSON, DAX)
4.Data Modeling.
a.Building views of data.
b.Sorting.
c.Grouping.
d.Filtering.
e.Pivoting.
f.Drill-down and hierarchies.
C.Analyze data and perform calculations to derive results.
1.Dimensions and Measures.
2.Aggregate Calculations.
3.Type Calculations.
4.Logic Calculations.
5.Level of detail expressions.
D.Design visualizations to enable quick decision making for key objectives.
1.Chart Types.
a.Combination charts.
b.Scatter graphs.
c.Waterfall and funnel charts.
d.Pareto charts.
e.Map visualizations.
2.Report Formatting.
a.Shapes, text boxes and images.
b.Page layout and formatting.
c.Enhancing display visualizations.
3.Building dashboards.
a.Gauges and sliders.
b.Visual hierarchies and drill-downs.
c.Group interactions among visualizations.
E.Identify ways to publish and share reports, dashboards and other key analytics information with stakeholders.
1.Print and export reports and dashboards.
2.Create user groups for role-based access.
3.Publish to web based resources.
4.Republishing after refreshing data.

VI. Assignments

A.Reading: Required reading from the textbook and class notes
B.Programs: 4-5 report generation homework assignments.
C.Group Project: Creating business intelligence dashboards for assigned datasets.

VII. Methods of Instruction

 Lecture and visual aids
Discussion of assigned reading
Discussion and problem solving performed in class
Collaborative learning and small group exercises
Collaborative projects

VIII. Methods of Evaluating Objectives

A.One or two midterm examinations requiring some programming, concepts clarification and
exhibiting mastery of reporting constructs presented in the course.
B.A final examination requiring concepts clarification and exhibiting mastery of data analysis and visualization principles.
C.Evaluation of programming assignments and group project, based on correctness, intuitiveness and visual appeal.

IX. Texts and Supporting References

A.Examples of Primary Texts and References
1.Evergreen, Stephanie: Effective Data Visualization: The Right Chart for the Right Data 1st Edition. SAGE Publications. ISBN-13: 978-1506303055, May 2016.
B.Examples of Supporting Texts and References
1.None.

X. Lab Topics

A.Data extraction from disparate sources.
B.Cleansing, blending and transforming data.
C.Modeling and calculating data.
D.Creating reports and charts.
E.Designing dashboards.
F.Publishing and sharing dashboards.