Data Analytics & Visualization Coursework: Overview
Data Analytics & Visualization Coursework: Overview
In this course, students learn to develop desktop analytical tools, informational frameworks and visual interfaces for improving resource-usage and process effectiveness in support of these issues. They become acquainted with data acquisition, cleaning, filtering, structuring (in the form of optimization and simulation modeling) as well as prescription and practical conveyance. They become familiar with complex spreadsheet modeling, VBA coding, integration of Microsoft Power BI tools, the Palisades @RISK suite and application mobility. Students emerge with the technical skills and integrated multi-application competency needed to lead cutting edge analytical projects.
The key deliverable of the DAV course is a group-developed stand-alone application catered to the on-going decision support needs of an organization (public or private) or section of the population. These take on a range of forms, pulling in the capabilities of multiple tools with design for use in mind. On the left are a few examples of pitches, walk-throughs and live-presentations of tools developed (also see Student Project Gallery).
The key deliverable of the DAV course is a group-developed stand-alone application catered to the on-going decision support needs of an organization (public or private) or section of the population. These take on a range of forms, pulling in the capabilities of multiple tools with design for use in mind. On the left are a few examples of pitches, walk-throughs and live-presentations of tools developed (also see Student Project Gallery).
Two reference texts are central to the discussions of interactive analytical and visual application development. These are Excel Basics to Blackbelt, and Visual Analytics for Management.
Additional references include a research note, Visualization in Operations Management Research, INFORMS Journal on Data Science
Example undergraduate student projects are available in the Gallery of this site, and details on the SMB-A capstone can be found here.
Additional references include a research note, Visualization in Operations Management Research, INFORMS Journal on Data Science
Example undergraduate student projects are available in the Gallery of this site, and details on the SMB-A capstone can be found here.
BLACKBELT RIBBON add-in
BLACKBELT RIBBON add-in
A host of data acquisition, visualization and analysis tools, packaged for simple access and use, see the Blackbelt Ribbon Add-in - A collaboration with my former students who are now Blackbelts themselves.
ExtraLite Version now available for user until May 2022(or place the following URL in your Browser and check downloads: www.experimental-instruments.com/BlackbeltRibbon_extralite.xlam )
Select cells and use Ctrl-Shift-V to clean references in BB functions if moving the add-in (otherwise sheets will refer to prior paths).
Full version with use cases and function directory, found in 3rd Edition Excel Basics to Blackbelt text
BLACKBELT RIBBON add-in download:
ExtraLite Version now available for user until May 2022(or place the following URL in your Browser and check downloads: www.experimental-instruments.com/BlackbeltRibbon_extralite.xlam )BLACKBELT RIBBON add-in download:
Select cells and use Ctrl-Shift-V to clean references in BB functions if moving the add-in (otherwise sheets will refer to prior paths).
Full version with use cases and function directory, found in 3rd Edition Excel Basics to Blackbelt text
Current Heat Mapper image-set library:http://www.experimental-instruments.com/HeatMapCatalog.pdf
Guide to the original 2013 Blackbelt Ribbon: http://www.experimental-instruments.com/BlackBelts/RibbonManual.pdf
Guide to the original 2013 Blackbelt Ribbon: http://www.experimental-instruments.com/BlackBelts/RibbonManual.pdf
Mobile App Projects
Mobile App Projects
These apps are designed for the support of classroom discussions of descriptive, predictive and prescriptive analytics. For support in the use of these apps, please contact Dr. Bendoly @ bendoly.2@osu.edu
MazeCrunch
MazeCrunch
TrendEst
TrendEst
Enterprise Applications
Enterprise Applications
Reference Guides
Reference Guides
Foundations of Data Analytics
'Standard Convention' Iconography of Data Visualization
Decision tree for Descriptive, Predictive, Prescriptive Analytics
Other Examples
Other Examples
Getting Involved - Corporate and Alumni Opportunities for Engagement
Getting Involved - Corporate and Alumni Opportunities for Engagement
The Analytics curricula at Fisher engages with organizational interests on a rolling basis. If you are an alumni or are otherwise interested in drawing on the analytical capabilities of our undergraduate or graduate students in a 7-week or 10-month project, yielding new ways of describing, predicting or offering prescriptions from your own data, please reach out.
You can contact me directly at bendoly.2@osu.edu