Data Analysis and Decision Making for Government Certificate

Data Analysis and Decision Making for Government Certificate

The Data Analysis and Decision Making for Government Certificate program is designed to expand participants' knowledge of analytics fundamentals, and help them stay on top of an ever-changing field. They will learn how to effectively interpret, package, and present data to different decision makers with ease.

The 60-hour program has an open enrollment and cohorts are limited to 18-24 participants. All classes meet in-person at UGA Gwinnett.

More information

Who Should Attend

Who Should Attend?



The primary audience for the program is state, local and school government staff. Within this group, we anticipate that finance, IT or communications staff will benefit the most. This program is open to all staff members. This program is not designed for elected officials.

 

Program Learning Objectives

Program Learning Objectives





Upon completing this program, participants will be able to:

  1. Use data storytelling and data analytics skills to present effectively to various audiences.

  2. Create engaging charts and presentations to incorporate best practices.

  3. Articulate data clearly and concisely to a broad range of decision-makers.

 

Course Objectives

Course Information

 

 

Course Materials

Course Outline

 

Day 1

Description
Before participants are ready to analyze, package and present data for decision makers, they will learn about their own strengths and growth areas. On day 1, participants will connect with other cohort members, discuss important concepts related to public speaking for various audiences and learn about the capstone project.

Learning Objectives
Upon completing day 1, participants will be able to:

  1. Recall the importance of self-awareness and understanding different audiences.
  2. Recognize different “data archetypes.”
  3. Identify the basics of good public speaking.
  4. Explain the capstone project.
Day 2

Description
Effective information packaging is critical to creating memorable and impactful presentations. In day 2, participants will learn all about the concepts of data storytelling. Participants will be assigned to their peer groups and begin work on the capstone project.

Learning Objectives
Upon completing day 2, participants will be able to:

  1. Identify the principles of data storytelling.
  2. Understand the process of creating a data story.
  3. Analyze one's intended audience in order to effectively craft and relate a data story.
  4. Relate the data storytelling to capstone project.

Day 3

Description
The first step in data analysis is understanding data literacy, where one’s data comes from and how it is collected. Day 3 will focus on these principles, and participants will be exposed to the principles of data literacy and the importance of knowing data sources. Participants will also study the DIKW Pyramid and different forms of analytics.

Learning Objectives
Upon completing day 3, participants will be able to:

  1. Identify and describe how data sources are collected.
  2. Recall the Data/Information/Knowledge/Wisdom (DIKW) Pyramid.
  3. Compare the five forms of analytics.
Day 4

Description
Building effective visualizations is at the center of every data story. On day 4, participants will learn how to create different charts in Excel. Participants will also learn best practices in chart making, including how to use color effectively and accessibly.

Learning Objectives
Upon completing day 4, participants will be able to:

  1. Compare the different chart types and identify the correct chart for different situations.
  2. Recognize best practices with using color in charts, including accessibility.
  3. Use Excel to create several different charts.

Day 5

Description
Presentation skills and data packaging are only part of what makes a successful analyst. Day 5 will begin by flexing some Excel muscles, as participants will explore how to get data ready for analysis before building basic pivot tables. Participants will also work to identify their key data sets and explore how secondary data sets such as demographics and economic data can enhance an analysis. Day 5 will introduce students to key secondary data sets and show how to incorporate that information into an analysis.

Learning Objectives
Upon completing day 5, participants will be able to:

  1. Clean data in Excel.
  2. Create a Pivot Table in Excel.
  3. Identify secondary sources of data to enhance analysis.
Day 6

Description
It is rare that a dataset will be a full representation of the population with no gaps or assumptions made. It is critical for analysts to contextualize gaps, understand what is missing and learn how to communicate it.

Learning Objectives
Upon completing day 6, participants will be able to:

  1. Recognize confirmation bias.
  2. Identify data significance.
  3. Articulate how to handle outliers.

Day 7

Description
On day 7, participants will dig even deeper into Excel. Participants will explore more advanced functions within the software, as well as experiment with the capabilities of Power Query.

Learning Objectives
Upon completing day 7, participants will be able to:

  1. Recall several different advanced Excel functions.
  2. Use Excel Power Query.
Day 8

Description
Accurate performance metrics are at the heart of all data storytelling and are critical in tracking change over time. This course will focus on measuring progress. Day 8 will allow participants an opportunity to deliver a practice presentation and solicit feedback for the capstone project.

Learning Objectives
Upon completing day 8, participants will be able to:

  1. Evaluate presentations.
  2. Appraise presentation feedback.
  3. Identify best practices of performance measures and relate them to participants’ work.

Day 9

Description
Working with data analytics does not stop with tools like Excel, and there is much more to learn. Day 9 will expose cohort members to data science and basic principles of working with Business Intelligence (BI) tools. Participants will be exposed to more details of data science, including ethics, and learn about the differing roles of data scientists.

Learning Objectives
Upon completing day 9, participants will be able to:

  1. Recognize the importance of ethics while working with data.
  2. Contrast different types of data scientists and how they fit into an organization.
  3. Understand the basics of working with a BI application.
Day 10

Description
As the culmination of the 60-hour course, participants will present their capstone projects to the other cohort members. The peer groups will role-play as a panel of “decision makers” for one another, and the presentations will be done in a “fish bowl” style, where the peer groups ask questions and the other group members observe.

Learning Objectives
Upon completing day 10, participants will be able to:

  1. Present their capstone project to their peer group and larger cohort.
  2. Role-play as a panel of “decision makers” during the presentations of their peer group members.

 

Questions? Contact Us.

Tessa Pendergraft
Program Coordinator
tpendergraft@uga.edu
706.542.0505