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A bird's-eye view of a team presenting a data-driven business project at work.
COURSE CATALOG

The Data Analytics Project

Formats ⟩  Live Virtual: 4 hrs./day, 2 Days  |  In-Person: 6 hrs./day, 2 Days

In today's fast-paced business environment, effectively harnessing and interpreting data is crucial. Whether starting in business analytics or simply looking to improve certain areas. This in-depth 2-day course is structured to enhance your knowledge and provide actionable insights, empowering you to effectively employ analytics in your work. You will learn the essential elements of a data analysis project, including problem identification, data collection, and analysis methods. Learn how to interpret and implement a step-by-step guide for data and analytics for your organization and team.

Course Prerequisite: Data Analytics for Informed Decision-Making

Learning Objectives »

  • Identify the critical components of a data analysis project.
  • Navigate the data analysis project lifecycle.
  • Formulate well-crafted questions to guide the analysis.
  • Differentiate between types of data and analysis methods.
  • Learn how to start your project correctly using stakeholders and scope.
  • Employ data visualization techniques.
  • Create a compelling data narrative.

Course Agenda

Introduction to Data Analysis Projects

  1. Components of a Data Analysis Project
  2. The Data Analysis Project Lifecycle
  3. Data Project Case Study

Everything Begins with a Question

  1. Identifying Problems and Opportunities
  2. Asking a Well-Crafted Question
  3. Problem and Solution Statements

The Basics of Data Analytics

  1. Data Types
  2. Exploratory or Explanatory Analysis
  3. Primary and Secondary Data Sets
  4. Self-service or Assisted Data Sourcing

Data Analytics with Targeted Questions

  1. Descriptive
  2. Diagnostic
  3. Predictive
  4. Prescriptive

Building Blocks of a Successful Project

  1. Stakeholders Engagement
  2. Individual Project or Project Team
  3. Defining Project Scope
  4. Developing Project Objectives

Data Collection

  1. Surveys
  2. Interviews
  3. Focus Groups
  4. Observation
  5. Tests

ETL-The Data Analysis Workflow

  1. Extracting Data for Analysis
  2. Clean, Organize, and Shape Data
  3. Transforming Data for Efficient Analysis
  4. Tools For Data Analysis

Visualizing Your Data

  1. Fitting Your Visualization to Purpose
  2. Data Visualizations to Avoid
  3. Best Practices for Visualizations

Data Project Stories

  1. Why Data is Better with A Story
  2. Critical Elements of a Data Story
  3. The Data Narrative Structure
A bird's-eye view of a team presenting a data-driven business project at work.

The Data Analytics Project

Formats ⟩  Live Virtual: 4 hrs./day, 2 Days  |  In-Person: 6 hrs./day, 2 Days

In today's fast-paced business environment, effectively harnessing and interpreting data is crucial. Whether starting in business analytics or simply looking to improve certain areas. This in-depth 2-day course is structured to enhance your knowledge and provide actionable insights, empowering you to effectively employ analytics in your work. You will learn the essential elements of a data analysis project, including problem identification, data collection, and analysis methods. Learn how to interpret and implement a step-by-step guide for data and analytics for your organization and team.

Course Prerequisite: Data Analytics for Informed Decision-Making

Learning Objectives »

  • Identify the critical components of a data analysis project.
  • Navigate the data analysis project lifecycle.
  • Formulate well-crafted questions to guide the analysis.
  • Differentiate between types of data and analysis methods.
  • Learn how to start your project correctly using stakeholders and scope.
  • Employ data visualization techniques.
  • Create a compelling data narrative.

Course Agenda

Introduction to Data Analysis Projects

  1. Components of a Data Analysis Project
  2. The Data Analysis Project Lifecycle
  3. Data Project Case Study

Everything Begins with a Question

  1. Identifying Problems and Opportunities
  2. Asking a Well-Crafted Question
  3. Problem and Solution Statements

The Basics of Data Analytics

  1. Data Types
  2. Exploratory or Explanatory Analysis
  3. Primary and Secondary Data Sets
  4. Self-service or Assisted Data Sourcing

Data Analytics with Targeted Questions

  1. Descriptive
  2. Diagnostic
  3. Predictive
  4. Prescriptive

Building Blocks of a Successful Project

  1. Stakeholders Engagement
  2. Individual Project or Project Team
  3. Defining Project Scope
  4. Developing Project Objectives

Data Collection

  1. Surveys
  2. Interviews
  3. Focus Groups
  4. Observation
  5. Tests

ETL-The Data Analysis Workflow

  1. Extracting Data for Analysis
  2. Clean, Organize, and Shape Data
  3. Transforming Data for Efficient Analysis
  4. Tools For Data Analysis

Visualizing Your Data

  1. Fitting Your Visualization to Purpose
  2. Data Visualizations to Avoid
  3. Best Practices for Visualizations

Data Project Stories

  1. Why Data is Better with A Story
  2. Critical Elements of a Data Story
  3. The Data Narrative Structure
COURSE CATALOG
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