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Data literacy is a capability to read, use and analyse data to produce information that can be acted upon. Every organisation creates and stores data but not everyone has the skills and confidence to work with it.

This course is designed for anyone who is not a data specialist but has a need to work with data in their role.

In this course you’ll gain an understanding of the role data can play, data structures, data quality and how you can use data to produce analysis to turn data into information and create a data story.

Examples, demonstrations and exercises may use a selection of common applications including Microsoft Excel and Google Sheets.

Understand how to write formulas using standard functions
Experience of creating or using charts and graphs

At the end of this course, you’ll be able to:

Identify data types and structures
Work with data quality challenges
Apply a structured approach to work with data
Create a testable hypothesis
Use fundamental analytics and statistical approaches
Select appropriate visuals
Build an effective data story

Module 1: Data Literacy and its Role

Data is Everywhere
Data-driven Culture
Creating Value from Data

Module 2: Data Management

Enterprise Data Management
Data Governance and Ethics
Data Collection

Module 3: Data Quality Management

Identifying Data Quality Issues
Data Quality Metrics
Common Data Challenges
- Incomplete Datasets
- Duplication
- Data Type and Formatting Issues

Module 4: Data Structures and Data Traits

Data Types
Tidy Data
Quantitative and Qualitative Data
Data Scales
Data Models
- Facts and Dimensions
- Relationships and Joins

Module 5: Data Analysis Process, Terms and Concepts

Data Analytics Lifecycle
Business Problems and Hypothesis
- A structured approach
- Stakeholders’ Perspective
- Creating a Hypothesis
- Determining the Data You Need
- Defining Success
Types of Analytics
Different types of Average
Beyond averages
- Distribution and Deviation
- Percentile, Quartiles and Rank

Module 6: Data Analysis and Testing

Regression Analysis
Correlation and Causation
Testing your Hypothesis
- A/B, Control and Multivariate
Preparing to tell the Data Story

Module 7: Visuals and Charts

Chart Types
Visualisation and Statistics
Matching the Visual to the Data
Drawing attention to Key Insights
Focussing on the Difference

Module 8: Storytelling with Data

What is data storytelling?
Three key questions
Context and Empathy
A Data Story in Three Acts
Defining Success Criteria
Dashboards – Types and Design Considerations

Module 9: Data Literacy Socialisation and Communication

Data-Led Change
Feedback Loops

Upcoming Trainings

Join our public courses in our New Zealand facilities. Private class trainings will be organized at the location of your preference, according to your schedule.

Classroom / Virtual Classroom

12 July 2024