Google
Google Data-Driven Decision Making Specialization
Google

Google Data-Driven Decision Making Specialization

Improve business decisions with data and AI.. Learn to ask SMART questions, analyze information, and turn complex data into actionable insights.

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Beginner level

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4 weeks to complete
at 6 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
Beginner level

Recommended experience

4 weeks to complete
at 6 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Apply structured thinking, data integrity checks, and ethical practices to real-world business problems

  • Use AI responsibly to speed up data analysis and prepare effective presentations

  • Communicate insights effectively to stakeholders and make confident, data-driven decisions

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Taught in English
Recently updated!

September 2025

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Specialization - 9 course series

What you'll learn

  • Discuss the use of data in everyday life decisions

  • Explain the data analysis process, making specific reference to the ask, prepare, process, analyze, share, and act phases

  • Define key concepts involved in data analytics including data, data analysis, and data ecosystem

  • Explain the concept of data-driven decision-making including specific examples

Skills you'll gain

Category: Data Ethics
Category: Data Quality
Category: Business Analytics
Ask Effective Questions

Ask Effective Questions

Course 22 hours

What you'll learn

  • Explore problem solving in data analysis through a variety of real-world business scenarios

  • Describe the six phases of the data analysis process

  • Identify the common problem types that data analysts face

  • Practice effective questioning techniques that can help guide analysis

Make Data-Driven Decisions

Make Data-Driven Decisions

Course 32 hours

What you'll learn

  • Discuss the importance and benefits of dashboards and reports to the data analyst with reference to Tableau and spreadsheets

  • Explain the difference between quantitative and qualitative data including reference to their use and specific examples

  • Compare and contrast data-driven decision making with data-inspired decision making

  • Discuss the use of data in the decision-making process

What you'll learn

  • Identify common limitations with data, with specific reference to speed versus accuracy and responding to time-sensitive requests

  • Discuss the importance of focus on stakeholder expectations.

  • Discuss best practices for the data analyst in reference to office communication, conflict resolution, facilitating meetings, and status reports.

Skills you'll gain

Category: Real Time Data
Data Responsibility

Data Responsibility

Course 53 hours

What you'll learn

  • Discuss the difference between biased and unbiased data.

  • Discuss characteristics of credible sources of data including reference to untidy data

  •  Explain the relationship between data ethics and data privacy

  • Demonstrate an awareness of the accessibility issues associated with open data

The Importance of Integrity

The Importance of Integrity

Course 62 hours

What you'll learn

  • Define different types of data integrity and identify risks to data integrity.

  • Describe the benefits of documenting data cleaning process.

  • Describe strategies that can be used to address insufficient data.

  • Describe the benefits of documenting the data cleaning process

Skills you'll gain

Category: Data Integrity
Category: Sampling (Statistics)
Category: Data Cleansing
Category: Data Quality
Category: Statistical Analysis
Category: Data Analysis
Category: Sample Size Determination
Category: Statistics
Category: Data Validation
Visualize Data

Visualize Data

Course 74 hours

What you'll learn

  • Describe the use of data visualizations to talk about data and the results of data analysis.

  • Describe the key concepts involved in data visualization.

  • Discuss accessibility issues associated with data visualization.

  • Explain the key concepts involved in design thinking as they relate to data visualization.

Skills you'll gain

Category: Web Content Accessibility Guidelines
Category: Correlation Analysis

What you'll learn

  • Explain principles and practices associated with effective presentations.

  • Describe how junior data analysts are expected to use their presentation skills.

What you'll learn

  • Apply the prompting framework to extract insights from data, identify and fix spreadsheet formulas, and explore data visualization

  • Develop a responsible prompting practice when entering data into generative AI tools

  • Understand AI sampling parameters, how they work, and strategies for their use

  • Apply the prompting framework to level up your presentation skills.

Skills you'll gain

Category: Data Analysis
Category: Verbal Communication Skills
Category: Responsible AI
Category: Presentations
Category: Sampling (Statistics)
Category: Excel Formulas
Category: Prompt Engineering
Category: Data Presentation
Category: Spreadsheet Software
Category: Generative AI

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