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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Instructor: Google Career Certificates

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Get in-depth knowledge of a subject
4.7

(10 reviews)

Beginner level

Recommended experience

1 month at 5 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject
4.7

(10 reviews)

Beginner level

Recommended experience

1 month at 5 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers

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

Overview

What’s included

Shareable certificate

Add to your LinkedIn profile

Taught in English
Recently updated!

September 2025

44 practice exercises

Advance your subject-matter expertise

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from Google

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

Business Analytics

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

Skills you'll gain

Interviewing Skills

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

Skills you'll gain

Big Data, Business Metrics, Data Visualization, Decision Making, Key Performance Indicators (KPIs), Data Visualization Software, and Small Data

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

Stakeholder Analysis, Team Building, Internal Communications, and Team Management

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

Skills you'll gain

Data Ethics, Informed Consent, Data Analysis, Data Quality, Information Privacy, and Data Sharing

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

Data Integrity, Data Validation, Data Cleansing, Sampling (Statistics), Sample Size Determination, Data Quality, Statistics, Data Analysis, and Statistical Analysis

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

Correlation Analysis and Solution Design

What you'll learn

  • Explain principles and practices associated with effective presentations.

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

Skills you'll gain

Oral Expression, Concision, Drive Engagement, and Stakeholder Communications

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

Generative AI, Prompt Engineering, Sampling (Statistics), Data Analysis, Excel Formulas, Presentations, Spreadsheet Software, Verbal Communication Skills, and Responsible AI

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Instructor

Google
Google
378 Courses14,039,625 learners

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