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Jordan Morrow

The ability to make smart decisions with data is paramount to an organization's success. This Executive Briefing will dive into the world of making smart, intelligent decisions with data, and how it ties to data literacy.

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The ability to make smart decisions with data is paramount to an organization's success. This Executive Briefing will dive into the world of making smart, intelligent decisions with data, and how it ties to data literacy.

Tech leaders need a fundamental understanding of the tools and technologies their teams use to build solutions. In this course, Making Data-informed Decisions: Executive Briefing, you will learn that the world of data and analytics should drive an organization to make smarter data-driven and data-informed decisions. First, you will see about making decisions with data. Then, you will discover the 4-levels of analytics and how it pertains to decision making with data. Finally, you will explore the two main types of decision making with data: data-driven and data-informed, and tying this into data literacy and a data literate culture. By the end of this course, you will have a greater understanding of data-informed decision making for your organization.

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What's inside

Syllabus

Utilizing Data to Make Decisions
Utilizing the 4 Levels of Analytics in Decision Making
Harnessing the Power of Data Decision Making
Utilizing Data Literacy in Decision Making with Data
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops your ability to make smart, data-driven decisions
Provides a fundamental understanding of tools and technologies used in data analytics
Fits decision-makers who want to understand the 4-levels of analytics, and how to apply it to decision making
Covers the types of decision making with data, which should interest data-literate decision-makers
Core audience includes mid- to senior-level executives, such as CEOs and VPs, who make data-driven decisions and want to learn more about this field
Assumes participants have a basic understanding of data and analytics

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Making Data-informed Decisions: Executive Briefing with these activities:
Join a data analytics community
Connect with other professionals to exchange knowledge and best practices in data analytics.
Browse courses on Data Analytics
Show steps
  • Join online forums or discussion groups focused on data analytics.
  • Attend local meetups or conferences related to data analytics.
  • Network with colleagues and professionals in the data analytics field.
  • Find a mentor or advisor who can provide guidance and support.
Organize your course materials
Keep your course materials well-organized for easy reference and review.
Show steps
  • Create a system for organizing your notes, assignments, and other materials.
  • Use digital tools like folders, note-taking apps, or cloud storage to keep your materials organized.
  • Review your materials regularly to reinforce your understanding of the course content.
Explore data literacy resources
Enhance your understanding of data literacy principles and techniques.
Browse courses on Data Literacy
Show steps
  • Visit websites and platforms dedicated to data literacy.
  • Watch videos and read articles on data literacy best practices.
  • Attend workshops or webinars on data literacy.
  • Find a mentor or colleague who can provide guidance on data literacy.
12 other activities
Expand to see all activities and additional details
Show all 15 activities
Review Calculus
Review your knowledge of calculus before taking this Executive Briefing, to ensure your foundational understanding is solid.
Browse courses on Differential Calculus
Show steps
  • Review your notes from previous calculus courses
  • Work through practice problems to test your understanding
  • Take practice quizzes online or in textbooks
Read 'Decision Intelligence: How to Create and Deliver Business Value'
Review a related field by reading 'Decision Intelligence: How to Create and Deliver Business Value' by Andrew Pearson, to build your foundational understanding of data-driven decision making prior to starting this course.
View Psychology and Life on Amazon
Show steps
  • Read the book's introduction and first chapter
  • Summarize the key points of each chapter
  • Identify examples of data-driven decision making in your own work or personal life
Learn data science basics
Refresh your knowledge of data science concepts and techniques to prepare for this course.
Browse courses on Data Science Basics
Show steps
  • Review online tutorials on data science basics.
  • Take a practice quiz on data science concepts.
  • Complete a hands-on data analysis project using a programming language like Python or R.
Watch Pluralsight's 'Data-Driven Decision Making' Video Series
Supplement your understanding by watching Pluralsight's series on data-driven decision making, to gain practical insights and best practices before the course begins.
Show steps
  • Watch the first three videos in the series
  • Take notes on the key concepts and techniques
Review data analytics fundamentals
Brush up on core data analytics concepts to strengthen your understanding of the course material.
Browse courses on Data Analytics
Show steps
  • Revisit key concepts such as data types, data structures, and data visualization.
  • Review statistical and mathematical foundations for data analytics.
Attend industry webinars or conferences
Connect with professionals in the field and stay updated on industry trends.
Show steps
  • Search for upcoming webinars or conferences related to data analytics.
  • Register and attend the events.
  • Engage with speakers and attendees to expand your network.
Explore real-world data analytics use cases
Enhance your understanding of data analytics by exploring how it's applied in various industries.
Show steps
  • Identify industries that heavily rely on data analytics.
  • Seek out case studies or tutorials that demonstrate data analytics applications in these industries.
  • Analyze the use cases and extract key insights and best practices.
Analyze Data to Make a Decision in Your Own Life
Apply your foundational knowledge by working on a project to analyze data and make a decision in your own life. This will help you internalize the decision-making process and see it in a practical context before starting the course.
Browse courses on Data Analysis
Show steps
  • Identify a personal decision you need to make
  • Gather data relevant to the decision
  • Analyze the data using basic techniques like visualization and summary statistics
  • Make a decision based on your analysis
Practice data analysis techniques
Reinforce your understanding of data analysis techniques through hands-on practice.
Browse courses on Data Analysis Techniques
Show steps
  • Find online platforms or resources that provide data analysis exercises.
  • Choose exercises that align with the topics covered in the course.
  • Solve the exercises and compare your solutions with expert answers.
Practice making data-driven decisions
Develop your skills in using data to make informed decisions.
Show steps
  • Analyze a real-world dataset and identify trends and patterns.
  • Use data visualization tools to create charts and graphs that present data insights.
  • Write a report or presentation based on your analysis and insights.
Develop a data-informed decision-making framework
Create a practical framework to guide data-informed decision-making in your organization.
Show steps
  • Define the problem or decision to be addressed.
  • Identify the data sources and data collection methods.
  • Analyze the data to identify relevant insights.
  • Develop recommendations based on the analysis.
  • Implement the recommendations and monitor the results.
Develop a data visualization dashboard
Apply your learning by creating an interactive dashboard that effectively communicates data insights.
Browse courses on Data Visualization
Show steps
  • Choose a dataset that aligns with the course content.
  • Select appropriate data visualization techniques to represent the data.
  • Use a data visualization tool to create an interactive dashboard.
  • Annotate the dashboard with insights and explanations.

Career center

Learners who complete Making Data-informed Decisions: Executive Briefing will develop knowledge and skills that may be useful to these careers:
Data Analyst
A Data Analyst collects, analyzes, and interprets data to provide insights and support decision-making. This course can help Data Analysts enhance their skills in making data-driven decisions, utilizing the 4 levels of analytics, and improving their data literacy.
Data Scientist
A Data Scientist uses advanced statistical and machine learning techniques to extract insights from data and solve complex business problems. This course can help Data Scientists develop their skills in leveraging data to make informed decisions and build data-driven solutions.
Chief Digital Officer
A Chief Digital Officer (CDO) leads a company's digital transformation, leveraging data to drive growth and innovation. This course can help build a foundation for success as a CDO by providing a comprehensive understanding of data-informed decision making and the tools and technologies used to analyze data.
Business Analyst
A Business Analyst helps businesses identify and solve problems by analyzing data, processes, and systems. This course can help Business Analysts improve their decision-making skills, understand the role of data in driving business outcomes, and enhance their data literacy.
Product Manager
A Product Manager oversees the development and launch of products or services. This course can help Product Managers make data-driven decisions, understand customer needs and market trends, and improve their product development strategies.
Marketing Manager
A Marketing Manager plans and executes marketing campaigns to promote products or services. This course can help Marketing Managers make data-driven marketing decisions, analyze marketing performance, and improve campaign effectiveness.
Project Manager
A Project Manager plans, executes, and controls projects to achieve specific goals. This course can help Project Managers develop their skills in data-driven project management, making informed decisions throughout the project lifecycle, and effectively communicating data insights to stakeholders.
Sales Manager
A Sales Manager leads a team of sales representatives and is responsible for achieving sales targets. This course can help Sales Managers make data-driven sales decisions, understand customer behavior, and improve their sales strategies.
Operations Manager
An Operations Manager oversees the day-to-day operations of a business or organization. This course may be useful for Operations Managers who want to develop their skills in data-driven decision making, process improvement, and resource allocation.
Market Researcher
A Market Researcher gathers and analyzes data to understand market trends and consumer behavior. This course may be useful for Market Researchers who want to develop their skills in data-driven market research, survey design, and data visualization.
Supply Chain Manager
A Supply Chain Manager plans and manages the flow of goods and services from suppliers to customers. This course may be useful for Supply Chain Managers who want to improve their skills in data-driven supply chain management, inventory optimization, and risk mitigation.
Financial Analyst
A Financial Analyst analyzes financial data to make investment recommendations and provide insights into financial markets. This course may be useful for Financial Analysts who want to enhance their skills in data-driven financial analysis, risk assessment, and portfolio management.
Data Engineer
A Data Engineer designs, builds, and maintains data pipelines and systems. This course may be useful for Data Engineers who want to develop their skills in data management, data integration, and data quality assurance.
Software Engineer
A Software Engineer designs, develops, and maintains software applications. This course may be useful for Software Engineers who want to develop their skills in data-driven software development, data visualization, and machine learning integration.
Database Administrator
A Database Administrator manages and maintains database systems. This course may be useful for Database Administrators who want to develop their skills in data management, data security, and data optimization.

Reading list

We've selected nine books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Making Data-informed Decisions: Executive Briefing.
Practical guide to using data and analytics to improve business performance. It provides clear and concise explanations of key concepts and tools, and it includes case studies to illustrate how analytics can be used in a variety of industries.
Provides a unique perspective on data science. It emphasizes the importance of ethics and critical thinking, and it provides practical advice on how to use data to solve problems and make better decisions.
Provides a comprehensive overview of data-informed decision making. It covers the basics of data analysis and interpretation, and it provides step-by-step instructions on how to use data to make better decisions.
Practical guide to using data for strategic advantage. It provides clear and concise explanations of key concepts and tools, and it includes case studies to illustrate how data can be used to improve decision-making in a variety of industries.
Provides a comprehensive overview of big data. It explains the challenges and opportunities of big data, and it provides practical advice on how to use big data to improve business outcomes.
Practical guide to data visualization. It provides clear and concise explanations of key concepts and tools, and it includes case studies to illustrate how data visualization can be used to communicate insights effectively.
Provides a unique perspective on the ethical implications of artificial intelligence. It explores the challenges of developing AI systems that are fair, unbiased, and transparent.
Comprehensive guide to data analytics. It covers the basics of data analytics, and it provides practical advice on how to use data analytics to make better decisions.

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