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Data-driven Decision Making

Alex Mannella

Welcome to Data-driven Decision Making. In this course, you'll get an introduction to Data Analytics and its role in business decisions. You'll learn why data is important and how it has evolved. You'll be introduced to “Big Data” and how it is used. You'll also be introduced to a framework for conducting Data Analysis and what tools and techniques are commonly used. Finally, you'll have a chance to put your knowledge to work in a simulated business setting.

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Welcome to Data-driven Decision Making. In this course, you'll get an introduction to Data Analytics and its role in business decisions. You'll learn why data is important and how it has evolved. You'll be introduced to “Big Data” and how it is used. You'll also be introduced to a framework for conducting Data Analysis and what tools and techniques are commonly used. Finally, you'll have a chance to put your knowledge to work in a simulated business setting.

This course was created by PricewaterhouseCoopers LLP with an address at 300 Madison Avenue, New York, New York, 10017.

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What's inside

Syllabus

Introduction to Data Analytics
In this module, you'll learn the basics of data analytics and how businesses use to solve problems. You'll learn the value data analytics brings to business decision-making processes. We’ll introduce you to a framework for data analysis and tools used in data analytics. Finally, we’re going to talk about careers and roles in data analytics and data science. Note: Video transcripts are auto generated and may contain spelling and punctuation errors.
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Technology and types of data
This module is an introductory look at big data and big data analytics where you will learn the about different types of data. We’ll also introduce you to PwC's perspective on big data and explain the impact of big data on businesses. Finally we will name some of the different types of tools and technologies used to gather data.
Data analysis techniques and tools
In this module we will describe some of the tools for data analytics and some of the key technologies for data analysis. We will talk about how visualization is important to the practice of data analytics. Finally we will identify a variety of tools and languages used and consider when those tools are best used.
Data-driven decision making project
The course project will give you an opportunity to practice what you have learned. You will participate in a simulated business situation in which you will select the best course of action. You will then prepare a final deliverable which will be evaluated by your peers. Additionally, you will have the opportunity to provide feedback on your peer's submissions.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Explores the basics of data analytics and how businesses use it to solve problems
Taught by instructors from PricewaterhouseCoopers LLP, a leading professional services firm
Covers different types of data and how to gather it
Provides an overview of big data and its impact on businesses
Offers hands-on practice in a simulated business setting

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Reviews summary

Data-driven decision making

Learners say this course provides a comprehensive overview of data-driven decision making. PWC professionals use real-world examples to teach data analytics, problem solving, and consultancy skills. The course has a strong focus on utilizing data analysis tools to solve business challenges. Students who successfully complete the course can earn a certificate to demonstrate their proficiency in data-driven decision making.
Suitable for learners with no prior knowledge of data analysis.
"This course is a great introduction to data analysis, even for beginners with no prior knowledge of the subject."
"The course is a great starting point for anyone interested in learning about data-driven decision-making."
Introduces students to industry tools and technologies used in data analysis.
"The course introduces students to a variety of industry-leading data analysis tools and technologies, including Python, R, SAS, and Tableau."
"The course content covers a range of data analysis techniques, including data collection, analysis, interpretation, and recommendation."
Offers opportunities to apply learning through quizzes, assignments, and a final project.
"The course was very interactive and engaging, with plenty of opportunities to apply the concepts learned through quizzes, assignments, and a final project."
Provides many examples of real-world business applications of data analysis.
"The course is filled with case studies and discussions of real-world problems and how data was used to solve these problems, which provides a very beneficial hands-on experience."
"The course content covers a range of data analysis techniques, including data collection, analysis, interpretation, and recommendation."
Learns about a 4-step data analysis framework that includes data collection, analysis, interpretation, and recommendation.
"Learners analyze real examples of how PWC consultants use data and analytics to solve business problems to improve effectiveness and profit."
"The course content covers a range of data analysis techniques, including data collection, analysis, interpretation, and recommendation."
Some learners felt the course was too promotional of PWC.
"The course is a bit too promotional for PWC, but the content is still good."

Career center

Learners who complete Data-driven Decision Making will develop knowledge and skills that may be useful to these careers:
Data Analyst
A Data Analyst gathers, processes, and analyzes data to help businesses make informed decisions. This course provides a solid foundation in data analytics, including data collection, analysis techniques, and visualization tools. By completing this course, you'll gain the skills necessary to succeed as a Data Analyst, enabling you to contribute to data-driven decision-making within organizations.
Data Scientist
A Data Scientist uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course provides a comprehensive overview of data analytics, including big data and data analysis techniques, which are essential for success in the field. By taking this course, you'll gain the knowledge and skills to become a successful Data Scientist, enabling you to contribute to data-driven innovation and decision-making.
Business Analyst
A Business Analyst identifies and analyzes business needs and develops solutions to improve efficiency and effectiveness. This course provides a strong foundation in data analytics, which is increasingly important for Business Analysts to understand and use in their work. By completing this course, you'll gain the skills to translate business requirements into data-driven solutions, enhancing your value as a Business Analyst.
Market Researcher
A Market Researcher gathers and analyzes data about consumer behavior, market trends, and industry dynamics to help businesses make informed decisions. This course provides a comprehensive introduction to data analytics and its applications in market research. By taking this course, you'll gain the skills to conduct effective market research studies and leverage data to gain insights into consumer behavior and market trends, enhancing your value as a Market Researcher.
Financial Analyst
A Financial Analyst analyzes financial data and trends to make investment recommendations and advise clients on financial matters. This course provides a solid foundation in data analytics, which is increasingly important for Financial Analysts to understand and use in their work. By completing this course, you'll gain the skills to analyze financial data, identify trends, and make informed recommendations, enhancing your value as a Financial Analyst.
Operations Research Analyst
An Operations Research Analyst uses mathematical and analytical techniques to solve complex business problems and improve decision-making. This course provides a strong foundation in data analytics, which is essential for Operations Research Analysts to use in their work. By completing this course, you'll gain the skills to analyze data, develop models, and optimize solutions, enhancing your value as an Operations Research Analyst.
Management Consultant
A Management Consultant advises businesses on how to improve their performance and achieve their goals. This course provides a comprehensive overview of data analytics, which is increasingly important for Management Consultants to understand and use in their work. By taking this course, you'll gain the skills to analyze data, identify trends, and make informed recommendations, enhancing your value as a Management Consultant.
Data Engineer
A Data Engineer designs, builds, and maintains data pipelines and infrastructure to support data analytics. This course provides a strong foundation in data analytics, including data storage, processing, and management techniques. By completing this course, you'll gain the skills to design and implement data pipelines, enabling you to contribute to the efficient and effective use of data within organizations.
Software Engineer
A Software Engineer designs, develops, and maintains software applications. This course provides a solid foundation in data analytics, which is increasingly important for Software Engineers to understand and use in their work. By completing this course, you'll gain the skills to analyze data, identify trends, and develop data-driven software solutions, enhancing your value as a Software Engineer.
Quantitative Analyst
A Quantitative Analyst uses mathematical and statistical models to analyze data and make investment decisions. This course provides a solid foundation in data analytics, which is essential for Quantitative Analysts to use in their work. By completing this course, you'll gain the skills to analyze financial data, identify trends, and develop quantitative models, enhancing your value as a Quantitative Analyst.
Actuary
An Actuary analyzes and manages financial risks for insurance companies and other financial institutions. This course provides a solid foundation in data analytics, which is increasingly important for Actuaries to understand and use in their work. By completing this course, you'll gain the skills to analyze data, identify trends, and develop risk models, enhancing your value as an Actuary.
Statistician
A Statistician collects, analyzes, and interprets data to provide insights and make informed decisions. This course provides a strong foundation in data analytics, which is essential for Statisticians to use in their work. By completing this course, you'll gain the skills to analyze data, identify trends, and develop statistical models, enhancing your value as a Statistician.
Data Architect
A Data Architect designs and manages data infrastructure to support data analytics. This course provides a strong foundation in data analytics, including data storage, processing, and management techniques. By completing this course, you'll gain the skills to design and implement data architectures, enabling you to contribute to the efficient and effective use of data within organizations.
Database Administrator
A Database Administrator manages and maintains databases to ensure data integrity and performance. This course provides a strong foundation in data analytics, including data storage, processing, and management techniques. By completing this course, you'll gain the skills to manage and maintain databases, enabling you to contribute to the efficient and effective use of data within organizations.
Information Security Analyst
An Information Security Analyst protects data and information systems from unauthorized access, use, disclosure, disruption, modification, or destruction. This course provides a solid foundation in data analytics, which is increasingly important for Information Security Analysts to understand and use in their work. By completing this course, you'll gain the skills to analyze data, identify trends, and develop security measures, enhancing your value as an Information Security Analyst.

Reading list

We've selected 27 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 Data-driven Decision Making.
Provides a comprehensive overview of data analytics, including data collection, analysis, and visualization. It good starting point for those who are new to the field.
Provides a practical guide to using data analytics to improve business performance. It covers topics such as data collection, analysis, and decision-making.
Provides a practical introduction to data science for business professionals. It covers topics such as data mining, machine learning, and data visualization.
Provides a comprehensive overview of the mathematics behind machine learning. It good read for those who want to understand the mathematical foundations of machine learning.
Explores the impact of big data on business and society. It good read for those who want to understand the potential of big data.
Provides a practical introduction to data visualization. It covers topics such as choosing the right chart type, creating effective visualizations, and using visualization tools.
Provides an overview of predictive analytics, a type of data analysis that uses data to predict future events. It good read for those who want to understand the potential of predictive analytics.
Provides a comprehensive overview of deep learning, a type of machine learning that uses artificial neural networks to learn from data. It good read for those who want to understand the state-of-the-art in machine learning.
Provides an introduction to reinforcement learning, a type of machine learning that allows computers to learn from their mistakes. It good read for those who want to understand the basics of reinforcement learning.
Provides a comprehensive overview of robotics, a type of artificial intelligence that allows computers to control physical systems. It good read for those who want to understand the state-of-the-art in robotics.
Provides a comprehensive overview of statistical learning, a type of machine learning that uses data to learn statistical models. It good read for those who want to understand the state-of-the-art in statistical learning.
Provides a practical guide to data science for business professionals. It covers the basics of data science, including data collection, cleaning, analysis, and visualization. It also provides case studies of how data science is being used to solve business problems.
Provides a practical guide to machine learning for business professionals. It covers the basics of machine learning, including data collection, cleaning, analysis, and visualization. It also provides case studies of how machine learning is being used to solve business problems.
Provides a practical introduction to natural language processing, a type of artificial intelligence that allows computers to understand human language. It good starting point for those who are new to the field.
Provides a practical guide to deep learning for business professionals. It covers the basics of deep learning, including data collection, cleaning, analysis, and visualization. It also provides case studies of how deep learning is being used to solve business problems.
Provides a practical guide to data-driven marketing. It covers the basics of data-driven marketing, including data collection, cleaning, analysis, and visualization. It also provides case studies of how data-driven marketing is being used to improve marketing campaigns.
Provides a practical guide to data-driven innovation. It covers the basics of data-driven innovation, including data collection, cleaning, analysis, and visualization. It also provides case studies of how data-driven innovation is being used to create new products and services.
Provides a comprehensive overview of data ethics. It covers the ethical challenges of data collection, cleaning, analysis, and visualization. It also provides case studies of how data ethics is being used to address real-world problems.
Provides a comprehensive overview of data science. It covers the basics of data science, including data collection, cleaning, analysis, and visualization. It also provides case studies of how data science is being used to solve real-world problems.
Provides a comprehensive overview of data visualization. It covers the basics of data visualization, including data collection, cleaning, and analysis. It also provides case studies of how data visualization is being used to communicate insights.
Provides a comprehensive overview of data mining. It covers the basics of data mining, including data collection, cleaning, and analysis. It also provides case studies of how data mining is being used to solve real-world problems.
Provides a comprehensive overview of statistical methods for data analysis. It covers the basics of statistical methods, including data collection, cleaning, and analysis. It also provides case studies of how statistical methods are being used to solve real-world problems.
Provides a comprehensive overview of machine learning. It covers the basics of machine learning, including data collection, cleaning, analysis, and visualization. It also provides case studies of how machine learning is being used to solve real-world problems.

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