Data Analysis for Business: Foundations from edX

The course provides an overview of data analysis for business: an introduction and review of methods to describe data using tables, charts and summary measures. The course is designed to respond to the needs of a non-specialist audience and also for participants with “non-scientific” backgrounds (humanities and other classical disciplines), who have not been extensively exposed to quantitative methods and basic calculation procedures or, more generally, for people who do not feel comfortable with basic statistical techniques. At the end of this course the participants will be able to manage the most common basic data analysis techniques: descriptive and data visualization to properly analyze categorical and numerical business variables.

What you'll learn

The Program aims to provide basic knowledge of data analysis. The main topics covered in the Program are:

Introduction and Data Collection
Data Visualization (describing data using tables and graphs)
Summary Statistics (describing data using numerical measures)
Reporting
Random Variables and Normal Probability Distribution
Linear Correlation and Regression Line

What's inside

Learning objectives

Introduction and data collection
Data visualization (describing data using tables and graphs)
Summary statistics (describing data using numerical measures)

Reporting
Random variables and normal probability distribution
Linear correlation and regression line

Introduction and data collection
Data visualization (describing data using tables and graphs)
Summary statistics (describing data using numerical measures)
Reporting
Random variables and normal probability distribution
Linear correlation and regression line

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Designed for non-specialists and those without extensive quantitative or statistical backgrounds

Provides basic knowledge of data analysis, covering essential topics such as data visualization, summary statistics, and probability distributions

Aims to develop skills in managing common data analysis techniques, enabling learners to analyze business variables effectively

May not be suitable for learners seeking advanced or specialized data analysis knowledge

Does not include hands-on labs or interactive materials

Career center

Learners who complete Data Analysis for Business: Foundations will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts apply analytical skills to transform raw data into meaningful insights. They use statistical techniques and data visualization tools to communicate their findings to stakeholders across an organization. This course offers a solid foundation in data analysis techniques, including data visualization, summary statistics, and linear regression, making it a valuable asset for aspiring Data Analysts. By equipping learners with these essential skills, the course empowers them to effectively analyze and interpret data, contributing to better decision-making and business outcomes.

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Business Analyst

Business Analysts bridge the gap between business and technology by analyzing business processes and identifying areas for improvement. They use data analysis techniques to evaluate current operations and recommend solutions that enhance efficiency and effectiveness. This course provides Business Analysts with the foundational knowledge they need to analyze data, understand business requirements, and develop data-driven recommendations. It covers topics such as data visualization, summary statistics, and reporting, which are essential for success in this role.

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Operations Research Analyst

Operations Research Analysts use mathematical and analytical methods to solve complex business problems and improve operational efficiency. They analyze data to identify patterns, develop models, and make recommendations that optimize processes and resource allocation. This course provides a strong foundation in data analysis techniques, including probability, statistics, and linear programming, which are essential for success in this role. It helps aspiring Operations Research Analysts build the skills they need to analyze data, develop models, and drive data-driven decision-making.

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Market Researcher

Market Researchers analyze market trends, customer behavior, and industry dynamics to provide insights that inform marketing strategies and product development. They use data analysis techniques to collect, analyze, and interpret data from surveys, experiments, and other sources. This course provides a strong foundation in data analysis techniques, including data visualization, summary statistics, and regression analysis, which are essential for success in this role. It helps aspiring Market Researchers develop the skills they need to analyze market data, understand consumer behavior, and make data-driven recommendations.

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Financial Analyst

Financial Analysts assess the financial performance and health of companies or investments. They use data analysis techniques to evaluate financial statements, analyze market trends, and make recommendations on investment strategies. This course provides a strong foundation in data analysis techniques, including financial ratios, probability, and statistics, which are essential for success in this role. It helps aspiring Financial Analysts develop the skills they need to analyze financial data, understand market dynamics, and make informed investment decisions.

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Consultant

Consultants provide expert guidance and advice to businesses on a wide range of issues, including strategy, operations, and technology. They use data analysis techniques to analyze business processes, identify areas for improvement, and develop recommendations that enhance performance. This course provides a strong foundation in data analysis techniques, including data visualization, summary statistics, and regression analysis, which are essential for success in this role. It helps aspiring Consultants develop the skills they need to analyze data, understand business challenges, and make data-driven recommendations.

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Statistician

Statisticians collect, analyze, and interpret data to draw meaningful conclusions. They use statistical techniques to design experiments, analyze data, and develop models that provide insights into complex phenomena. This course provides a strong foundation in data analysis techniques, including probability, statistics, and regression analysis, which are essential for success in this role. It helps aspiring Statisticians develop the skills they need to analyze data, draw inferences, and communicate their findings.

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Data Scientist

Data Scientists use advanced statistical and machine learning techniques to extract insights from data. They build predictive models, develop algorithms, and apply data analysis techniques to solve complex business problems. While this course may not directly cover advanced topics such as machine learning, it provides a solid foundation in data analysis techniques, including data visualization, summary statistics, and probability, which are essential for aspiring Data Scientists. It helps build a foundation that can be further developed through specialized training or coursework in data science.

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Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment decisions. They develop trading strategies, evaluate risk, and manage portfolios. While this course may not directly cover advanced topics in quantitative finance, it provides a solid foundation in data analysis techniques, including probability, statistics, and regression analysis, which are essential for aspiring Quantitative Analysts. It helps build a foundation that can be further developed through specialized training or coursework in quantitative finance.

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Actuary

Actuaries use mathematical and statistical techniques to assess risk and uncertainty. They develop models to predict future events, such as mortality rates and insurance claims, and use these models to make informed decisions about risk management and financial planning. This course provides a strong foundation in data analysis techniques, including probability, statistics, and regression analysis, which are essential for success in this role. It helps aspiring Actuaries develop the skills they need to analyze data, assess risk, and make data-driven recommendations.

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Software Engineer

Software Engineers design, develop, and maintain software applications. While this course may not directly cover software engineering concepts, it provides a strong foundation in data analysis techniques, including data visualization, summary statistics, and regression analysis, which are increasingly used in software development for tasks such as data-driven decision-making and quality assurance. It helps aspiring Software Engineers develop the skills they need to analyze data, understand user behavior, and improve software products.

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Marketing Manager

Marketing Managers develop and execute marketing campaigns to promote products or services. They use data analysis techniques to track campaign performance, measure customer engagement, and make data-driven decisions to optimize marketing strategies. This course provides a strong foundation in data analysis techniques, including data visualization, summary statistics, and regression analysis, which are essential for success in this role. It helps aspiring Marketing Managers develop the skills they need to analyze data, understand customer behavior, and make data-driven marketing decisions.

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Product Manager

Product Managers are responsible for the development and success of products. They use data analysis techniques to understand customer needs, define product requirements, and make data-driven decisions throughout the product lifecycle. This course provides a strong foundation in data analysis techniques, including data visualization, summary statistics, and regression analysis, which are essential for success in this role. It helps aspiring Product Managers develop the skills they need to analyze data, understand customer feedback, and make data-driven decisions.

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Financial Planner

Financial Planners help individuals and families manage their finances to achieve their financial goals. They use data analysis techniques to assess financial situations, develop financial plans, and make investment recommendations. This course provides a strong foundation in data analysis techniques, including financial ratios, probability, and statistics, which are essential for success in this role. It helps aspiring Financial Planners develop the skills they need to analyze financial data, understand investment strategies, and make data-driven financial recommendations.

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Data Visualization Specialist

Data Visualization Specialists design and develop data visualizations to communicate insights from data. They use data analysis techniques to transform raw data into visually appealing and informative representations. This course provides a strong foundation in data visualization techniques, including data visualization tools and best practices, which are essential for success in this role. It helps aspiring Data Visualization Specialists develop the skills they need to analyze data, create effective visualizations, and communicate insights effectively.

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