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Introduction to Data

Josh Bernhard , Derek Steer, Mat Leonard, Dana Sheahan, and Sam Nelson

Take Udacity's Introduction to Data Analytics for Business course and learn to utilize data & statistics in business strategy & planning. Gain skills to drive business results.

What's inside

Syllabus

In this lesson, you will learn about data types, measures of center, and the basics of statistical notation.
In this lesson, you will learn about measures of spread, shape, and outliers as associated with quantitative data. You will also get a first look at inferential statistics.
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In this lesson, you will learn about the basic functionality for spreadsheet software, use cell referencing and menu shortcuts.
In this lesson, you will learn basic spreadsheet function: sort and filter data, use text and math functions, split columns and remove duplicates.
In this lesson, you will learn how to summarize data with aggregation and conditional functions. You will learn how to use pivot tables and lookup functions.
In this lesson you will build data visualizations for quantitative and categorical data; create pie, bar, line, scatter, histogram, and boxplot charts, and build professional presentations.
This lesson will cover how to calculate business metrics used by business analysts across a range of business functions. You will also learn how to calculate and interpret key performance metrics.
This lesson will cover the fundamentals of sales and financial forecasting models. You will learn how to create forecast models using advanced lookup and data validation tools in Excel and Sheets.
In this project, you will use a data set containing financial performance data from companies listed in NYSE S&P to create an income statement and forecast financial metrics.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Designed explicitly for business professionals looking to gain data analytics skills
Teaches core data analytics concepts and techniques used in business
Taught by experts in the field with extensive industry experience
Develops strong data analysis and visualization skills for business decision-making
In-demand skills that can enhance career prospects in various business roles
May require prior knowledge of basic statistics and spreadsheet software

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Activities

Coming soon We're preparing activities for Introduction to Data. These are activities you can do either before, during, or after a course.

Career center

Learners who complete Introduction to Data will develop knowledge and skills that may be useful to these careers:
Data Analyst
As a Data Analyst, your work will involve utilizing data to solve analytical problems in both qualitative and quantitative ways. The Introduction to Data Analytics for Business course can help you get started in the role of a Data Analyst by giving a firm foundation in fundamental concepts like data collection and interpretation, statistical analysis, and data visualization.
Business Analyst
A Business Analyst will most often leverage various data analysis techniques in order to contribute to fact-based decision making. By taking this course, you will learn how to use statistical and spreadsheet software and apply it to diverse business applications. These skills can help you prepare for this role.
Market Research Analyst
Market Research Analysts leverage data to understand trends and consumer and market patterns. This course can help you get started in the role of a Market Research Analyst by providing a basis in business data analysis and visualization.
Data Scientist
Data Scientists employ a variety of tools and techniques to extract meaning from data. This course can be helpful to an aspiring Data Scientist, as it covers data analysis and visualization, two core competencies of a Data Scientist.
Financial Analyst
Financial Analysts gather and interpret data in order to help individuals and groups make investment decisions. This course can help you build a foundation in the skills needed to be a Financial Analyst by providing a background in data collection and analysis.
Operations Research Analyst
Operations Research Analysts use mathematical and analytical methods to solve complex problems in business and industry. The Introduction to Data Analytics for Business course may help prepare you for the role of an Operations Research Analyst by providing a background in data analysis and visualization.
Statistician
Statisticians collect, analyze, interpret, and present numerical data. The Introduction to Data Analytics for Business course may be useful as it provides a foundation in the fundamentals of statistics.
Economist
Economists study how societies produce, distribute, and consume goods and services. The Introduction to Data Analytics for Business course may be useful as it provides an introduction to data analysis.
Actuary
Actuaries evaluate the financial consequences of risk. The Introduction to Data Analytics for Business course may be useful as it provides an introduction to data analysis.
Marketing Manager
Marketing Managers plan and execute marketing campaigns. The Introduction to Data Analytics for Business course may be useful as it provides an introduction to data analysis and visualization.
Product Manager
Product Managers define and oversee the development of products. The Introduction to Data Analytics for Business course may be useful as it provides an introduction to data analysis.
Consultant
Consultants identify and solve problems that businesses face. The Introduction to Data Analytics for Business course may be useful as it provides an introduction to data analysis and visualization.
Data Engineer
Data Engineers build and maintain data infrastructure. The Introduction to Data Analytics for Business course may be useful as it provides an introduction to data analysis.
Database Administrator
Database Administrators manage databases. The Introduction to Data Analytics for Business course may be useful as it provides an introduction to data analysis.
Software Engineer
Software Engineers design, develop, and maintain software. The Introduction to Data Analytics for Business course may be useful as it provides an introduction to data analysis.

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 Introduction to Data.
This widely-used textbook provides a solid foundation in statistical learning methods, including supervised and unsupervised learning, regression analysis, and classification. While it's a more advanced read, it offers a comprehensive and rigorous approach to understanding the underlying principles of data analysis.
This comprehensive textbook provides a thorough understanding of forecasting methods and techniques. It covers topics such as time series analysis, regression models, and machine learning algorithms, making it a valuable reference for those seeking to develop forecasting skills.
Provides a comprehensive guide to data analysis using Python and Pandas. It covers topics such as data loading and cleaning, data manipulation, and statistical analysis, making it a valuable resource for those who want to use Python for data analysis.
This comprehensive reference book covers various data mining techniques, including association rule mining, clustering, classification, and forecasting. It's an excellent resource for those seeking a deeper understanding of data mining algorithms and their applications.
Provides a clear and accessible introduction to data visualization techniques. It covers topics such as chart types, color theory, and data storytelling, making it a helpful resource for those seeking to effectively communicate data insights.
This practical guide provides a step-by-step approach to using Tableau Desktop for data visualization and analysis. It covers topics such as data preparation, chart creation, and dashboard development, making it a valuable resource for those seeking to use Tableau effectively.
Provides a comprehensive guide to business intelligence using SQL Server. It covers topics such as data warehousing, data mining, and reporting, making it a valuable resource for those who want to use SQL Server for business intelligence.
Provides a practical introduction to machine learning for business. It covers topics such as supervised learning, unsupervised learning, and model evaluation, making it a valuable resource for those who want to use machine learning to solve business problems.
This straightforward guide explains key business metrics and how to use them to measure performance and make informed decisions. It's a helpful resource for those who want to understand the metrics commonly used in business and how to interpret them.

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