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This course features interactive videos to help you understand both the analytical concepts and the software. This course contains a capstone project, in which you will apply the concepts taught using a separate data source; this realistic project gives you the practice and confidence necessary to connect, explore, and analyze data sources into the future.This course is also part of a certificate:

Data Analytics and Visualization Certificate

What's inside

Learning objective

In this course, you will learn the basics of business analytics using excel. you'll start by learning all about business analytics, including the importance of the role of obtaining crucial information for the organization. then, you will begin working on a dataset in excel, and learn essential tasks such as sorting and filtering the data to learn more about the business. finally, learn how to analyze both categorical and numeric data: for categorical data, learn how to aggregate data using excel's pivot table feature; for numeric data, learn the basics of analyzing distributions using statistics and common visualizations such as histograms and boxplots. by the end of the course, you will have hands-on practice in preparing data for analysis and thoroughly analyzing a dataset using descriptive analytic techniques.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Builds a strong foundation for beginners who are new to business analytics in Excel
Develops skills in preparing and thoroughly analyzing data using descriptive analytic techniques
Applies the concepts taught using a separate data source, giving learners hands-on practice
Provides interactive videos to help learners understand analytical concepts and software

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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 Business Intelligence and Data Analytics with these activities:
Read Python Data Science Handbook
Get a comprehensive understanding of data science fundamentals and how to apply Python for data analysis.
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  • Review chapter summaries and key concepts.
  • Work through coding exercises to practice Python implementation.
Review Basic Data Analysis Concepts
Refresh your understanding of foundational data analysis concepts prior to starting the course.
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  • Review key concepts from previous statistics or data analysis courses.
  • Take online quizzes or practice problems related to basic data analysis.
  • Consult textbooks or online resources for additional clarity.
Excel Data Analysis Exercises
Reinforce data analysis concepts and improve proficiency in using Excel for data manipulation and analysis.
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  • Solve practice problems involving data sorting and filtering.
  • Analyze data using PivotTables and charts.
  • Perform statistical calculations and create visualizations.
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Data Analysis Study Group
Collaborate with peers to discuss data analysis concepts, share insights, and work through problems together.
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  • Join or create a study group with fellow students.
  • Meet regularly to discuss course material and assignments.
  • Help each other understand concepts and solve problems.
Explore Advanced Functions in Excel
Supplement learning about Excel Functions by watching tutorials on using specific functions to execute more complex tasks.
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Show steps
  • Search for tutorials on advanced Excel functions.
  • Choose a tutorial that aligns with your interests or needs.
  • Follow the tutorial and explore additional resources on the topic.
  • Apply the functions you learned in your own projects or assignments.
Solve Business Analytics Practice Problems
Reinforce your understanding of Business Analytics concepts by engaging in practice problems.
Show steps
  • Find practice problems online or in textbooks.
  • Solve the problems using the techniques learned in the course.
  • Review your answers and identify areas for improvement.
  • Seek help from classmates or the instructor if needed.
SQL for Data Analysis Tutorial
Gain practical experience in using SQL for data querying, manipulation, and analysis.
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  • Follow online tutorials on SQL syntax and commands.
  • Practice writing SQL queries on sample datasets.
  • Complete hands-on exercises to apply SQL concepts.
Excel Problem-Solving Study Group
Enhance your learning through collaborative problem-solving and peer support.
Show steps
  • Join or create a study group with classmates.
  • Meet regularly to work on problems and share knowledge.
  • Take turns leading discussions and presenting solutions.
  • Provide constructive feedback to your peers.
Data Analytics Workshop
Attend a workshop to gain exposure to advanced data analytics techniques and industry best practices.
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Show steps
  • Research and identify relevant workshops.
  • Register and attend the workshop.
  • Actively participate in discussions and hands-on exercises.
Data Visualization Project
Apply data analysis techniques to create meaningful and impactful visualizations that effectively communicate insights.
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  • Choose a dataset and define the project goals.
  • Explore and clean the data.
  • Select appropriate visualization techniques.
  • Design and create the visualizations.
  • Present the project and findings.
Develop a Data Visualization Dashboard
Demonstrate your ability to analyze and present data effectively by creating a comprehensive dashboard.
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  • Gather and prepare the data you want to visualize.
  • Choose an appropriate visualization tool (e.g., Tableau, Power BI).
  • Design and develop the dashboard, ensuring clarity and usability.
  • Present your dashboard to classmates or the instructor for feedback.
Excel Function Reference Guide
Organize and reinforce your knowledge by creating a comprehensive reference guide for Excel functions.
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Show steps
  • Gather information on a variety of Excel functions, including their syntax, arguments, and examples.
  • Organize the functions into a logical structure, such as by category or type.
  • Include clear and concise descriptions for each function.
  • Provide examples and scenarios to illustrate the practical applications of each function.
  • Share your reference guide with classmates or the instructor for feedback and improvement.
Data Analysis Blog Post
Demonstrate understanding of data analysis concepts and share insights gained from analyzing real-world data.
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Show steps
  • Choose a data analysis topic and gather relevant data.
  • Perform data analysis and draw conclusions.
  • Write a blog post outlining the analysis process and findings.
Contribute to Open-Source Excel Add-Ins
Deepen your understanding of Excel's functionality and collaborate with others to enhance the Excel ecosystem.
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  • Identify an existing open-source Excel add-in that interests you.
  • Review the add-in's codebase and identify areas where you can contribute.
  • Develop and test your contributions, following the add-in's development guidelines.
  • Submit your contributions to the add-in's repository and engage in code reviews.
Data Analytics Volunteer Project
Apply data analysis skills to make a meaningful contribution to a non-profit organization or social cause.
Browse courses on Data Analytics
Show steps
  • Research and identify volunteer opportunities that align with interests.
  • Apply for and secure a volunteer position.
  • Use data analysis techniques to assist with projects and initiatives.

Career center

Learners who complete Business Intelligence and Data Analytics will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts use their knowledge of data and analytical tools to examine data and extract meaningful insights. This course provides a strong foundation for a career as a Data Analyst by teaching the basics of business analytics using Excel, including how to prepare data for analysis, analyze both categorical and numeric data, and use Excel's Pivot Table feature to aggregate data.
Business Analyst
Business Analysts use data to identify and solve problems within an organization. This course can help you become a Business Analyst by providing you with the skills you need to analyze data, identify trends, and make recommendations to improve business processes.
Market Researcher
Market Researchers use data to understand consumer behavior and trends. This course can provide you with the skills you need to become a Market Researcher by teaching you how to collect, analyze, and interpret data to identify opportunities and make recommendations for marketing campaigns.
Financial Analyst
Financial Analysts use data to analyze financial performance and make investment recommendations. This course can help you become a Financial Analyst by providing you with the skills you need to analyze financial data, identify trends, and make recommendations for investment decisions.
Operations Research Analyst
Operations Research Analysts use data to improve the efficiency of operations within an organization. This course can help you become an Operations Research Analyst by providing you with the skills you need to analyze data, identify bottlenecks, and make recommendations for process improvements.
Statistician
Statisticians use data to analyze and interpret data. This course may be useful for aspiring Statisticians by providing them with a foundation in data analysis and visualization.
Data Scientist
Data Scientists use data to build models and predict future outcomes. This course may be useful for aspiring Data Scientists by providing them with a foundation in data analysis and visualization.
Risk Analyst
Risk Analysts use data to assess risk and make financial decisions. This course may be useful for aspiring Risk Analysts by providing them with a foundation in data analysis and visualization.
Data Visualization Specialist
Data Visualization Specialists use data to create visual representations of data. This course may be useful for aspiring Data Visualization Specialists by providing them with a foundation in data analysis and visualization.
Quantitative Analyst
Quantitative Analysts use data to make investment decisions. This course may be useful for aspiring Quantitative Analysts by providing them with a foundation in data analysis and visualization.
Actuary
Actuaries use data to assess risk and make financial decisions. This course may be useful for aspiring Actuaries by providing them with a foundation in data analysis and visualization.
Business Intelligence Analyst
Business Intelligence Analysts use data to identify and solve problems within an organization. This course may be useful for aspiring Business Intelligence Analysts by providing them with a foundation in data analysis and visualization.
Data Architect
Data Architects use data to design and implement data management systems. This course may be useful for aspiring Data Architects by providing them with a foundation in data analysis and visualization.
Software Engineer
Software Engineers use data to design and develop software applications. This course may be useful for aspiring Software Engineers by providing them with a foundation in data analysis and visualization.
Computer Scientist
Computer Scientists use data to design and develop computer systems. This course may be useful for aspiring Computer Scientists by providing them with a foundation in data analysis and visualization.

Reading list

We've selected ten 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 Business Intelligence and Data Analytics.
Provides a practical introduction to data analytics, covering topics such as data cleaning, data analysis, and data visualization. It valuable resource for students and professionals who want to learn more about the field of data analytics.
Provides a practical introduction to data visualization. It valuable resource for students and professionals who want to learn more about how to create effective data visualizations.
Provides a practical guide to big data analytics. It valuable resource for students and professionals who want to learn more about how to use these tools for big data analysis.
Provides a practical introduction to machine learning. It valuable resource for students and professionals who want to learn more about how to use these tools for machine learning.
Provides a comprehensive overview of deep learning. It valuable resource for students and professionals who want to learn more about the field of deep learning.
Provides a comprehensive guide to Spark. It valuable resource for students and professionals who want to learn more about the field of Spark.
Provides a practical guide to natural language processing with Python. It valuable resource for students and professionals who want to learn more about the field of natural language processing.
Provides a practical guide to machine learning for beginners. It valuable resource for students and professionals who want to learn more about the field of machine learning.

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