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Beth Prince-Bradbury

In this course, you will learn how to organize your data within the Microsoft Office Excel software tool. Once organized, we will discuss data cleaning. You will learn how to identify outliers and anomalies in the data, and how to identify and change data-types. Together we will develop a data analysis plan, after which we will apply analysis methods and tools, including exploratory analysis, evaluation of results, and comparison with other findings.

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In this course, you will learn how to organize your data within the Microsoft Office Excel software tool. Once organized, we will discuss data cleaning. You will learn how to identify outliers and anomalies in the data, and how to identify and change data-types. Together we will develop a data analysis plan, after which we will apply analysis methods and tools, including exploratory analysis, evaluation of results, and comparison with other findings.

In this robust Excel course, you will gain a solid foundation in using advanced Excel functions such as pivot tables and vlookup to organize and analyze data sets. You will be able to create an Excel chart in a variety of chart types including scatter plot, pie charts, and more. We’ll discuss various techniques such as descriptive statistics, and review the variety of Excel add-ins available to use this powerful tool to organize, analyze, and transform your data into actionable insights. All course activities are designed and demonstrated using Windows OS and Microsoft Excel 2016.

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What's inside

Learning objectives

  • After completing this course, learners will be able to use microsoft excel to:
  • ● perform basic data organization
  • ● clean data
  • ● develop a data analysis plan
  • ● perform analysis methods and tools

Good to know

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Teaches essential Excel skills for data organization and analysis, useful in various industries and domains
Covers advanced Excel functions like pivot tables and vlookup for efficient data organization and analysis
Provides a solid foundation for using Excel to analyze and interpret data, enhancing learners' problem-solving abilities
Offers a comprehensive approach to data analysis, including exploratory analysis, evaluation, and comparison with other findings
Emphasizes data cleaning and handling techniques, equipping learners with skills to manage and prepare data for analysis
Requires Windows OS and Microsoft Excel 2016, which may not be accessible to all learners

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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 Data Processing and Analysis with Excel with these activities:
Review Data Analysis Concepts
Refresh your knowledge of data analysis concepts, such as descriptive statistics, hypothesis testing, and data visualization, to strengthen your foundation for this course.
Show steps
  • Review your previous coursework or study materials on data analysis
  • Complete practice questions or exercises to assess your understanding
Read Excel User Guide
Gain foundational knowledge and understanding of core Excel functions, tools, and processes to enhance your learning experience in this course.
View Excel 2019 Bible on Amazon
Show steps
  • Download the Microsoft Excel 2016 User Guide
  • Review the table of contents and identify relevant chapters
  • Read and comprehend the selected chapters
Excel Resources Compilation
Consolidate and organize valuable Excel resources, such as tutorials, templates, and online communities, to support your ongoing learning and problem-solving in Excel.
Show steps
  • Gather and bookmark relevant Excel resources
  • Create a central repository or document to store these resources
  • Categorize and tag the resources for easy retrieval
Four other activities
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Basic Data Manipulation Exercises
Reinforce your understanding and proficiency in performing basic data manipulation techniques, such as sorting, filtering, and manipulating data types.
Browse courses on Data Organization
Show steps
  • Access practice exercises on data manipulation
  • Complete the exercises, experimenting with different data manipulation functions
  • Review your results and identify areas for improvement
Excel Chart Creation Exercises
Enhance your proficiency in creating visually appealing and informative charts in Excel to effectively communicate your data analysis results.
Browse courses on Data Visualization
Show steps
  • Access practice exercises on Excel chart creation
  • Experiment with different chart types and customize their appearance
  • Analyze and interpret the charts to draw meaningful conclusions
Collaborate on a Data Analysis Project
Enhance your understanding and teamwork skills by collaborating with peers on a data analysis project, applying the principles and tools learned in this course.
Browse courses on Data Analysis Techniques
Show steps
  • Form a study group with other course participants
  • Select a dataset and define the project scope
  • Work together to analyze the data, create visualizations, and draw conclusions
  • Present your findings to the group
Create an Excel Data Analysis Workbook
Apply your knowledge to create a practical workbook that demonstrates your ability to organize, analyze, and interpret data using Excel's advanced functions.
Browse courses on Data Analysis
Show steps
  • Gather and prepare a dataset
  • Design and create a data analysis workbook using Excel
  • Utilize pivot tables, charts, and formulas for data analysis
  • Write a brief report summarizing your findings

Career center

Learners who complete Data Processing and Analysis with Excel will develop knowledge and skills that may be useful to these careers:
Management Consultant
Management Consultants use their skills in data analysis to help businesses improve their performance. This course can help Management Consultants develop a strong foundation in data analysis methods and tools, as well as how to apply these methods and tools to real-world business problems. It also covers advanced Excel functions like pivot tables and vlookup, which are commonly used by Management Consultants.
Data Scientist
Data Scientists use their skills in data analysis to develop and implement machine learning models. This course can help Data Scientists build a foundation in data analysis methods and tools, as well as how to apply these methods and tools to develop and implement machine learning models. It also covers advanced Excel functions like pivot tables and vlookup, which are commonly used by Data Scientists.
Business Analyst
Business Analysts use their skills in data analysis to identify and solve business problems. This course can help Business Analysts develop a strong foundation in data analysis methods and tools, as well as how to apply these methods and tools to real-world business problems. It also covers advanced Excel functions like pivot tables and vlookup, which are commonly used by Business Analysts.
Operations Research Analyst
Operations Research Analysts use their skills in data analysis to develop and implement mathematical models to improve the efficiency of business operations. This course can help Operations Research Analysts develop a strong foundation in data analysis methods and tools, as well as how to apply these methods and tools to develop and implement mathematical models. It also covers advanced Excel functions like pivot tables and vlookup, which are commonly used by Operations Research Analysts.
Statistician
Statisticians use their skills in data analysis to collect, analyze, and interpret data. This course can help Statisticians develop a strong foundation in data analysis methods and tools, as well as how to apply these methods and tools to real-world data. It also covers advanced Excel functions like pivot tables and vlookup, which are commonly used by Statisticians.
Data Architect
Data Architects use their skills in data analysis to design and build data architectures. This course can help Data Architects develop a strong foundation in data analysis methods and tools, as well as how to apply these methods and tools to design and build data architectures. It also covers advanced Excel functions like pivot tables and vlookup, which are commonly used by Data Architects.
Software Engineer
Software Engineers use their skills in data analysis to develop and implement software applications. This course can help Software Engineers develop a strong foundation in data analysis methods and tools, as well as how to apply these methods and tools to develop and implement software applications. It also covers advanced Excel functions like pivot tables and vlookup, which are commonly used by Software Engineers.
Data Analyst
Data Analysts use their skills in organization, data cleaning, and data analysis to wrangle data. They use this data to develop insights that help businesses make better decisions. This course can help Data Analysts build a foundation in organizing, cleaning, and analyzing data. It also covers advanced Excel functions like pivot tables and vlookup, which are commonly used by Data Analysts.
Financial Analyst
Financial Analysts use their skills in data analysis to evaluate the financial performance of companies and make investment recommendations. This course can help Financial Analysts develop a strong foundation in data analysis methods and tools, as well as how to apply these methods and tools to financial data. It also covers advanced Excel functions like pivot tables and vlookup, which are commonly used by Financial Analysts.
Data Engineer
Data Engineers use their skills in data analysis to design and build data pipelines. This course can help Data Engineers develop a strong foundation in data analysis methods and tools, as well as how to apply these methods and tools to design and build data pipelines. It also covers advanced Excel functions like pivot tables and vlookup, which are commonly used by Data Engineers.
Quantitative Analyst
Quantitative Analysts use their skills in data analysis to develop and implement trading strategies. This course can help Quantitative Analysts develop a strong foundation in data analysis methods and tools, as well as how to apply these methods and tools to develop and implement trading strategies. It also covers advanced Excel functions like pivot tables and vlookup, which are commonly used by Quantitative Analysts.
Actuary
Actuaries use their skills in data analysis to assess risk and uncertainty. This course can help Actuaries develop a strong foundation in data analysis methods and tools, as well as how to apply these methods and tools to assess risk and uncertainty. It also covers advanced Excel functions like pivot tables and vlookup, which are commonly used by Actuaries.
Business Intelligence Analyst
Business Intelligence Analysts use their skills in data analysis to develop and implement business intelligence solutions. This course can help Business Intelligence Analysts develop a strong foundation in data analysis methods and tools, as well as how to apply these methods and tools to develop and implement business intelligence solutions. It also covers advanced Excel functions like pivot tables and vlookup, which are commonly used by Business Intelligence Analysts.
Risk Manager
Risk Managers use their skills in data analysis to identify and manage risks. This course can help Risk Managers develop a strong foundation in data analysis methods and tools, as well as how to apply these methods and tools to identify and manage risks. It also covers advanced Excel functions like pivot tables and vlookup, which are commonly used by Risk Managers.
Market Researcher
Market Researchers use their skills in data analysis to understand market trends and consumer behavior. This course can help Market Researchers develop a strong foundation in data analysis methods and tools, as well as how to apply these methods and tools to real-world data. It also covers advanced Excel functions like pivot tables and vlookup, which are commonly used by Market Researchers.

Reading list

We've selected 14 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 Processing and Analysis with Excel.
Covers advanced Excel techniques for data analysis. It covers topics such as data mining, forecasting, and optimization. The book is written in a clear and concise style, making it easy to follow for experienced users.
Provides a comprehensive overview of the data analysis process. It covers topics such as data collection, cleaning, analysis, and visualization. The book is written in a clear and concise style, making it easy to follow for both beginners and experienced users.
Provides a comprehensive overview of data science for business. It covers topics such as data collection, cleaning, analysis, and visualization. The book is written in a clear and concise style, making it easy to follow for both beginners and experienced users.
Provides a comprehensive overview of deep learning with Python. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks. The book is written in a clear and concise style, making it easy to follow for both beginners and experienced users.
Provides a comprehensive overview of data visualization with Python. It covers topics such as data preparation, visualization techniques, and interactive visualization. The book is written in a clear and concise style, making it easy to follow for both beginners and experienced users.
Provides a comprehensive overview of Python programming. It covers a wide range of topics, from basic programming concepts to advanced topics such as data analysis and machine learning.
Provides a comprehensive overview of Excel VBA programming. It covers a wide range of topics, from beginner-level concepts to advanced.
Provides a comprehensive overview of Power BI for data analysis. It covers topics such as data preparation, visualization, and reporting.
Provides a comprehensive overview of data analysis using SQL and Excel. It covers topics such as data extraction, cleaning, and analysis.
Provides a comprehensive overview of data analysis with Python and Jupyter Notebooks. It covers a wide range of topics, from basic programming concepts to advanced topics such as data visualization and machine learning.
Provides a comprehensive overview of effective data visualization. It covers topics such as choosing the right charts and graphs, and designing visualizations that are clear and easy to understand.
Provides a comprehensive overview of Tableau for data analysis. It covers topics such as data preparation, visualization, and reporting.
Provides a comprehensive overview of Power Query for data analysis. It covers topics such as data extraction, cleaning, and transformation.

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