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Ronald Guymon
and
Gies College of Business, University of Illinois
This course introduces several tools for processing business data to obtain actionable insight. The most important tool is the mind of the data analyst. Accordingly, in this course, you will explore what it means to have an analytic mindset. You will also practice identifying business problems that can be answered using data analytics. You will then be introduced to various software platforms to extract, transform, and load (ETL) data into tools for conducting exploratory data analytics (EDA). Specifically, you will practice using PowerBI, Alteryx, and RStudio to conduct the ETL and EDA processes.
Read more
This course introduces several tools for processing business data to obtain actionable insight. The most important tool is the mind of the data analyst. Accordingly, in this course, you will explore what it means to have an analytic mindset. You will also practice identifying business problems that can be answered using data analytics. You will then be introduced to various software platforms to extract, transform, and load (ETL) data into tools for conducting exploratory data analytics (EDA). Specifically, you will practice using PowerBI, Alteryx, and RStudio to conduct the ETL and EDA processes.
Read more
This course introduces several tools for processing business data to obtain actionable insight. The most important tool is the mind of the data analyst. Accordingly, in this course, you will explore what it means to have an analytic mindset. You will also practice identifying business problems that can be answered using data analytics. You will then be introduced to various software platforms to extract, transform, and load (ETL) data into tools for conducting exploratory data analytics (EDA). Specifically, you will practice using PowerBI, Alteryx, and RStudio to conduct the ETL and EDA processes.
The learning outcomes for this course include:
1. Development of an analytic mindset for approaching business problems.
2. The ability to appraise the value of datasets for addressing business problems using summary statistics and data visualizations.
3. The ability to competently operate business analytic software applications for exploratory data analysis.
Register for this course and see more details by visiting:
OpenCourser.com/course/02yl72/tools
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What's inside
Syllabus
Course Orientation and Module 1: Analytics Mindset
Your mind is the most important tool. Prepare your mind by learning about various mindsets and terms for approaching business analytic problems.
Read more
Syllabus
Course Orientation and Module 1: Analytics Mindset
Your mind is the most important tool. Prepare your mind by learning about various mindsets and terms for approaching business analytic problems.
Read more
Module 2: ETL and EDA Using PowerBI
PowerBI is great for both data assembly and visualization. In this module we will use PowerBI to prepare the Teca data for analysis, and then visually explore that data with various charts.
Module 3: ETL and EDA Using RStudio
Using R in RStudio to load, transform, clean, and explore data
Module 4: ETL and EDA Using Alteryx
Alteryx is great for visually documenting the data analytic workflow. In this module we will use Alteryx to assemble the Teca data and explore it with plots and tables.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Examines various data analytics software platforms, which is typical in industry settings
Develops an analytic mindset for approaching business problems, which is a core skill for data analysts
Exposes learners to a real-world business dataset, which enhances the practical relevance of the course
Imparts the ability to competently operate business analytic software applications, which is crucial for real-world implementation
Prerequisites are required, which may be inconvenient for some learners
Save this course
Save Tools for Exploratory Data Analysis in Business to your list so you can find it easily later:
Save
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Reviews summary
Tools for exploratory data analysis
Learners say this exploratory data analysis course is well-structured and engaging. Students particularly appreciate the real-world business scenarios that illustrate how each data tool can be applied. The instructors are knowledgeable and provide valuable insights.
Course includes real-world business scenarios to illustrate applications of data tools.
"I particularly appreciated the use of real-world business scenarios to illustrate the applications of each tool, which helped me understand the practical applications of what I was learning."
"The course content was well-structured, and the instructors explained each tool thoroughly, making it easy to follow along."
"Excellent course and excellent professors!"
Instructors are knowledgeable and provide valuable insights.
"But what really stood out to me was the professor's business sense."
"It was evident that he had a deep understanding of the challenges that businesses face when dealing with data"
"I learned a lot about how to approach data analysis in a business context, and I feel much more confident in my ability to use these tools to drive business decisions."
Students not receiving reviews in a timely manner.
"The course materials are brilliant, however, my not-so-goof review is because of the peers review phase."
"I submitted my answer three weeks now, and I didn't get a review yet neither positive nor negative..."
Course includes Alteryx tool explanation.
"Good course. I could make my first step with Alteryx. Thanks. I just regret that the assignement is not on Alteryx."
"Brilliant stuff from the team. Thanks for Alteryx tool explanation."
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 Tools for Exploratory Data Analysis in Business with these
activities:
Review PowerBI Tutorials
Show steps
Reviewing tutorials will help you gain a strong foundation in PowerBI before the course begins.
Browse courses on
PowerBI
Show steps
-
Find beginner-friendly tutorials on PowerBI
-
Follow the tutorials step-by-step
-
Experiment with the PowerBI interface
Review Calculus and Probability Skills
Show steps
A solid foundation in Calculus and Probability will be essential to success in this course.
Browse courses on
Calculus
Show steps
-
Revisit the concepts of derivatives, integrals, and probability distributions.
-
Solve several practice problems to improve proficiency.
Review ETL Processes
Show steps
Review ETL processes to strengthen foundational understanding of data manipulation techniques used in this course.
Browse courses on
ETL
Show steps
-
Read course syllabus and identify ETL topics
-
Review online resources or textbooks on ETL
-
Try out ETL tools (e.g., Power BI, Alteryx) in practice exercises
13 other activities
Expand to see all activities and additional details
Show all 16 activities
Data Analytics Peer Discussion
Show steps
Engage with fellow learners to discuss business problems, approach data analysis challenges, and exchange insights.
Browse courses on
Data Analytics
Show steps
-
Identify a real-world business problem to analyze.
-
Form groups and schedule meetings with your peers.
-
Develop a data analysis plan and present it to the group.
-
Analyze data and present findings to the group for feedback.
-
Document the results of the discussion and share them with the group.
ETL Practice with PowerBI
Show steps
Practice data extraction and loading using PowerBI to reinforce your understanding of the basic ETL process.
Browse courses on
PowerBI
Show steps
-
Import data from a source such as CSV or Excel into PowerBI.
-
Connect multiple data sources into a single dataset.
-
Transform data using PowerBI's built-in functions.
-
Clean data by removing duplicates and errors.
-
Model the data to create dashboards and visualizations.
Participate in Study Groups
Show steps
Working with peers can enhance understanding and provide diverse perspectives.
Show steps
-
Join or form a study group with classmates.
-
Meet regularly to discuss course topics, work on assignments, and prepare for exams.
-
Share knowledge, perspectives, and resources with group members.
Guided Tutorials on Power BI
Show steps
Enhance proficiency in using Power BI for data exploration and visualization, a key tool in this course.
Browse courses on
Power BI
Show steps
-
Find online tutorials on Power BI basics
-
Follow tutorials to create visualizations and dashboards
-
Practice using Power BI features in sample datasets
EDA with RStudio
Show steps
Gain hands-on experience with exploratory data analysis using RStudio, deepening your understanding of data exploration and visualization.
Browse courses on
RStudio
Show steps
-
Import data from various sources into RStudio.
-
Clean and preprocess data to prepare it for analysis.
-
Explore data using summary statistics and visualization techniques.
-
Create publication-ready visualizations.
-
Write code to automate and replicate your analysis.
Practice Data Visualization and Analysis
Show steps
This will help develop proficiency in data handling and interpretation.
Browse courses on
Data Visualization
Show steps
-
Use various visualization tools to create charts and graphs from datasets.
-
Analyze data to identify patterns and trends.
-
Interpret the results and draw meaningful conclusions.
Practice EDA with Sample Dataset
Show steps
Completing a project will strengthen your EDA skills and help you apply the concepts learned in the course.
Browse courses on
Data Analysis
Show steps
-
Find a small dataset related to business analytics
-
Load the dataset into PowerBI or another EDA tool
-
Explore the data using various visualizations and techniques
-
Draw insights and conclusions from the data
Practice Data Transformation Drills
Show steps
Reinforce data transformation skills through repetitive exercises, improving accuracy and efficiency in data preparation.
Browse courses on
Data Transformation
Show steps
-
Find online data transformation exercises
-
Practice transforming data using SQL or Python
-
Review solutions and identify areas for improvement
Volunteer at a Data Analytics Organization
Show steps
Practical experience can provide valuable insights and connections.
Browse courses on
Data Analytics
Show steps
-
Identify data analytics organizations or initiatives in your community.
-
Contact the organization and inquire about volunteer opportunities.
-
Participate in projects, assist with data analysis, or contribute to the organization's initiatives.
Create an Infographic on Data Analytics
Show steps
Creating an infographic will reinforce your understanding of key concepts and trends in the field.
Browse courses on
Data Analytics
Show steps
-
Research and gather relevant data and statistics.
-
Design a visually appealing and informative infographic.
-
Present your infographic to the class or a group of peers for feedback and discussion.
Develop a Data Analytics Project Proposal
Show steps
This will provide hands-on experience in defining and planning a data analytics project.
Show steps
-
Identify a business problem or opportunity that can be addressed with data analytics.
-
Define the project scope, objectives, and expected outcomes.
-
Describe the data sources and methods to be used for analysis.
-
Outline the project timeline and resources required.
-
Submit the project proposal for review and feedback.
Develop a Data Exploration Dashboard
Show steps
Apply data exploration and visualization skills to create a dashboard that communicates insights from a given dataset.
Browse courses on
Data Exploration
Show steps
-
Choose a dataset and define the scope of the dashboard
-
Use data exploration techniques to identify patterns and trends
-
Design and create visualizations to effectively present insights
-
Review and refine the dashboard for clarity and impact
Data Analysis Project on a Real-World Dataset
Show steps
Gain hands-on experience applying data analytics techniques to solve a real-world problem, reinforcing course concepts in a practical context.
Browse courses on
Data Analysis
Show steps
-
Identify a problem statement and gather a suitable dataset
-
Explore and clean the data using appropriate techniques
-
Analyze the data to identify patterns and insights
-
Develop recommendations or solutions based on the findings
-
Present the project findings and discuss the implications
Review PowerBI Tutorials
Show steps
Reviewing tutorials will help you gain a strong foundation in PowerBI before the course begins.
Browse courses on
PowerBI
Show steps
Show steps
Show steps
- Find beginner-friendly tutorials on PowerBI
- Follow the tutorials step-by-step
- Experiment with the PowerBI interface
Review Calculus and Probability Skills
Show steps
A solid foundation in Calculus and Probability will be essential to success in this course.
Browse courses on
Calculus
Show steps
Show steps
Show steps
- Revisit the concepts of derivatives, integrals, and probability distributions.
- Solve several practice problems to improve proficiency.
Review ETL Processes
Show steps
Review ETL processes to strengthen foundational understanding of data manipulation techniques used in this course.
Browse courses on
ETL
Show steps
Show steps
Show steps
- Read course syllabus and identify ETL topics
- Review online resources or textbooks on ETL
- Try out ETL tools (e.g., Power BI, Alteryx) in practice exercises
13 other activities
Expand to see all activities and additional details
Show all 16 activities
Data Analytics Peer Discussion
Show steps
Engage with fellow learners to discuss business problems, approach data analysis challenges, and exchange insights.
Browse courses on
Data Analytics
Show steps
Show steps
Show steps
- Identify a real-world business problem to analyze.
- Form groups and schedule meetings with your peers.
- Develop a data analysis plan and present it to the group.
- Analyze data and present findings to the group for feedback.
- Document the results of the discussion and share them with the group.
ETL Practice with PowerBI
Show steps
Practice data extraction and loading using PowerBI to reinforce your understanding of the basic ETL process.
Browse courses on
PowerBI
Show steps
Show steps
Show steps
- Import data from a source such as CSV or Excel into PowerBI.
- Connect multiple data sources into a single dataset.
- Transform data using PowerBI's built-in functions.
- Clean data by removing duplicates and errors.
- Model the data to create dashboards and visualizations.
Participate in Study Groups
Show steps
Working with peers can enhance understanding and provide diverse perspectives.
Show steps
Show steps
Show steps
- Join or form a study group with classmates.
- Meet regularly to discuss course topics, work on assignments, and prepare for exams.
- Share knowledge, perspectives, and resources with group members.
Guided Tutorials on Power BI
Show steps
Enhance proficiency in using Power BI for data exploration and visualization, a key tool in this course.
Browse courses on
Power BI
Show steps
Show steps
Show steps
- Find online tutorials on Power BI basics
- Follow tutorials to create visualizations and dashboards
- Practice using Power BI features in sample datasets
EDA with RStudio
Show steps
Gain hands-on experience with exploratory data analysis using RStudio, deepening your understanding of data exploration and visualization.
Browse courses on
RStudio
Show steps
Show steps
Show steps
- Import data from various sources into RStudio.
- Clean and preprocess data to prepare it for analysis.
- Explore data using summary statistics and visualization techniques.
- Create publication-ready visualizations.
- Write code to automate and replicate your analysis.
Practice Data Visualization and Analysis
Show steps
This will help develop proficiency in data handling and interpretation.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Use various visualization tools to create charts and graphs from datasets.
- Analyze data to identify patterns and trends.
- Interpret the results and draw meaningful conclusions.
Practice EDA with Sample Dataset
Show steps
Completing a project will strengthen your EDA skills and help you apply the concepts learned in the course.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Find a small dataset related to business analytics
- Load the dataset into PowerBI or another EDA tool
- Explore the data using various visualizations and techniques
- Draw insights and conclusions from the data
Practice Data Transformation Drills
Show steps
Reinforce data transformation skills through repetitive exercises, improving accuracy and efficiency in data preparation.
Browse courses on
Data Transformation
Show steps
Show steps
Show steps
- Find online data transformation exercises
- Practice transforming data using SQL or Python
- Review solutions and identify areas for improvement
Volunteer at a Data Analytics Organization
Show steps
Practical experience can provide valuable insights and connections.
Browse courses on
Data Analytics
Show steps
Show steps
Show steps
- Identify data analytics organizations or initiatives in your community.
- Contact the organization and inquire about volunteer opportunities.
- Participate in projects, assist with data analysis, or contribute to the organization's initiatives.
Create an Infographic on Data Analytics
Show steps
Creating an infographic will reinforce your understanding of key concepts and trends in the field.
Browse courses on
Data Analytics
Show steps
Show steps
Show steps
- Research and gather relevant data and statistics.
- Design a visually appealing and informative infographic.
- Present your infographic to the class or a group of peers for feedback and discussion.
Develop a Data Analytics Project Proposal
Show steps
This will provide hands-on experience in defining and planning a data analytics project.
Show steps
Show steps
Show steps
- Identify a business problem or opportunity that can be addressed with data analytics.
- Define the project scope, objectives, and expected outcomes.
- Describe the data sources and methods to be used for analysis.
- Outline the project timeline and resources required.
- Submit the project proposal for review and feedback.
Develop a Data Exploration Dashboard
Show steps
Apply data exploration and visualization skills to create a dashboard that communicates insights from a given dataset.
Browse courses on
Data Exploration
Show steps
Show steps
Show steps
- Choose a dataset and define the scope of the dashboard
- Use data exploration techniques to identify patterns and trends
- Design and create visualizations to effectively present insights
- Review and refine the dashboard for clarity and impact
Data Analysis Project on a Real-World Dataset
Show steps
Gain hands-on experience applying data analytics techniques to solve a real-world problem, reinforcing course concepts in a practical context.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Identify a problem statement and gather a suitable dataset
- Explore and clean the data using appropriate techniques
- Analyze the data to identify patterns and insights
- Develop recommendations or solutions based on the findings
- Present the project findings and discuss the implications
Career center
Learners who complete Tools for Exploratory Data Analysis in Business will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
**Data Analysts** identify business problems that can be answered using data analytics and then find and use data to solve those problems. They extract, transform, and load (ETL) data into tools for conducting exploratory data analytics (EDA) and develop an analytic mindset for approaching business problems. This course can help you develop the skills needed to be a successful Data Analyst by providing you with a strong foundation in the tools and techniques used in this field.
Data Scientist
Data Scientist
**Data Scientists** use data to build models and develop solutions to business problems. They may use a variety of techniques, including machine learning, artificial intelligence, and data mining. The skills you will learn in this course can help you build a foundation in the tools and techniques used in this field.
Actuary
Actuary
**Actuaries** use data to assess risk and uncertainty. They may work in the insurance, finance, or healthcare industries, and they use mathematical and statistical techniques to develop models that can help businesses make decisions about risk management, pricing, and other financial matters. The skills you will learn in this course will help you develop the foundation needed to assess risk and uncertainty.
Operations Analyst
Operations Analyst
**Operations Analysts** use data to help businesses improve their operations. They may analyze data on production, inventory, and other factors to identify inefficiencies and develop recommendations for improvement. The skills you will learn in this course can help you build a foundation in the tools and techniques used in this field.
Business Analyst
Business Analyst
**Business Analysts** use data to help businesses understand their customers, identify trends, and make better decisions. They may use statistical analysis, data mining, and other techniques to analyze data and develop recommendations for businesses. The skills you will learn in this course will be helpful in developing many of the skills needed to succeed in this field.
Quantitative Analyst
Quantitative Analyst
**Quantitative Analysts** use data to make investment decisions. They may work in the financial industry, and they use mathematical and statistical techniques to analyze data and develop models that can help them make informed decisions about investments. The skills you will learn in this course can help you build a foundation in the tools and techniques used in this field.
Market Researcher
Market Researcher
**Market Researchers** collect, analyze, and interpret data to understand consumer behavior. This information can be used to develop new products and services, improve marketing campaigns, and make informed decisions about business strategy. The skills you will learn in this course can help you develop a strong foundation in the tools and techniques used in this field.
Financial Analyst
Financial Analyst
**Financial Analysts** use data to help businesses make sound financial decisions. They may analyze financial statements, market data, and other data to identify trends and make recommendations about investments, mergers and acquisitions, and other financial matters. The skills you will learn in this course can help you build a strong foundation in the tools and techniques used in this field.
Software Engineer
Software Engineer
**Software Engineers** design, develop, and maintain software systems. They may work in a variety of industries, and they use a variety of programming languages and technologies to build software. This course can provide you with a foundation in the principles and practices of software engineering. By learning about software engineering best practices, you can develop a valuable skill that can be applied to a variety of jobs in the tech industry.
Web Developer
Web Developer
**Web Developers** design and develop websites. They may work in a variety of industries, and they use a variety of programming languages and technologies to build websites. This course can provide you with a foundation in the principles and practices of web development, which is a valuable skill that can be applied to a variety of jobs in the tech industry.
Database Administrator
Database Administrator
**Database Administrators** design, implement, and maintain databases. They may work in a variety of industries, and they use a variety of database technologies to manage data. This course can provide you with a foundation in the principles and practices of database administration, which is a valuable skill that can be applied to a variety of jobs in the tech industry.
Information Security Analyst
Information Security Analyst
**Information Security Analysts** design and implement security measures to protect computer systems and networks. They may work in a variety of industries, and they use a variety of technologies to protect data and systems from cyberattacks. This course can provide you with a foundation in the principles and practices of information security, which is a valuable skill that can be applied to a variety of jobs in the tech industry.
Systems Analyst
Systems Analyst
**Systems Analysts** analyze and design computer systems. They may work in a variety of industries, and they use a variety of techniques to develop and implement systems. This course can provide you with a foundation in the principles and practices of systems analysis, which is a valuable skill that can be applied to a variety of jobs in the tech industry.
Computer Programmer
Computer Programmer
**Computer Programmers** write and test code that runs on computers. They may work in a variety of industries, and they use a variety of programming languages and technologies to develop software. This course can provide you with a foundation in the principles and practices of computer programming, which is a valuable skill that can be applied to a variety of jobs in the tech industry.
Network Engineer
Network Engineer
**Network Engineers** design, implement, and maintain computer networks. They may work in a variety of industries, and they use a variety of technologies to build and manage networks. This course can provide you with a foundation in the principles and practices of network engineering, which is a valuable skill that can be applied to a variety of jobs in the tech industry.
For more career information including salaries, visit:
OpenCourser.com/course/02yl72/tools
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
Tools for Exploratory Data Analysis in Business.
Provides a comprehensive and rigorous introduction to statistical learning. It covers a wide range of topics, including linear models, regression, classification, and clustering.
Save
Provides a thorough and practical introduction to R for data science. It covers both foundational concepts and advanced techniques.
Provides a comprehensive introduction to machine learning and pattern recognition. It covers a wide range of topics, including supervised and unsupervised learning, feature selection, and model evaluation.
Save
This classic R textbook is the authoritative guide to foundational EDA methods. It is widely used in academic settings and the industry. Students taking this course will find it an invaluable reference for learning how to apply R for EDA.
Provides a comprehensive overview of data visualization principles and techniques. It will help students improve the effectiveness and impact of their data visualization.
Save
Provides a comprehensive and practical introduction to data mining using R. It covers a wide range of data mining techniques, including classification, clustering, and association analysis.
Provides a comprehensive introduction to data analysis using R, with a focus on economic applications.
This practical guide to data science thinking will help students develop the analytical mindset needed for success in the field.
Save
This thought-provoking book provides a critical perspective on the role of data science in society. It will stimulate students' thinking about the ethical implications and limitations of data analysis.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/02yl72/tools
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Effort
4 weeks of study, 3-5 hours/week
Level
Introductory
Via
Coursera
Institution
University of Illinois at Urbana-Champaign
Instructors
Ronald Guymon
Gies College of Business, University of Illinois
Language
English
Transcripts
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آذربایجان دیلی
This course belongs to a
collection
called
Business Analytics. It's comprised of six courses:
- Tools for Exploratory Data Analysis in Business (viewing)
- Introduction to Business Analytics with R
- Introduction to Business Analytics: Communicating with Data
- Machine Learning Algorithms with R in Business Analytics
- Applying Data Analytics in Accounting
- Applying Data Analytics in Marketing
Good to know
Examines various data analytics software platforms, which is typical in industry settings
Develops an analytic mindset for approaching business problems, which is a core skill for data analysts
Exposes learners to a real-world business dataset, which enhances the practical relevance of the course
Imparts the ability to competently operate business analytic software applications, which is crucial for real-world implementation
Prerequisites are required, which may be inconvenient for some learners
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