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Brandon Larkin

This course introduces you to how to use spreadsheets and SQL queries to analyze and extract data. You will learn how to practically apply the OSEMN data analysis framework and spreadsheet functions to clean data, calculate summary statistics, evaluate correlations, and more. You’ll also dive into common data visualization techniques and learn how to use dashboards to tell a story with your data.

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This course introduces you to how to use spreadsheets and SQL queries to analyze and extract data. You will learn how to practically apply the OSEMN data analysis framework and spreadsheet functions to clean data, calculate summary statistics, evaluate correlations, and more. You’ll also dive into common data visualization techniques and learn how to use dashboards to tell a story with your data.

By the end of this course you will be able to:

• Clean data with spreadsheets

• Use common spreadsheet formulas to calculate summary statistics

• Identify data trends and patterns

• Write foundational SQL statements and queries to extract data in spreadsheets

• Create charts in Google Sheets and use Tableau to visualize data

• Use dashboards to create data visualizations

You don't need marketing or data analysis experience, but should have basic internet navigation skills and be eager to participate. Ideally you have already completed course 1: Marketing Analytics Foundation and course 2: Introduction to Data Analytics in this program.

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What's inside

Syllabus

Working with Data in Spreadsheets
This week you learn the basics of spreadsheets and their usefulness in data analysis. You will also identify how to apply the OSEMN framework when working with data in spreadsheets.
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Data Analysis with Spreadsheets
This week you will learn how to clean data in spreadsheets using foundational spreadsheet functions. You will also learn how to calculate summary statistics in spreadsheets as well as how to identify data trends and relationships between variables.
Extracting Data with SQL
This week you will be introduced to SQL and how it is used in spreadsheets. You will utilize basic queries and functions for handling data with SQL.
Data Visualization
This week you will learn about common chart types and how to determine the best type of chart for the dataset you want to present. You will also learn how to create these charts using both Google Sheets and Tableau.
Creating Dashboards
In the final week you will be introduced to dashboards and how to use them to report on progress within a business setting. You will also learn how to create dashboards in Tableau and use these to tell a story when presenting your data findings.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides hands-on labs and interacive materials
Teaches skills, knowledge, and/or tools that are highly relevant to industry
Builds a strong foundation for beginners
Offers extensive background knowledge that may be useful in taking this course
May require learner to purchase additional software or tools

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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 Analysis with Spreadsheets and SQL with these activities:
Connect with Industry Professionals
Expand your professional network by reaching out to individuals working in data analysis or related fields.
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  • Identify potential mentors through online platforms, industry events, or personal connections.
  • Craft a professional email or message to introduce yourself and express your interest in connecting.
  • Schedule a virtual or in-person meeting to discuss your career goals and seek guidance.
Review Spreadsheet Basics
Start the course with a renewed understanding of spreadsheet basics and terminology.
Browse courses on Spreadsheets
Show steps
  • Revisit a spreadsheet program of your choice and explore the basic menus and functions.
  • Enter and format data in a spreadsheet, including numbers, text, and formulas.
  • Save your spreadsheet with a descriptive name and in a convenient location.
Read 'SQL Queries for Mere Mortals'
Enhance your understanding of SQL by reviewing a book specifically tailored for beginners.
Show steps
  • Read through the book, focusing on the fundamentals of SQL.
  • Complete the practice exercises provided in the book to reinforce your understanding.
Four other activities
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Complete Spreadsheet Challenges
Build your spreadsheet skills by completing a series of practice exercises.
Browse courses on Data Analysis
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  • Use a spreadsheet program to complete a set of practice exercises that focus on data analysis, spreadsheet functions, and conditional formatting.
  • Troubleshoot any errors or issues you encounter while completing the challenges.
Assist a Nonprofit with Data Analysis
Gain practical experience while contributing to a meaningful cause by volunteering your data analysis skills to a nonprofit organization.
Show steps
  • Reach out to local nonprofits and inquire about opportunities to volunteer your data analysis abilities.
  • Assist with data collection, analysis, and visualization projects to support their mission.
Develop a Data Visualization Dashboard
Deepen your understanding of data visualization by creating a dashboard to present your findings in a visually engaging way.
Browse courses on Data Visualization
Show steps
  • Choose a dataset to visualize using a data visualization tool like Tableau.
  • Create visualizations to represent different aspects of the data, using appropriate chart types and formatting.
  • Design a dashboard layout that effectively presents your visualizations and insights.
Participate in a Data Science Competition
Challenge yourself and apply your skills in real-world data analysis scenarios through participation in a data science competition.
Browse courses on Kaggle
Show steps
  • Identify relevant competitions on platforms like Kaggle or DrivenData.
  • Obtain the competition dataset and familiarize yourself with the problem statement.
  • Develop and implement a data analysis solution, using appropriate techniques and algorithms.
  • Submit your solution and evaluate your performance against other participants.

Career center

Learners who complete Data Analysis with Spreadsheets and SQL will develop knowledge and skills that may be useful to these careers:
Data Analyst
A Data Analyst collects, analyzes, interprets, and presents data to help businesses make informed decisions. This course helps build a foundation for success in this role by providing learners with the skills to clean data in spreadsheets, calculate summary statistics, identify data trends and patterns, extract data with SQL, and create data visualizations.
Business Analyst
A Business Analyst helps businesses improve their performance by analyzing their data and processes. This course may be useful for this role by providing learners with the skills to calculate summary statistics, identify data trends and patterns, and create data visualizations. These skills can help Business Analysts to better understand the data they are working with and to make more informed recommendations.
Market Researcher
A Market Researcher collects and analyzes data about consumers, markets, and competitors to help businesses make informed decisions. This course may be useful for this role by providing learners with the skills to clean data in spreadsheets, calculate summary statistics, identify data trends and patterns, and create data visualizations. These skills can help Market Researchers to better understand the data they are working with and to make more informed recommendations.
Financial Analyst
A Financial Analyst analyzes financial data to help businesses make informed decisions about investments, lending, and other financial matters. This course may be useful for this role by providing learners with the skills to calculate summary statistics, identify data trends and patterns, and extract data with SQL. These skills can help Financial Analysts to better understand the data they are working with and to make more informed recommendations.
Data Scientist
A Data Scientist uses data to solve business problems and develop new products and services. This course may be useful for this role by providing learners with the skills to clean data in spreadsheets, calculate summary statistics, identify data trends and patterns, extract data with SQL, and create data visualizations. These skills can help Data Scientists to better understand the data they are working with and to develop more effective solutions.
Operations Research Analyst
An Operations Research Analyst uses mathematical models to help businesses improve their operations. This course may be useful for this role by providing learners with the skills to clean data in spreadsheets, calculate summary statistics, identify data trends and patterns, extract data with SQL, and create data visualizations. These skills can help Operations Research Analysts to better understand the data they are working with and to develop more effective models.
Software Engineer
A Software Engineer designs, develops, and maintains software applications. This course may be useful for this role by providing learners with the skills to clean data in spreadsheets, calculate summary statistics, identify data trends and patterns, and create data visualizations. These skills can help Software Engineers to better understand the data they are working with and to develop more effective software applications.
Computer Programmer
A Computer Programmer writes and tests code to create software applications. This course may be useful for this role by providing learners with the skills to clean data in spreadsheets, calculate summary statistics, identify data trends and patterns, and create data visualizations. These skills can help Computer Programmers to better understand the data they are working with and to develop more effective software applications.
Database Administrator
A Database Administrator manages and maintains databases. This course may be useful for this role by providing learners with the skills to clean data in spreadsheets, extract data with SQL, and create data visualizations. These skills can help Database Administrators to better understand the data they are working with and to maintain their databases more effectively.
Systems Analyst
A Systems Analyst analyzes and designs computer systems. This course may be useful for this role by providing learners with the skills to clean data in spreadsheets, calculate summary statistics, identify data trends and patterns, and create data visualizations. These skills can help Systems Analysts to better understand the data they are working with and to design more effective systems.
Web Developer
A Web Developer designs and develops websites. This course may be useful for this role by providing learners with the skills to clean data in spreadsheets, calculate summary statistics, identify data trends and patterns, and create data visualizations. These skills can help Web Developers to better understand the data they are working with and to develop more effective websites.
Graphic designer
A Graphic Designer creates visual concepts, using computer software or by hand, to communicate ideas that inspire, inform, and captivate consumers. This course may be useful for this role by providing learners with the skills to create data visualizations. These skills can help Graphic Designers to better understand the data they are working with and to create more effective visual designs.
Marketing Manager
A Marketing Manager plans and executes marketing campaigns to promote a company's products or services. This course may be useful for this role by providing learners with the skills to clean data in spreadsheets, calculate summary statistics, identify data trends and patterns, and create data visualizations. These skills can help Marketing Managers to better understand the data they are working with and to develop more effective marketing campaigns.
Sales Manager
A Sales Manager leads and manages a team of sales professionals to achieve sales goals. This course may be useful for this role by providing learners with the skills to clean data in spreadsheets, calculate summary statistics, identify data trends and patterns, and create data visualizations. These skills can help Sales Managers to better understand the data they are working with and to develop more effective sales strategies.
Project Manager
A Project Manager plans and executes projects to achieve specific goals and objectives. This course may be useful for this role by providing learners with the skills to clean data in spreadsheets, calculate summary statistics, identify data trends and patterns, and create data visualizations. These skills can help Project Managers to better understand the data they are working with and to develop more effective project plans.

Reading list

We've selected 18 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 Analysis with Spreadsheets and SQL.
Provides a comprehensive introduction to data analysis with Python and Pandas. It covers data cleaning, data transformation, data visualization, and data modeling.
Provides a comprehensive introduction to data visualization with Tableau. It covers data visualization principles, chart types, and data storytelling.
Provides a comprehensive introduction to data science for practitioners. It covers data science ethics, data science tools, and data science projects.
Provides a comprehensive introduction to machine learning with Scikit-Learn, Keras, and TensorFlow. It covers machine learning algorithms, model selection, and model evaluation.
Provides a comprehensive introduction to data-driven marketing. It covers data-driven marketing strategies, data-driven marketing analytics, and data-driven marketing campaigns.
Provides a comprehensive introduction to deep learning with Python. It covers deep learning algorithms, model architectures, and model training.
Could serve as additional reading for learners interested in Bayesian statistics.
Provides a comprehensive introduction to reinforcement learning. It covers reinforcement learning algorithms, environment modeling, and policy evaluation.
Provides a comprehensive introduction to digital marketing analytics. It covers digital marketing analytics metrics, digital marketing analytics tools, and digital marketing analytics strategies.
Provides a comprehensive introduction to statistical methods for machine learning. It covers probability theory, statistical inference, and Bayesian statistics.
Provides a comprehensive introduction to social media marketing. It covers social media marketing strategies, social media marketing tactics, and social media marketing measurement.
Provides a comprehensive introduction to search engine optimization. It covers search engine optimization techniques, search engine optimization tools, and search engine optimization campaigns.
Provides a comprehensive introduction to mathematics for machine learning. It covers linear algebra, calculus, and optimization.
Provides a comprehensive introduction to content marketing. It covers content marketing strategies, content marketing tactics, and content marketing measurement.

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