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## Course Summary
+This course is an introduction to Data Analysis concepts and tools, such as Google Sheets, Python, SQL, and Tableau. Data Analysis is a multi-faceted field that includes working with business leaders, writing code, and digging through data to find solutions to issues a business is facing. As more and more companies turn to data to assist in making decisions, Data Analysis has grown exponentially. Not only is this a field that many companies need, but the analytical and learning skills you pick up in this course will serve you as you navigate today's technical landscape.
+
+We use Google Sheets to master spreadsheets as it is a tool that is available to all our students and it is robust enough for us to dive into complex datasets and start to seek out answers to important questions. To further dive into the data, we will be using Python. Python is a programming language that is used by many data analysts worldwide to perform complex functions and navigate very large datasets. Python also has other uses beyond data analystics so after learning the basics of programming and Python, you will find that you can adapt that skillset to many other stages of your learning journey. SQL is a different type of programming language that helps us navigate databases. We will learn more about what a database is later, but for now, you should know that a database holds large quantities of data. Companies store their data different ways, but by diving into the basics with SQL, we hope to give you the foundation you need to confidently explore a company's data storage and get the numbers you require. Finally, we will be using Tableau to put together visuals and graphics to help us communicate our findings to our colleagues. Tableau is one of the industry's most powerful visualization tools and we will use this tool to foster conversation about what makes a visual effective and how we can communicate our findings to the appropriate team.
+
+As you work through this course, we encourage you to remember that learning data analytics is not only valuable and challenging, it can also be fun! Every moment inspires us to keep going forward and to learn new things. You may find some concepts difficult to understand at first, but these will also be the skills you may take the most pride in mastering making the journey long and winding and rewarding.
+
+From the moment you started reading this book, you became a data analyst. We hope you enjoy your journey with us!
+
## Where this Course Leads
-## Why Python?
+Upon completion of this course, you will be capable of using different methods and techniques to collect, analyze, and summarize data. You will also be ready to start reviewing the Liftoff materials, which focus on career-readiness.
+
+While you are entering a new career in technology, we hope you use the tools you learned in this program to learn new skills. You may find yourself wanting to learn more about machine learning, complex calculations, or building bigger and better visualizations. Whatever it is, now that you have conquered the foundations of data analysis, we know you are ready for the challenge!
## Chapters
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+chapter = true
+pre = "1. "
+title = "About LaunchCode Courses"
+weight = 1
+originalAuthorGitHub = "gildedgardenia"
++++
+
+Before we dive into learning Data Analysis, we want to share with you more about our educational philosophy here at LaunchCode and how we structure our courses. We appreciate that many adults thrive in learning environments that are based on transparency and trust.
+
+You will hear us say many times that our ultimate goal is to empower you to learn how to learn. The first step in this process is for us to be clear with you on how we teach. If something is not effective for you, we encourage you to investigate why it is not effective and seek the assistance of your course staff. Perhaps the alternate phrasing about a key term in an article online will help you understand what that concept is about. Maybe a video will help drive home the importance of a certain concept. Everyone learns differently and this book serves as a starting point.
+
+Ultimately, we aim to teach the fundamental concepts and technologies we have found you will need to launch a career in data analytics. As you progress in your career, you will have to learn new concepts and technologies to succeed. We want to set you up for success, by not only teaching you the core fundamentals, but also by inspiring you to continue learning and exploring this field after you have left our classroom.
+
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We have created the course activities to make the most of your time. It is important to actively engage with each activity to maximize your learning potential. Skipping the textbook reading or falling behind on assignments can quickly lead to struggling to complete the course.
+{{% notice blue "Note" "rocket" %}}
+
+As you read through a chapter, you may realize you already know a lot about that topic. You still need to participate fully in the course activities. Each assignment builds on the course activities and doing the course activities will help you better understand the graded assignment requirements which is vital to passing the graded assignment.
+
+{{% /notice %}}
+
### Textbook Reading
Think of this textbook as your first destination in your learning journey. In addition to reading, this text includes small questions that can help you reinforce your understanding of the new material. At the beginning of the chapter, you will find your goals for the chapter and the list of key terms to guide your note-taking process. Reviewing your notes from a given chapter before moving on to the next is another great way to make the most of your learning potential. At the end of many chapters, we have recommendations of additional resources on the given topic. If you are unsure about what you just read, try reviewing those resources and making note of questions you want to ask during classtime.
### Exercises
-Towards the end of most of the textbook chapters, you will find a a page of exercises. These are small coding problems and are a chance for you to implement what you have just learned. While exercises do not count towards your final grade in the class, it is essential to practice in order to reinforce your understanding of the new concepts. We recognize that working on something that is graded can be stressful and stress can actually inhibit your ability to learn! Make the most of every opportunity to practice coding without being graded on the end result!
+Towards the end of most of the textbook chapters, you will find a page of exercises. These are smaller problems and are a chance for you to implement what you have just learned. While exercises do not count towards your final grade in the class, it is essential to practice in order to reinforce your understanding of the new concepts. We recognize that working on something that is graded can be stressful and stress can actually inhibit your ability to learn! Make the most of every opportunity to practice without being graded on the end result!
### Studios
-Many chapters also include a studio. These studios are going to be more difficult than exercises, but these activities are designed to be done in class and with a smaller group, so you can pair with other students and ask questions of course staff as you navigate these challenges. Some of the studios are not about coding, but are about goal setting, building confidence, and other equally important topics when pursuing a new career. We encourage you to participate in these activities to your best abilities!
+Many chapters also include a studio. These studios are going to be more difficult than exercises, but these activities are designed to be done in class and with a smaller group, so you can pair with other students and ask questions of course staff as you navigate these challenges. We encourage you to participate in these activities to your best abilities!
### Graded Assignments
Graded assignments are larger projects where you demonstrate what you have learned and challenge yourself. Assignments oftentimes cover multiple lessons, but we encourage you to get started as soon as you can instead of waiting until the end. The assignments are broken down into different tasks, so when you first start, read through every task and determine what you can start working on right away and what you may need to wait on.
+
+### Final Project
+
+The final project of this course is a full data analysis project on a topic which interests you. We have set up several checkpoints for you to complete throughout the course so that you can stay on top of each stage. At the end of the course, you will be sharing your project work with your course staff and classmates!
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+++
-This page covers what to expect during in-class time for students enrolled in a LaunchCode blended learning course. Students taking an independent learning course may skip this page.
-
We only have a short amount of time in class to learn a lot, so using a **blended learning model** helps us make the most of our time in this course. A blended learning model incorporates in-class learning with online materials like this textbook.
## In-Class Time
In class, you join fellow students on the same learning journey as you. We encourage students to engage, interact, and encourage each other throughout the class.
-In-class time is run by an instructor and teaching assistants. This dedicated staff facilitates the activities and provides support to the students.
+In-class time is run by an instructor and instructional assistants. This dedicated staff facilitates the activities and provides support to the students.
## Large Group Time
@@ -20,4 +18,4 @@ During the large group time, the whole class participates in the lesson, led by
## Small Group Time
-After the large group time, we break up into small groups, each led by a teaching assistant. During small group time, we do our studios. This is a time to ask for individual support if you need it. It is meant to be a place where you can feel comfortable talking openly about concepts you are struggling with.
+After the large group time, we break up into small groups, each led by a instructional assistant. During small group time, we do our studios. This is a time to ask for individual support if you need it. It is meant to be a place where you can feel comfortable talking openly about concepts you are struggling with.
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Throughout this book, you will find a variety of different sections and practice exercises. We are writing this guide to help you make the most of the book.
+## Learning Objectives and Key Terms
+
+The cover page for each chapter outlines the learning objectives for that chapter as well as the key terms you need to make note of as you read the chapter. You can use this section to guide your reading and guide the questions you may want to ask of your instructor or instructional assistants. For example, if one of the objectives for the chapter is "Set up a formula in a spreadsheet to sum multiple values in a column" and after completing the reading and exercises, you are still not sure how to do so, you should ask your instructional assistant before class or ask during the in-class time. You never know who may have the same question!
+
## Concept Checks
Many pages end with a “Check Your Understanding” header. This section is full of questions for you to double check that you understand the concepts in the reading. Although your score does not count towards your final grade in the class, you should use it to help evaluate your understanding of the main concepts. After you read the chapter, you will take a quiz in Canvas that includes all of these questions.
@@ -18,8 +22,4 @@ The label “Try It” signals an example that includes code you can modify and
## Supplemental Content
-Occasionally, you will find a link to another resource. While not required reading, these additional resources can boost your learning with videos, other examples, and more information about the code.
-
-## Python in Context
-
-Our approach is different from other ways you can learn Python. The book focuses on programming fundamentals. These fundamentals are problem-solving and transferable concepts. While we will cover the exact way to perform certain tasks in Python, we want to remind you that these tasks are relatively common and many programming languages have ways to carry them out.
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+Occasionally, you will find a link to another resource. While not required reading, these additional resources can boost your learning with videos, other examples, and more information about the code. The home to most of the supplemental content is each chapter's "Next Steps" page. This page has articles that either serve as an additional resource in case you feel that you are not confident about any of the learning objectives or serve as a stepping off point if you want to explore a topic more.
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+chapter = true
+pre = "3. "
+title = "Intro to Spreadsheets"
+weight = 3
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+
+## Learning Objectives
+
+- Introduce what datasets and spreadsheets are and what Google Sheets is.
+- Talk about why we are using Google Sheets for this class.
+- Be able to add new columns and rows to an existing spreadsheet.
+- Be able to add a new sheet to an existing spreadsheet.
+- Be able to use quick actions to do calculations.
+- Be able to set up a formula for a cell
+
+## Key Terminology
+
+Here is a list of the key terms for this chapter broken down based on the page the term first appears on.
+
+### Getting Started with Google Sheets
+
+1. dataset
+1. cell
+1. header row
+
+
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+title = "Next Steps"
+weight = 2
+originalAuthorGitHub = "gildedgardenia"
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+
+Now that you have started to learn more about spreadsheets, you may want to continue to practice making and editing spreadsheets. Another benefit of using Google is that the team there has added free resources on Google Sheets and practice opportunities to the [Google Workspace Learning Center](https://support.google.com/a/users/answer/9282959).
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+title = "Reading"
+weight = 1
+originalAuthorGitHub = "jwoolbright23"
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+
+## Reading Content
+
+{{% children %}}
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+title = "Adding onto an Existing Spreadsheet"
+weight = 2
+originalAuthorGitHub = "gildedgardenia"
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+
+## Adding Rows and Columns to a Spreadsheet
+
+As you work more on spreadsheets, you may find that you want to add a row or column in the middle of the spreadsheet. Maybe you realized that another column was necessary or you were importing data and a row was lost in the process.
+
+Let's revisit our Car Info workbook. While we already have some great data stored about the two cars, we need some more information.
+
+1. We want to insert a column between "Model" and "Car Mileage". Right-click on the D for the "Model" column and select *Insert 1 column right*. Alternatively, you can right-click on the E for the "Car Mileage" column and select *Insert 1 column left*.
+1. You now have an empty column that is the column E and "Car Mileage" is now column F. Type "Current Value" in E1.
+1. Add the current value for both the cars you created on the previous page.
+
+You can do the same for rows by right-clicking on the row number and inserting a new row above or below the one you selected.
+
+## Adding Another Spreadsheet to an Existing Workbook
+
+Now we want to add some additional information about the two cars. We want to add a maintenance log for each car so we can track how much we spent on the car in one year. This information would not make sense on the current spreadsheet so we are going to add a second one to our Car Info workbook.
+
+At the bottom of the page, you will see a tab that says "Sheet1" next to a plus sign and a hamburger menu (three horizontal lines stacked on top of each other). Let's rename "Sheet1" by right-clicking and selecting *Rename*. Give it the new name, "Overview" and hit *enter* or *return*.
+
+We are now ready to add a maintenance log for one of our cars. For example, we are going to add one for a car nicknamed Bob.
+
+1. Hit the plus sign in the bottom left-hand corner. We have a new sheet called "Sheet2"
+1. Rename the new sheet by right-clicking. For this exercise, we will rename ours to "Bob Maintenance".
+1. Add the following to the first row in this order: "Task", "Date", "Cost".
+1. Add one maintenance item to the spreadsheet. For example, we might add "Brake repair", 12/23/23, and 1000.
+
+From here, we can continually add more data and spreadsheets to our workbook as the need arises.
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+title = "Calculations"
+weight = 3
+originalAuthorGitHub = "gildedgardenia"
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+
+
+Right now, we have a lot of information stored in our spreadsheet, but we haven't fully unlocked all that we can do with spreadsheets. One feature that many data analysts make use of is formulas. Formulas in spreadsheets enable us to run a mathematical calculation using the value of a cell. We can sum multiple cells together or multiple a cell's value by 3.
+
+To write a formula, we can start by typing a `=` in the cell. This tells Google Sheets that we are going to write a formula. If we want to multiple the value of B4 by 3, then we type `=B4*3`. When you are done with your formula you can hit *Enter* to see the result.
+
+Let's explore some ways we can use formulas in Car Info.
+
+## Setting Up a New Column Based on a Formula
+
+Sometimes, we want to set up a whole column where each value is the result of a formula. In the case of cars, since we have to pay property taxes on our vehicle, we want to set up a column for the tax value of each car.
+
+1. In the "Overview" tab, add a new header to column G called "Tax Value".
+1. We checked the tax rate and on cars right now, it is 2%, so the taxes we owe would be 2% of the current value.
+1. Starting with G2, write in that cell the formula for finding the tax value of the car. As you write the cell identifuer for the current value of row 2, Google Sheets will highlight the cell that you are referencing which can serve as a helpful visual reminder of what the formula is going to be using.
+1. Now we want every row in column G to accurately reflect the tax value of the car. To copy the formula and not the value in G2, hover your mouse over the bottom right corner of G2 and you will see a plus sign appear. Click and drag down to G3. Release once both cells are highlighted and you should see 2% of E3 in G3. To confirm, click on the cell to see what the formula looks like.
+1. If you want to add another row, you can click and drag down as you did above.
+
+The benefit of setting up a formula like this is that we don't have to worry about a human miscalculating and even more importantly, these cars are going to depreciate in value so that "Current Value" column is going to look different over time. Instead of us have to updating both the current value and the tax value when the car depreciates, we can update the current value and the tax value will update to reflect the change.
+
+## Setting up a constant
+
+Just as the current value may change, so may the tax rate. However, we don't want to go through every cell and make sure the formula is updated. We also don't want to add a new column with the tax rate because that is going to involve some extra data entry. We want to make this as simple as possible!
+
+1. Over in J6, let's add "Current Tax Rate" and in K6, we will add 0.02.
+1. We want to reference K6 in our formula for the tax value, but we want it to be constant for each row. We can reference K6 with dollar signs to designate that the value is a constant in our formula, like so `$K$6`. Try updating your formula in G2 and seeing if you get the same number.
+1. Once you are satisfied, click and drag down to G3 to update that formula. You won't see the number change, but you can click on the cell to see that the formula is updated and that both values are based on the current tax rate.
+
+## Connecting to Another Sheet
+
+Finally, in a formula, you may want to reference a cell in another spreadsheet. In the case of Car Info, we want to take the sum of all the maintenance tasks and place it in a column on our Overview spreadsheet.
+
+{{% notice blue "Note" rocket %}}
+ For now, we will be importing one cell at a time. We can reference a range of cells in a formula using `IMPORTRANGE`, which we will see later in this class.
+{{% /notice %}}
+
+1. Add another header to H for "Maintenance Budget Used"
+1. To reference another spreadsheet in a formula, we first need to type the name of the spreadsheet, an exclamation point, and then the cell. If we have a spreadsheet named "Budget" and we want to reference A1 in that spreadsheet, then we would write `Budget!A1`. If there are spaces in our spreadsheet name, then it should be wrapped in single quotes like `'Budget 2024'!A1`.
+1. We want to track how much of each car's maintenance budget has been spent. Since there is only one maintenance job for one car in another spreadsheet, we are going to set up a formula and NOT click and drag it to the second car. Use the above to reference the cost of the one maintenance task and divide it by a budget of 2000 to see how much we have used so far.
+
+With formulas, the possibilities are endless! We can also make use of the *Quick Calculations* menu to easy set up sums and averages.
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+title = "Getting Started with Google Sheets"
+weight = 1
+originalAuthorGitHub = "gildedgardenia"
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+
+Spreadsheets are a technology that is derived from accounting ledgers called "spread sheets". These ledgers were based on a grid of columns and rows. While the technology is based on accounting, there are many more uses for spreadsheets than just to track money. People make spreadsheets to track their fantasy sports leagues, plan trips, and assemble their meal plan for the week. Many software companies offer spreadsheet software, such as Microsoft Excel, Google Sheets, and Apple's Numbers. Spreadsheet software may have different functionalities, but at the level we are going to be learning about spreadsheets, most software works very similarly. We are going to be using Google Sheets for this class because it is readily available to all our students and makes it simple for you to share your work with your course staff and submit assignments. Spreadsheets also serve as a place where we can store smaller datasets. A **dataset** is a collection of data and can hold numbers, dates, text, and more.
+
+To get started with Google Sheets, you need to first sign up for a [Google account](https://support.google.com/accounts/answer/27441?hl=en) and select that you are making an account *For yourself*. Once you have created an account or if you were already a Google account owner, head to the home of [Google Sheets](sheets.google.com).
+
+You can then create a new spreadsheet or use one of Google's templates. For now, we are going to focus on creating new spreadsheets so we can learn more about the underlying structures of these popular templates. Let's set up a new spreadsheet!
+
+1. Click *Blank Spreadsheet*.
+1. Right now, in the upper left-hand corner, the workbook name is "Untitled Spreadsheet". Click on the workbook title to change the name to "Car Info".
+1. The columns in the spreadsheet are labeled by letters and the rows of the spreadsheet are labeled by numbers. A **cell** of a spreadsheet is referred to by the column number and then the row number, so the first cell in the spreadsheet in the upper left-hand corner is A1. In this cell, put the word, "Car Mileage".
+1. Oftentimes, row 1 is referred to as the **header row**. The header row is where we add labels for what type of data will be stored in that column. Column A is where we might store other identifiers that help us determine what is going on with each row. If we wanted to store just one car's information in this spreadsheet, we might need any labels in column A, but if we wanted this spreadsheet to work for multiple cars, then we would need to add some additional identifiers in column A. Let's make it work for multiple cars by doing that next!
+1. We can move the information in a cell by cutting and pasting. Click on cell A1 and for *Mac users*, hit command+x at the same time. For *Windows users*, hit control+x at the same time. You are now ready to move this info to a different cell. We are going to move this info to cell E1 by selecting that cell and pasting with command+v for *Mac users*, or control+v for *Windows users*.
+1. Now we can add additional headers for our car information. In the following order, starting at A1, add the following labels to the header row: "Nickname", "Year", "Make", and "Model".
+1. Add the info for two cars to your spreadsheet by filling rows 2 and 3.
+
+One of the benefits of a spreadsheet is that Google Sheets can help format our data for us. If we want to dedicate a cell to storing dates or currency values, we can click on the cell and then click on *Format* > *Number* and select the type of number we want to store. This helps us understand what is in the column and allows us to apply additional rules if necessary. For instance, if we are working on a spreadsheet about taxes, we may want to use the *Rounded Currency* option for the cells where we are adding the values from a W2, since all tax software rounds the numbers as well.
+
+Now that your spreadsheet is set up, you are ready to dive deeper into all the functionalities that spreadsheets can offer.
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-title = "Why Learn Data Analysis?"
-weight = 1
-originalAuthorGitHub = "jwoolbright23"
-+++
-
-In today’s world, it is nearly impossible to go through the day without hearing about data. During the news, you may hear about how many visitors went to a local state park. During the work day, you may hear about how much revenue was made that day. While sitting at home, you may crack open your planner and start your monthly budget, updating personal spreadsheets as you go. This world and your life comes with so much data.
-
-Data Analysis is a field in tech that focuses on finding data, digging through it, and reporting on the key takeaways. In the case of your monthly budget, finding data might include locating the monthly statements from your bank and other financial institutions. Digging through the data encompasses the part of the process where you start looking through transactions for your regularly occurring monthly expenses. Reporting that data is when you create graphs going over debt plans. On a larger scale, this process and the people who perform it are some of key members of an organization. Businesses today rely on data analysts to find the information needed to make decisions and chart paths forward.
-
-Data Analysts use a wide variety of tools to accomplish these tasks. They code, use reporting software such as Tableau, and create databases. While this book focuses on how to use these tools as a data analyst, each tool is a valuable skill on its own. The tools used in this book include Python, various Python tools specifically geared towards data analysis, Azure Data Studio, and Tableau. Before reading further, you should bookmark this list of all the necessary software and tools for the class.
-
-As you get to know these tools better, you will begin to see that while one tool can do many things, each tool is created to excel at one thing. In the case of learning data analysis, we first teach you how to code in Python so you can effectively use Python and its packages. As a data analyst, you may find yourself having to perform complex calculations and parse through large datasets, which is something Python is very good at. Azure Data Studio allows you to connect to SQL databases and write SQL queries, which is another key part of a data analyst’s work. Tableau can perform some calculations, as you will see, but it is best at creating beautiful visualizations. When you are working as a data analyst, visualizations are integral to creating an effective report of your work.
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chapter = true
-pre = "1. "
-title = "Introduction"
-weight = 1
-originalAuthorGitHub = "jwoolbright23"
+pre = "2. "
+title = "Our Approach to Learning Data Analysis"
+weight = 2
+originalAuthorGitHub = "gildedgardenia"
+++
## Why Learn Data Analysis?
@@ -12,6 +12,6 @@ In today’s world, it is nearly impossible to go through the day without hearin
Data Analysis is a field in tech that focuses on finding data, digging through it, and reporting on the key takeaways. In the case of your monthly budget, finding data might include locating the monthly statements from your bank and other financial institutions. Digging through the data encompasses the part of the process where you start looking through transactions for your regularly occurring monthly expenses. Reporting that data is when you create graphs going over debt plans. On a larger scale, this process and the people who perform it are some of key members of an organization. Businesses today rely on data analysts to find the information needed to make decisions and chart paths forward.
-Data Analysts use a wide variety of tools to accomplish these tasks. They code, use reporting software such as Tableau, and create databases. While this book focuses on how to use these tools as a data analyst, each tool is a valuable skill on its own. The tools used in this book include Python, various Python tools specifically geared towards data analysis, Azure Data Studio, and Tableau. Before reading further, you should bookmark this list of all the necessary software and tools for the class.
+Data Analysts use a wide variety of tools to accomplish these tasks. They make spreadsheets, code, use reporting software such as Tableau, and create databases. While this book focuses on how to use these tools as a data analyst, each tool is a valuable skill on its own. The tools used in this book include Google Sheets, Python, various Python tools specifically geared towards data analysis, Azure Data Studio, and Tableau. Before reading further, you should bookmark this list of all the necessary software and tools for the class.
-As you get to know these tools better, you will begin to see that while one tool can do many things, each tool is created to excel at one thing. In the case of learning data analysis, we first teach you how to code in Python so you can effectively use Python and its packages. As a data analyst, you may find yourself having to perform complex calculations and parse through large datasets, which is something Python is very good at. Azure Data Studio allows you to connect to SQL databases and write SQL queries, which is another key part of a data analyst’s work. Tableau can perform some calculations, as you will see, but it is best at creating beautiful visualizations. When you are working as a data analyst, visualizations are integral to creating an effective report of your work.
+As you get to know these tools better, you will begin to see that while one tool can do many things, each tool is created to excel at one thing. In the case of learning data analysis, we start with spreadsheets and Google Sheets, then teach you how to code in Python so you can effectively use Python and its packages. As a data analyst, you may find yourself having to perform complex calculations and parse through large datasets, which is something Python is very good at. Azure Data Studio allows you to connect to SQL databases and write SQL queries, which is another key part of a data analyst’s work. Tableau can perform some calculations, as you will see, but it is best at creating beautiful visualizations. When you are working as a data analyst, visualizations are integral to creating an effective report of your work.
diff --git a/content/learning-data-analysis/reading/_index.md b/content/learning-data-analysis/reading/_index.md
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+title = "Reading"
+weight = 1
+originalAuthorGitHub = "gildedgardenia"
++++
+
+## Reading Content
+
+{{% children %}}
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diff --git a/content/learning-data-analysis/reading/how-much-math/_index.md b/content/learning-data-analysis/reading/how-much-math/_index.md
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+title = "How Much Math You Need"
+weight = 6
+originalAuthorGitHub = "gildedgardenia"
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+
+Before we dive into the world of data, we want you to know there will be some math involved in your journey. Here is a checklist of the math concepts you may want to be familiar with before diving in:
+
+1. Averages
+1. Medians
+1. Max and min
+1. Standard deviation and other measures of variation
+1. Solving for a single term in algebra
+1. Solving for multiple terms in algebra
+
+If you feel shaky on any of these concepts, here are some of our favorite math resources:
+
+1. [Introduction to Statistics](https://www.youtube.com/watch?v=XZo4xyJXCak&list=PL0o_zxa4K1BVsziIRdfv4Hl4UIqDZhXWV&index=1)
+1. [Algebra Basics - Solving 1-Step Equations](https://www.youtube.com/watch?v=l3XzepN03KQ&pp=ygUdYWxnZWJyYSBzb2x2ZSBmb3Igc2lnbmxlIHRlcm0%3D)
+1. [Algebra Basics - Solving 2-Step Equations](https://www.youtube.com/watch?v=LDIiYKYvvdA&pp=ygUfYWxnZWJyYSBzb2x2ZSBmb3IgbXVsdGlwbGUgdGVybQ%3D%3D)
+
diff --git a/content/introduction/reading/why-learn-code/_index.md b/content/learning-data-analysis/reading/why-learn-code/_index.md
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originalAuthorGitHub = "jwoolbright23"
+++
-Many might think that every data analyst’s career starts with learning the ins and outs of spreadsheets, but spreadsheets are not the only way to start off on your journey. We start with learning to code for a few reasons.
+Many might think that every data analyst’s career solely composes of spreadsheets, but spreadsheets are not the only way to explore data. We will also learn to code for a few reasons.
-First, as an analyst, every program you use is allowing you to communicate instructions to a machine. Whether it is writing Python code or using a drag-and-drop menu in Tableau, you are asking a machine to perform certain necessary tasks to help you achieve a goal. Code is the undercurrent of all of these programs. By learning to code first, you are learning the most universal aspect of all of the tools you will use throughout your career. With this particular knowledge, you will also be better prepared to adapt to the needs of your workplace. Not every company uses Tableau and Azure Data Studio. Some may insist you use a code-centric tool like Matplotlib for visualizations.
+First, as an analyst, every program you use is allowing you to communicate instructions to a machine. Whether it is writing Python code or using a drag-and-drop menu in Tableau, you are asking a machine to perform certain necessary tasks to help you achieve a goal. Code is the undercurrent of all of these programs. By learning to code, you are learning the most universal aspect of all of the tools you will use throughout your career. With this particular knowledge, you will also be better prepared to adapt to the needs of your workplace. Not every company uses Tableau and Azure Data Studio. Some may insist you use a code-centric tool like Matplotlib for visualizations.
Through learning to code, you will also gain confidence in handling errors. Errors come up when working with any software program and they also come up when handling data. All it can take is one typo to throw off your analysis of a dataset.
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+title = "Why Learn Spreadsheets?"
+weight = 1
+originalAuthorGitHub = "gildedgardenia"
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+
+Spreadsheets are a great way for us to begin to explore data. Many data analysts use spreadsheets in their day-to-day work in conjunction with other tools. Spreadsheets store data in a grid of columns and rows. Spreadsheet software, such as Google Sheets or Microsoft Excel, allow the user to click through this data, run calculations, and create visuals to illustrate what is happening in the data. If you have worked with spreadsheets before, you might have seen multiple spreadsheets or tabs within one project. Those projects are oftentimes called workbooks.
+
+For this course, we will be using Google Sheets. Google Sheets is free to use to anyone with a personal or business Google account. We can filter data, make graphs, and compose formulas to complete our analysis of what is happening in the data. As you progress further in your career, you may want to explore Microsoft Excel too. As we stated in the introduction, we are here to give you the foundations you need to launch your learning. Google Sheets will help you understand the foundations of spreadsheets and key functions that you need to use. If you are not already a Microsoft user, you may find Microsoft Excel to be cost-prohibitive so by using Google Sheets, you can take the time to decide if you would like to save up for a license.
+
+
diff --git a/content/learning-data-analysis/reading/why-learn-sql/_index.md b/content/learning-data-analysis/reading/why-learn-sql/_index.md
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+title = "Why Learn SQL?"
+weight = 4
+originalAuthorGitHub = "gildedgardenia"
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+
+Structured query language or SQL is the coding language we will be using to interact with databases. While spreadsheets can hold a lot of data, a database can hold even more. Databases can also establish relationships between data. SQL refers to a family of languages that all do this same task. T-SQL or Transactional SQL is the one we will be focusing on for this course.
+
+At the level that we are working, you may not notice any differences between T-SQL and other forms of SQL. The differences get larger the deeper you get into your SQL learning journey so it is important that you make sure that you are focusing on T-SQL when looking up alternate resources.
+
diff --git a/content/learning-data-analysis/reading/why-learn-tableau/_index.md b/content/learning-data-analysis/reading/why-learn-tableau/_index.md
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+title = "Why Learn Tableau?"
+weight = 5
+originalAuthorGitHub = "gildedgardenia"
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+
+The final tool we will be covering in this course is Tableau. Tableau is a powerful tool for putting together data visualizations. One key part of being a data analyst is sharing your findings with other analysts and business leaders.
+Visualizations can help portray to these other users what is going on with the data.
+
+While we work on Tableau, we will be focusing not just on setting up these visualizations, but also learning more about what makes a good visualization. What style of visualization helps tell the story and other tips and tricks to strengthen your presentations so if you end up using another tool, like PowerBI, on the job, the concepts you learned while working on visualizations in Tableau will transfer over.
+
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