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About Excel

What is Excel?

Released in 1985, Microsoft Excel is the world’s most commonly used spreadsheet program, with high estimates suggesting that the program has nearly three-quarters of a billion users globally. The application is one of the most popular computer applications in the professional world, and virtually everyone who works in an office building can benefit from knowing Excel. However, the program isn’t just for white-collar professionals like CPAs. Employees in virtually any career field where data organization is essential or productive can benefit from learning Excel. The program rewards new learners and advanced Students alike, so no matter how much Excel training you have or plan to acquire, there are practical benefits to learning the application.

students interested in learning Excel can opt to learn the basics of the program for everyday use, or they can receive more advanced training in the more complex aspects of the program. one of the reasons that Excel is so popular is that it has a robust collection of functionalities for new and experienced users, and students who only learn the basics of the program can still regularly use it to streamline their own workflow and optimize their data organization processes. Whether you are a data scientist looking to build complex, ten-thousand-cell databases or a teacher looking for the best way to organize a grade book and an attendance calendar, Microsoft Excel is an ideal program to learn.

since it is part of the Microsoft 365 suite, Excel is closely integrated with other important workplace software applications, like Microsoft Word and Microsoft Outlook. anyone learning one of these programs will be able to take advantage of their access to Excel to build a toolkit of simple but versatile computer applications that they can apply in almost any professional setting.

Reasons to Learn Excel

Organize Data

The most basic function of Microsoft Excel is as a data organization tool. At its core, a spreadsheet is just a way to help users ensure that information is organized and easy to locate when needed. Learning Excel can help users of all skill levels organize their data, regardless of how much data they happen to be working with. Whether you are working in the financial department of a corporation and dealing with thousands of rows of accounting data or keeping productivity records for your company’s two dozen employees, Excel is one of the best programs available for tracking and organizing this data. This is true even for data organization that takes place outside of the workplace. Learning Excel can be useful for people looking to track their finances better or work on projects like cataloging health and exercise logs.

Easy to Learn Basics

One reason Excel has become so popular is that it is incredibly easy to learn the basic functionalities of the program. As a tool used solely for organizing data, users are unlikely to need any training since the program has a Microsoft Word-level of beginner accessibility. Beyond this, the program’s basic features are easy to pick up. Students looking to learn how Excel can calculate functions, build simple databases, and relate data points to one Another can find a wide range of introductory materials to help them understand these features. Noble Desktop, for example, offers an Excel Level I: Fundamentals course that teaches students the basics of using Excel to create graphs, format tables, print pages, and utilize multi-page spreadsheets. Noble also offers a collection of free Excel resources and a free introductory seminar for students looking to learn the basics of the program.

Advanced Data Processing Features

Excel wouldn’t be as popular if it were just a simple spreadsheet program. Excel has a number of advanced data analysis, processing, and visualization features. Excel users can automate significant calculations and tasks by building complex functions and macros within their spreadsheets, they can turn their spreadsheets into elaborate and functional databases, and they can use data visualization tools to transform raw data into charts, graphs, and maps that data analysts can use to communicate information with stakeholders and other invested parties. Students interested in learning the more advanced functions of Excel can enroll in Noble’s Excel Bootcamp, in which students will learn these skills and more, including how to use pivot tables and macros to streamline workflow.

Easily Integrated with Other Programs and Programming Languages

another advantage of learning Excel is that it is applicable in a wide range of fields, and the databases that it is used to create can be used in many different contexts. The program has applications in data science, computer programming, financial analytics, and many other fields. Learning Excel can complement your existing skills and make a wide range of data-related work responsibilities much easier. Combined with the robust functions system and the deep customization offered by users' ability to write macros, Excel is one of the most versatile programs you can learn.

Lay the Groundwork for Future Training

Excel is a vital tool in many advanced computer science fields, including data science, machine learning, and financial technology. Each of these fields uses Excel to organize and query large datasets that can provide astute programmers and analysts with actionable insights about trends and patterns. Learning Excel is only the first step in the process of learning data science, but it is one of the most important tools in the field, so if you are aspiring to work as a data scientist, machine learning engineer, or investment analyst (among many other data-related jobs), you’ll want to start by becoming familiar with the advanced functionalities of Excel.

What Can You Do in Microsoft Excel?

As a data organization spreadsheet tool, there are a few obvious uses for Excel, but the program has a deep enough suite of tools that once you look beyond the surface, you’ll see that the program has something to offer virtually everyone. This versatility is one of the reasons that the program is so popular to learn and use since it doesn’t matter whether you are using Excel to manage hundreds of millions of dollars in a company’s financial department or managing your own extra spending money. You’ll find that Excel makes the process all that much easier.

Enter, Store and Format Data

A single MS Excel spreadsheet can be grouped with other Excel spreadsheets to form a workbook. Excel workbooks often track data over time with a worksheet to represent each month of the year, day of the week, or task. Excel spreadsheets can hold numbers, dates, times, and formulas, which can be used to calculate new data in adjacent columns.

Excel functions allow users to combine text and data into one string. For example, a row with name, date, and academic major could be combined in one column, with each characteristic separated by a comma. For this reason, Excel is also an excellent tool for formatting or cleaning data before analysis. Formulas, functions, and conditional statements (e.g., if this, then that) can transform raw data into a standard format.

Mathematical Calculations

Excel can perform basic mathematical functions like adding, subtracting, multiplying, and dividing numbers. Mathematical functions can be programmed to use specific cells or numeric values. These features are often useful for budget management or calculating a final total. These calculations can help Excel users optimize their work and create spreadsheets that automatically perform necessary calculations without rebuilding the spreadsheet each time.

Data Analysis

Users can enter data or connect MS Excel to an external database such as Bloomberg or Reuters to retrieve data automatically. Despite the intensive process required to program such features, information is often exchanged this way using Microsoft’s Dynamic Data Exchange. At an advanced level, Excel can be programmed to retrieve data from an external source, analyze this data, and update a spreadsheet automatically as changes occur.

Statistical Functions

Excel performs basic statistics on data, including mean, median, mode, permutations, and quartiles. For research studies, Excel can also analyze variance (ANOVA), regression, and factor analysis. The program can also make forecasts and predictions based on trends and display these changes in graphs.

Charts and Graphs

Excel users can generate basic visuals to support data analysis in MS Excel. The most common data visualizations created in MS Excel are bar and pie charts, histograms, and line graphs. The program can generate a standalone graph for insertion in another document or within the spreadsheet. If cell values are changed, the chart or graph will also update the data labels and the figure automatically.

• Pie charts
• Histograms
• Bar charts
• Line charts
• Area charts
• Scatter charts

Ready to master Microsoft Excel? Uncover data insights with pivot tables, advanced formulas, and charts. Expedite tasks with macros and database functions. Learn time-saving techniques, earn certification, and advance your career. Become an Excel expert today with our hands-on courses.

Start with the basics, including formulas, functions, graphs, formatting, and printing in our fundamentals class. In our intermediate course, you’ll learn more advanced functions for manipulating text and extracting information from databases, summarizing data with pivot tables, and managing large databases. In our advanced training, expand on various LOOKUP functions, learn data tables and Goal Seek, and create basic macros to automate work.

Who Uses Excel?

Data Scientists and Data Analysts

Data scientists and data analysts use Excel to create the databases they use to store, organize, and query data. Excel ensures that their databases are clean, organized, and easy to use, since without a good dataset to draw from, an analyst’s conclusion can’t be trusted. Excel’s tools for organizing and collating data are an important part of building a working database since data needs to be easy to find and stored alongside other similar data points. Data scientists will also use programming languages like Python and SQL to create applications that query this data and give it more practical functionalities. Excel is even utilized in machine learning contexts for organizing and cataloging some of the datasets used to teach machine learning programs how to read and interpret data. If you aim for a career in data science, learning how to use Excel will be an important first step because if you don’t have clean and functional datasets, you won’t be able to build programs that can use your data.

Financial Analysts

Like data analysts, financial analysts need to understand Excel to organize and construct the datasets from which they will draw insights using FinTech tools. In addition, they will need to understand how Excel can be used to automate and calculate complex financial data automatically, using function tools or macros to build dedicated Excel sheets that perform these calculations in real time. Excel is commonly used for financial record keeping and accounting, making it understandable that the tool is commonly used in financial analysis projects. An important tool used in FinTech projects programs that automatically read webpages and financial reports to input that data into an Excel spreadsheet without a human interloper so that databases can be updated fast enough to use the information. Excel is also used to create visualizations of trends in financial data and to track shifts in markets using some of the advanced analytic tools either built into Excel or built using Excel and programming languages like Python and SQL.

Project Managers

Excel is useful for more than just organizing financial and numerical data. It is also a powerful tool for tracking large projects involving significant amounts of tasks delegated to different employees or departments. Project managers may want to learn Excel to keep detailed records of who is working on what, which aspects of a project are currently being worked on, what aspects of the project have top priority and what aspects of the project have been completed (and by whom). It is also a useful tool for tracking individual and team performance and productivity, and Excel can be used for functions as simple as recording contact information in a single place. The versatility of the program makes it an ideal tool for anyone who needs to organize and manage multiple aspects of a project and wants to keep a functional, easy-to-read record of the progress that they are making. Excel’s function tools and macros can also help serve a predictive function to gauge whether or not a project is on schedule and under budget or if issues should be addressed before they become significant problems.

Office Workers

Excel is commonly associated with office work environments, and there is a reason for this. Despite its many uses in data science, financial technology, and project management contexts, it is still a powerful tool for making office bureaucracy run more efficiently and effectively. Microsoft estimates that about 66% of office workers will use Excel regularly, making it the most commonly used office application in the world. What you will use Excel for will vary from job to job, but many office workers utilize Excel to track their tasks and productivity, input important financial or business data, keep records of everything from sales and accounts receivable to taxes and clientele information. Learning even the most basic functionalities of Excel can greatly improve your productivity and make you a more valuable employee of your organization. Learning more advanced features may open up new career opportunities as you use that training to complement your existing skills.

Anyone Organizing Data

Using spreadsheets isn’t only applicable in a professional office environment. Most people regularly track some amount of data, and it can be useful to learn the basics of Excel to organize and access that data. This can be anything from using Excel to track your household budget to save money to documenting how much running you’ve done every day in preparation for a 10,000-mile run you want to participate in. This kind of data organization can be useful for helping you visualize the data you are collecting, and it can make setting and achieving goals all that much easier. Learning the basics of Excel can also help you utilize the function and formatting features to create slightly more complicated spreadsheets. For example, if your goal is to write a certain amount of words in a month for a writing project, you can build a spreadsheet that automatically calculates your pace and the pace you’ll need to stay on to reach your goal. These Excel functions make the program useful for virtually anyone who thinks that they will benefit from the organization tools offered by the application.

Excel Careers

Excel is a unique program in that it is utilized in many professional fields and work environments, but very few professionals are Excel specialists. Almost every career path that regularly utilizes Excel will require candidates to know a range of more field-specific skills. This means that career-focused students looking to learn Excel will need to learn other skills but will also have a wider range of options available for building on their Excel training.

Data scientists and data analysts regularly use Excel when engaging with databases and other large datasets. Excel is used to build the collections of data that they interpret and analyze, and without Excel, there would be no databases for querying. Scientists and analysts must learn how to use Excel to ensure that their datasets are well-organized and easy to query. Alongside learning Excel, they will need to know programming languages like Python and SQL to build the programs that utilize, query, and interpret the data that they have collected. Data analysts tend to focus more on interpreting and visualizing data for their clients, while data scientists are tasked with building the infrastructure that allows analysts to work more effectively. In the US, data scientists’ average salary is about $125,000 a year. The average salary for a data analyst is about $70,000.

Similar to data analysts, financial analysts and investment analysts will need to learn how to use Excel for basic financial record keeping and for building the databases that they use to interpret financial data. Plus, they will need to know how to read the Excel spreadsheets many companies and organizations use to track their financial data. Beyond this, they will either need to learn Python programming skills or they will need to learn programs built using Python. Financial analysts may want to receive training in machine learning algorithms, since financial data is produced so quickly, they may need to train machines to read the Excel spreadsheets they produce. Finally, aspiring financial professionals will need to learn how to use Excel’s data visualization tools to present their findings to investors and stakeholders. Financial analysts tend to work for companies to identify trends in the economic environment to help businesses make informed decisions about how to use their assets. In the US, they make about $72,000 annually. Investment analysts focus on market data and trends to help businesses and individuals identify assets and futures that make for good investment opportunities. Their average salaries are about $78,000 a year.

Project managers utilize Excel for various tasks, including organizing delegated tasks, managing costs and resources, and keeping records of what elements of the project have been completed. Excel is not a necessary tool for project managers, but it can be very useful for workflow optimization if you have experience or training with the program. To optimize these processes, project managers will need to understand project management techniques for managing human and financial resources during a project and building long- and short-term plans for accomplishing goals. They will also need to practice the soft skills necessary to lead teams and see projects through to completion. In the US, project managers make around $82,000 annually, but these salaries can vary greatly depending on the industry in which you are managing projects (software engineering pays more than construction, for example).

Since none of these professions rely strictly on Excel, you’ll need further training to hold these jobs. To learn more about the course offerings available, please visit the Noble course pages for Data Science, where you can learn Python and SQL, Finance, where you can learn FinTech, and Project Management.