There has never been a better time to add ‘Data Analytics’ as a skill to your resume. Data analysts are critical to the success of most organizations today, and experts are increasingly concerned about a talent shortage in the field. If you're considering investing in a data analytics certification, you'll want to know: Is a data analytics certification really worth it? And, if so, which data analytics certification programs should you look into?
In this Excel Data Analyst ultimate guide we will talk about who Excel Data Analysts are, what they do exactly, how much they earn, and finally, how to become one.
Excel is a spreadsheet that Microsoft created for various operating systems such as Windows, macOS, Android, and iOS. It includes a variety of features such as calculation, graphing tools, pivot tables, and a macro programming language known as Visual Basic for Applications. It is a part of the Microsoft Office suite of applications.
In practice, the business world has embraced Excel because it is smooth, effective, and flexible in its application. Excel is used in some capacity by nearly every major business.
It is appropriate for all types of business processes, including sales, marketing, accounting, finance, HR, and others. It has become an important part of any business because it can be customized and produces effective results quickly.
Read on to find out how getting a certification in Excel can open new doors of opportunities for you.
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What this Excel Data Analyst ultimate guide covers
Knowing how to use Microsoft Excel is so common these days that it barely merits a line on our resumes. But, let's be honest: how well do you know how to use it? You may be able to enter numbers and add up cells in a column, but that won't get you very far when it comes to reporting on your metrics.
While you might have really good intuition, if you start making business decisions based on your gut feeling without looking at what the data is telling you, you are not going to get very far in your career.
You've probably already been tasked with identifying trends in customer survey results, conducting content topic analyses, or pulling sales data to calculate return on investment. What is the link between all of these things? They necessitate a little more Excel knowledge than we were taught in school.
This is why we have put together this comprehensive guide on Excel for Data Analysts. It will cover the following:
What is MS Excel and why is it so much in demand?
What are Data Analysts and what do they do?
Data Analyst job outlook and salary
What kind of jobs require Data Analysis with Excel
Technical skills every data analyst should have
Important ways in which you can use Excel for data analytics
And finally, some Unmudl tips to master Excel
Whether you want to make more beautiful charts, finally understand pivot tables, or finish your first VLOOKUP, this guide will teach you everything you need to know to make better marketing decisions in less time.
So let’s jump straight in and start arming you with the knowledge to make you an expert Excel Data Analyst.
Excel is a useful and powerful data analysis and documentation program developed by Microsoft, the people that bought you Windows. It is a spreadsheet program with a number of columns and rows, with each intersection of a column and a row referred to as a "cell."
Each cell contains one piece of information or one point of data. You can make information easier to find and automatically draw conclusions from analyzing this data by organizing it in ways that display relevant trends.
Simply put, Excel is a place where you can store all your data and it can then find patterns within the data for you to draw conclusions. For example, let’s say Daniel is an SEO specialist.
Now if he has the names of all his clients in an Excel sheet and he has the dollar value of all the business they have given him this year, he can find out with a press of a button who his top 10 clients are.
Not only that, with the help of Excel, Daniel can figure out if any of his clients give more business during specific seasons which can help him manage his workload better. A travel and tours client, for example, demands more content during Summers when their business peaks.
The power of Excel doesn’t end there. If he wants, Daniel can also keep a spreadsheet where he records what he is paying his employees, his official expenses, articles being submitted by his writers and the list goes on.
In fact, he can even use Excel to plan his own Summer vacation which he has easily earned thanks to his Excel certification!
Excel is included with Microsoft Office, the world’s most popular office productivity application suite. This has helped it become the standard analytical tool in offices all over the world. There is a massive user base for Excel, which means there are plenty of resources to assist you.
There is a wealth of information available online or from your office Excel expert.
Excel is user-friendly, and it is simple to learn the fundamentals. There is no code to execute, and the data is immediately visible.
You can directly type in information, giving you a sense of control. Adjusting data, sorting, and filtering are all simple tasks in Excel. With the click of a mouse, you can change the formatting. You can even make some surprisingly appealing charts and dashboards.
Here are 10 key reasons why it has such a huge following of 750 million users worldwide:
1. Best way to store data
Even if you don’t want to do complicated analysis, Excel is still the easiest and most flexible way to store data. You can use it to keep track of employee overtime, the reps you do for each exercise at your gym, or how much money you owe people.
2. You can perform calculations with ease
From the simplest to the most complex calculations, Excel can handle it all. With a click of a mouse button, it can tell you the total number of calories you have been consuming (provided you are recording the daily intake data) or it can tell you what is the probability of a particular baseball player to score during the next match based on his last 6 years of performance data.
3. All the tools for data analysis
The primary goal of having data is to analyze it and gain insights from it. The good news is that Excel has some of the most powerful data analysis tools available.
As an example, assume you have data with tens of thousands of rows; you can create a summary of all this data by inserting a pivot table into that data. A PivotTable is a powerful tool for calculating, summarizing, and analyzing data that allows you to see comparisons, patterns, and trends.
4. Easy to data visualizations with charts
No matter how smart you are, rows and rows of data can quickly overwhelm you. Excel has many built-in features that can help you visualize large amounts of data with things like pie charts, scatter charts, heat maps, etc.
5. You can print reports easily
You can define templates to print regular reports with minimum effort. For example, you can set the template for salaries once and all you have to do is press the print button every month.
Excel will automatically go back to look at the data for the last month, calculate overtime of employees, days employees were absent, the days they are allowed to be absent… all the calculations seamlessly in the background within a second, and out pops a report without any effort.
6. So many free templates to use
Thanks mainly due to its popularity, there are thousands of ready-made templates available online to help you do your job quickly with the minimum of effort.
7. You can code to automate
If you are an advanced user, VBA (visual basic for applications) is Microsoft Office's own coding language that allows you to write code for almost all of the activities that you perform manually in Excel.
This feature can help you automate repetitive tasks making your job easier.
8. Transform and clean data
If you work with data a lot or know someone who does, there are a lot of situations where you have to deal with messy data that needs to be cleaned before you use it.
Cleaning and transforming data used to consume a significant amount of a Data Analyst’s time and was a laborious process.
Excel has simplified this considerably, yet another reason why it is so popular.
These are just some of the reasons why Excel has created such a demand for itself.
Now that we have understood what Excel is and what it can do, let’s talk about what Data Analysts are and what they do.
What does a data analyst do?
Data analysts play an important role in the operations of businesses in a variety of industries. Data analysts contribute to their organizations in healthcare, finance, consumer goods, and almost every other sector by processing, visualizing, and translating data into actionable insights.
Demand for data analysts will continue to rise over the next ten years (and beyond), particularly in the healthcare sector. So, what exactly do data analysts do on a daily basis, and how do you go about becoming one? First and foremost, it is critical to define data analytics.
What exactly is data analytics?
Data analytics is the discipline of organizing, interpreting, and displaying data in a useful manner for a business. Although the field has evolved significantly over the last few decades, the primary goal of data analytics has always been to extract valuable insight from data.
The data itself can be quantitative or qualitative, and it can be further classified as categorical data (language, gender, etc.), ordinal data (ordered ratings such as customer satisfaction), and so on.
Analytic methods, regardless of the type of data, aid in the processing and interpretation of often complex information.
The industry you are working in as a data analyst also impacts your salary a lot. In May 2021, the following were the median annual wages for operations research analysts in the top industries in which they worked:
Federal government $120,950
Professional, scientific, and technical services $99,790
Management of companies and enterprises $94,070
Finance and insurance $79,450
Job outlook for Data Analysts
From 2020 to 2030, employment of Data Analysts is expected to grow by 25%, which is much faster than the recent projected average of 7.7% for all occupations.
On average, 10,200 openings for Data Analysts are expected each year over the next decade. Many of those openings are expected to be created as a result of the need to replace workers who transfer to different occupations or leave the labor force for other reasons, such as retirement.
Job Description for a Data Analyst
A data analyst employs analytical tools and methods to convert sometimes confusing, disorganized, or disparate data into readable and understandable information.
Although duties vary depending on position and industry, data analysts are frequently in charge of gathering data, organizing it, and identifying trends and patterns.
Setting up the actual infrastructure to gather data, as well as maintaining databases and using programming languages to perform analysis, can be major components of the job for highly technical roles.
Even for less technical roles, most data analysts must be proficient in Microsoft Excel and SQL. Data analysts also create visualizations and reports in the later stages of a project and communicate their findings to leadership.
What are the typical tasks that Data Analysts have?
Data analysts are an invaluable part of any organization, juggling a variety of day-to-day tasks that vary depending on the needs of their organization. As a data analyst, you may be required to perform the following duties:
Specifying data requirements
To conduct effective data analysis, it is critical to specify the data requirements from the start. Assume the data is about the population. If this is the case, specific variables such as age, income, and so on must be specified and obtained. The information gathered could take the form of numbers or categories.
Once the variables have been specified, the information about the variables must be gathered. It can be gathered from a variety of sources and made available for processing. In its current state, this data may not contain any insights. As a result, it must be processed and cleaned.
Whether an analyst collects data on their own or collaborates with others in the organization, efficient data collection processes must be in place. Data could come from Google Analytics tracking tools, company surveys, email marketing software, or any number of other sources.
The collected data must be organized for further analysis. This would imply structuring the data in a specific way so that it is compatible with various analysis tools.
For example, you might need to arrange the data according to date and time in rows and revenue figures in columns in a table for further analysis in a Spreadsheet or Statistical Application. You may also need to create a data model.
Database design and maintenance
Data analysts must not only establish processes for storing, retrieving, and categorizing data, but also address any structural issues or coding errors within databases. Depending on their role, they may work on this alone or in collaboration with an engineer.
Although it is not the most exciting aspect of the job, data must be cleaned of duplicates, errors, and unnecessary information. This can be done manually, but it is more often than not done with automated formulas or programming.
Using tools to interpret data
Statistical programs are an essential component of any analyst's toolkit. To discover patterns and insights and make sense of large amounts of data, data analysts use software such as SAS and Excel or programming languages such as Python.
Documenting and improving processes
Data analysts collaborate with other members of the organization, such as engineers and business leaders, to develop data policies, improve data collection, and create detailed documentation which helps define SOPs (Standard Operating Procedures).
Visualization and presentation
Data is meaningless if it does not result in meaningful action or business decisions. Data analysts format and visualize data in order to make it more understandable, and they present their findings to key stakeholders.
As is usually the case, most stakeholders in the business are not data analysts and they can be easily overwhelmed by large amounts of data. This is why Data Analysts learn how to present their findings in easy-to-digest graphical or tabular form.
What kinds of Data Analyst jobs require Microsoft Excel Certification?
Every single kind. MS Excel is such a fundamental tool in the world of data management that it would be impossible to get a job without certification in the hand unless in rare cases it was waved off at entry-level positions.
But even in these positions, the first item on the agenda is to start with Excel training immediately.
Having an Excel certification, especially an advanced level certification, will not only greatly improve your chances of employment, but will help you get paid better.
The top three jobs with increasing demand across industries in the United States, according to the World Economic Forum's The Future of Jobs Report 2020, are Data Analysts and Scientists, AI and Machine Learning Specialists, and Big Data Specialists, all of which fall under the data and analytics umbrella.
Clearly, data and analytics is a hot field worth investigating. But what exactly are the roles you might be interested in? Here are eight options (along with salary data from the compensation resource Pay scale, whose database is updated nightly; the figures below reflect the most recent data as of May 2022):
Lowest and highest in this field: $41k to $89k/ year
Job Description: A data analyst gathers information about specific topics by analyzing data. This typically begins with the survey process, in which data analysts locate and collect the necessary information.
The information is then interpreted and presented in the form of charts or reports. Data analysts must be familiar with computer programs such as Microsoft Excel, Microsoft Access, SharePoint, and SQL databases.
Lowest and highest in this field: $67k to $146k/ year
Job Description: While the primary responsibility of a data analyst is to examine and analyze data, the primary function of a data scientist is to create the framework for that analysis to take place.
This includes implementing statistical models and algorithms, conducting data testing and experiments, creating data products, and constantly optimizing their frameworks to better analyze the data—all with the goal of reaching the most accurate business conclusions.
A bachelor's degree in computer science, math, statistics, engineering, or a related field is typically required for employment as a data scientist, though many employers prefer candidates with advanced degrees.
Lowest and highest in this field: $75k to $166k/ year
Job Description: Machine learning engineers are programmers who create the algorithms, models, systems, and frameworks that enable machines to learn and perform functions autonomously—without the need for commands.
These engineers are also in charge of converting data scientists' models into real code that can be used in production.
Machine learning engineers should be fluent in programming languages such as Java and Python, as well as have a bachelor's or advanced degree in computer science, math, statistics, or a related field.
Lowest and highest in this field: $51k to $102k/ year
Job Description: Business intelligence analysts are concerned with how data can be used to improve an organization. Gathering, organizing, and analyzing both internal and external industry data—and then using that data to identify trends, patterns, or potential issues that need to be addressed—could be part of this.
By statistical analysis using Excel, analysts in business intelligence are also expected to translate their data analysis into actionable strategies to improve the business—and to present their strategic analysis to leadership.
Because this is a highly technical position, candidates should have a bachelor's degree in computer science, math, or a related field. Many business intelligence analysts also pursue advanced degrees, such as MBAs, and some employers may require one.
Lowest and highest in this field: $40k to $83k/ year
Job Description: Logistics analysts are in charge of utilizing data to optimize supply chain processes, from procurement to shipment and delivery.
These analysts use data to identify potential profit loss within the supply chain, and then use that data to develop cost-cutting solutions to improve the efficiency of product production, distribution, and delivery.
A bachelor's degree is typically required for logistics analysts, but a proven track record in logistics and supply chain management can be enough for qualified candidates to get their foot in the door.
Lowest and highest in this field: $81k to $178k/ year
Job Description: A data architect, like an architect, designs the structures that an organization needs to effectively acquire, organize, analyze, manage, and utilize data.
This includes converting business objectives into a data management framework, designing the framework, defining how data will flow through the framework, and collaborating with other teams and engineers to develop and implement the framework throughout the organization.
The majority of data architects have a bachelor's degree in computer science or computer engineering, though many have advanced degrees.
Lowest and highest in this field: $52k to $105k/ year
Job Description: Business systems analysts, as the name implies, are in charge of analyzing and leveraging data to improve an organization's systems and processes, particularly in information technology (IT).
They analyze the company's current systems using data tools, then identify ways to optimize systems, cut costs, and make IT more effective across the organization. Business systems analysts may also conduct research on new systems and tools to improve IT before assisting in the implementation of those systems across departments.
Business systems analysts typically hold a bachelor's degree in a technical field such as information technology management or information systems. Candidates with a business background and a strong interest in and knowledge of IT, on the other hand, may be a good fit.
Lowest and highest in this field: $41k to $82k/ year
Job Description: Marketing analysts are in charge of assisting businesses in better understanding their customers and markets. They analyze data sets related to a company's target demographic, such as market research, purchasing trends, and customer surveys.
They use their analysis to develop strategies to help companies better connect with new customers and market to their existing customer base. Marketing analysts must also be able to present their findings to senior management as well as colleagues in marketing and other non-technical departments, so they must be able to translate their analysis into reports, charts, and other materials that are easy to understand and act on.
Marketing analysts typically hold a bachelor's degree and come from a variety of academic backgrounds, including marketing, economics, business, math, statistics, or psychology.
How to become a Data Analyst
We have listed some courses below for every level of Analyst, from entry-level to advanced level. These courses that are very reasonably priced can kick off your career as a Data Analyst, advance your career in the field or even help you switch from a job that you are not satisfied with right now.
Course Duration: 10 Hours per Week - 18 Estimated Weeks
Description: This entry-level course helps you get familiar with the entire MS Office Suite of Applications.
It is a great way to start becoming a Data Analyst. Each course in the Microsoft Office 2019 Value Suite introduces students to the fundamental features and functionality of Microsoft's 2019 software suite, which includes Microsoft Word, Excel, and PowerPoint.
Course Duration: 10 Hours per Week - 6 Estimated Weeks
Description: Make worksheets to help you manage, store, organize and analyze this data. Excel, Microsoft's powerful spreadsheet software, is the most commonly used program for this purpose.
This course will introduce you to the basic functions and uses of Microsoft Excel. You will learn numerous shortcuts to quickly and efficiently set up worksheets through hands-on lessons.
You will also learn how to use the function wizard to compute statistics, future values, and other things. You'll also learn how to sort and analyze data, create three-dimensional workbooks, and automate frequently-repeated tasks with macros and buttons.
Course Duration: 2 Hours per Week - 1 Estimated Week
Description: This overview course will introduce you to the power of pivot tables and pivot charts, as well as how to create Vlookups and an introduction to Excel's suite of business intelligence tools.
Course Duration: 15 Hours per Week - 1 Estimated Week
Description: This is an introduction to spreadsheets. A good spreadsheet will provide you with accurate data. Microsoft Excel is one of the most important tools for entering, formatting, and calculating data. It is a critical middle-technical skill that is required for all management positions.
Course Duration: 5 Hours per Week - 3 Estimated Weeks
Description: Understanding formulas is a critical middle-technical skill in mobility analysis, as well as related fields such as management and engineering. Formulas convert information into decisions. Logical and statistical formulas can analyze a dataset and return a result based on the criteria you specify.
Course Duration: 5 Hours per Week - 6 Estimated Weeks
Description: Mastering Microsoft Excel is a stepping stone to a better job. Learn how to enter data and create formulas in order to analyze and present complex data. Understanding Microsoft Excel is a critical middle-technical skill in mobility analysis, as well as related fields such as management and engineering.
Course Duration: 5 Hours per Week - 4 Estimated Weeks
Description: Data collection and data management are expanding fields in data analysis and business intelligence. XML is a popular coding language that is being used more and more in data management. Learning XML does not have to be difficult!
To improve understanding of the building blocks of XML code, the code components, right down to the characters, are labeled and color-coded.
Course Duration: 5 Hours per Week - 6 Estimated Weeks
Description: Using real-world data from counties and municipalities, you will learn how to enter, analyze, and create advanced reports such as PivotTables and Pivot Charts.
Offered at: Washtenaw Community College
Unmudl tips to learn Excel!
1. Make a decision as to why you want to learn Excel:
What motivates you to learn Excel? Do you want to improve your data visualization and evaluation skills in order to land a job in an office? Do you want to increase your productivity by becoming more organized?
Whatever the reason, determining what you want to use Excel for will point you in the direction of the features you need to learn.
2.Look for accredited institutions to get certified:
As a beginner, it's not so much about how quickly you learn as it is about whether you truly understand the fundamentals. Look for reputable resources that will assist you in diving into more difficult Excel topics.
Fortunately, there are a plethora of free and paid resources available online for both beginning and advanced students. We have listed some in the section above.
3.Consider taking online classes:
Enrolling in an online course is one of the best ways to learn Excel. Many people want to learn Excel to add to their professional skillset. This is difficult when you already have a job.
With online courses, you can easily manage a couple of hours a week from any location. There are numerous advanced courses and video tutorials available to assist you in using this analytics software for more complex functions.
4.Practice is key:
Because Excel has so many features, if you want to become an expert, you'll need to keep practicing. Begin by solving simple math problems using a basic formula. Data analysis exercises in Excel are a great way to practice and improve your skill.
Then you can proceed to make charts and tables. If you're really eager to put your skills to the test, you could also try your hand at one of the top Excel projects.
5. Learn to use keyboard shortcuts:
This might seem like an obvious tip, but you will be surprised how many Excel users do not know some of the most basic keyboard shortcuts.
Consider learning the program's keyboard shortcuts if you want to improve your efficiency. Then, without using your mouse, you'll be able to perform mathematical functions, draw tables, and conduct quick analyses.
Many advertised job openings for data analysts will include a requirement for Excel Data Analytics certification. Some businesses will go so far as to list specific Excel certifications that they will accept.
In this article, we have discussed in detail how and why you should get certified in MS Excel. It is one of the easiest ways to get started on a dependable and stable career that will continue to pay well into the future.
Frequently Asked Questions
Can I be a data analyst with just Excel?
Excel is a fantastic tool for data analysts. Data analysts use it as an indispensable tool for analysis. Excel excels at producing clear, polished charts and plots of business data.
How Data Analysts use Excel?
Data Analysts use Excel to manipulate large amounts of data to find trends that they offer to stakeholders in easy-to-understand visual or tabular form.
Can I become a Data Analyst without a degree?
To become a data analyst, you don't need a full-fledged degree, but you do need a structured and formal approach to learning the necessary skills. A project-based certification is the best (and most flexible) way to do so.