Considering a career in data analytics? That’s a great choice, but knowing exactly where to get started can be a bit of a challenge. Should you dive right into the major data analytics tools? Or maybe focus on a basic understanding of what data analytics is? There’s no totally correct answer here and the right choice will depend on your previous experience, existing knowledge, and ultimate career goals.
No matter where you’re looking to begin, we’ve collected a list of the best beginner-friendly data analytics tools that will help you create a solid foundation in data analytics, setting you up for future success.
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Starting Out in Data Analytics
Strengthening your knowledge in data analytics is a great choice–after all, a good introduction will help you decide if data analytics is right for you and pinpoint your areas of improvement. Learning a new skill can be a serious investment and it’s best to start out slowly to make sure you’ll stick with it.
You’ve probably already completed this step, but make sure you review the basics of data analytics, familiarizing yourself with different data types, how data is organized, and the basic process of analyzing data (learning, preparing, visualizing). There are many YouTube videos out there that cover the basics of data analytics, in addition to online guides and tutorials.
Beginner-Friendly Data Analytics Tools
A simple online search will tell you there are quite a few tools available for data analytics, but it’s important to start slow and build a basic understanding of data before you invest in a tool that may not be right for your needs or skill level. While there are many options, three that are truly the best place to start for beginners are Excel, PowerBI, and Google Sheets.
Excel for data analysis
You’ve probably used Excel for something and that’s because it’s an incredibly versatile tool that is actually quite powerful when it comes to data analysis. While your possibilities with Excel are quite vast, it’s particularly useful for learning how to organize, manipulate, and analyze data with its built-in features.
For cleaning data, Excel helps you master the data cleaning process with tools such as ‘Remove Duplicates’ and conditional formatting, which highlights any issues before you begin the analysis process. In addition, functions like average, median, and standard deviation familiarize you with some basic processes of data analysis.
To prepare you for working with larger datasets, Excel’s data manipulation features teach you about conditional formatting based on specific criteria.
Power BI for data analysis
Microsoft’s Power BI is a tool specifically designed for data visualization and is a great place to start, as it will help you begin using various data sources for your analysis and discover the important role data visualization plays in data analysis. Luckily for beginners, it doesn’t require extensive programming language knowledge and uses beginner-friendly features like drag & drop.
Power BI allows you to input data from various places, such as Excel, an SQL server, SharePoint, Google Analytics, and Salesforce. The ability to combine data from multiple sources is an important skill in data analysis, and its interactive and visually appealing dashboards are very useful for displaying the results of your analysis to your audience and, most importantly, allowing you to test various data visualization methods to determine the best for your specific use case.
Google Sheets for data analysis
Another tool for beginners is Google Sheets, which is similar to Excel and probably something you’ve worked with before. Google Sheets is particularly useful when it comes to collaborating with others, as its sharing abilities make teamwork very straightforward. Even if you’re just getting started on your own, familiarizing yourself with shared spreadsheets will be useful for your career.
It has built-in QUERY functions that allow for advanced data manipulation, in addition to functions like IF, VLOOKUP, and FILTER, to organize and extract important data points.
Source: iFour
Building a Strong Foundation in Data Analytics
Starting with beginner-friendly tools like Excel, Power BI, and Google Sheets is the best way to develop confidence in data analysis. These platforms introduce you to essential concepts such as data cleaning, visualization, and manipulation, all of which are crucial for advancing in the field.
Once you’re comfortable with the basics, consider taking structured courses, joining a data analytics bootcamp, or exploring more advanced tools like SQL and Python. A strong foundation will set you up for long-term success, making it easier to transition into more complex data projects and career opportunities.
Ready to take the next step? Explore structured learning options and hands-on projects to deepen your skills and open new doors in data analytics.
About the Author:
Juliette Carreiro is a skilled content creator with over five years of experience in SEO, content ideation, and digital marketing strategy. She has spent more than two years at Ironhack, where she developed in-depth articles on topics ranging from career growth in tech to the future impact of AI. With expertise across tech, hospitality, and education industries, Juliette has helped brands like Ironhack engage their audiences with impactful storytelling and data-driven insights.
