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10 Essential Tools and Tricks to Help You Merge Data and Visualization


If you’ve ever encountered a Gantt chart, pie chart, dashboard, or even a mind map, you’ve interacted with data visualization. This collates the entire role of data science, helping students and professionals alike to convey ideas, figures, projections, etc.

According to the Harvard Business Review, data visualization can be categorized into four main purposes: idea generation, illustration, visual discovery, and everyday visualization. As a college student or even a professional in a niche field, being adept at data viz tools allows you to communicate more effectively, understand your data better

This article is just for anyone thinking of working with data or turning those numbers into raw, compelling stories. But we go beyond the basics into the tech tools you can use to make yourself stand out as a data professional.

Steps Before Adopting a Visualization Tool

As with every other great article, we always give you some great advice on how to advance yourself, especially as a student or a young professional. Professional writers such as RoyalWriter.co.uk can help you save quite some time with your research and writing. That means more time to explore subjects such as data visualization.

Every data viz tool you adopt is meant to help you tell an actionable story. Thus, it would help if you had a pretty good idea of what insights you are trying to reveal through your data and visualization tool. For example, you may want to demonstrate a process, workflow, or even statistical results from different tests.

Next, you must consider the audience you are tailoring the data for. Tailor the complexity and level of detail to their needs. Also, since you are tailoring a story for them, what takeaway would you like them to remember?

With those three questions answered you are now ready to dive into data viz tools.

10 Data Visualization and Wrangling Essentials

Again, this depends on what you are trying to achieve, your target audience, and general objectives. Let’s dive into some of these tools.


This is a powerful open-source tool from Google that helps to clean and transform messy data. You can use it to identify inconsistencies, handle duplicates, and standardize data formats. the key features of this tool are faceting, clustering, reconciliation, and infinite undo/redo. With its friendly UI and guided steps, you’ll be whipping your data into shape in no time.

Trifacta Wrangler

This is another excellent option for data wrangling and viz that also offers a free product trial. You will get an intuitive drag-and-drop UI and with handy white space to make sense of all your data. This can be used by anyone regardless of their skill level or coding ability.

Pandas (Python)

If you are comfortable with code, Python offers a dynamic workflow tool through Pandas. This is a versatile library for data manipulation, cleaning, and merging. You can leverage its powerful DataFrame structure and functions such as merge, concat, and join to combine data sets efficiently.

dplyr (R)

Another coding tool that you can use for data viz and wrangling is dplyr. This R package tool provides a verb-based syntax that makes cleaning and data transformation intuitive. For example, “mutate” adds new variables, “select” picks variables based on their names, and “arrange” changes the ordering of rows.

For those deeper in code, dplyr allows you to go into the backend by translating data to relational databases such as SQL, and high-performance data tables.


Tableau is one of the most popular visualization tools both professionally and in academia. You can use it to blend data from various sources. Tableau offers an easy drag-and-drop functionality and visual cues that help you seamlessly combine data sets and create insightful viz.

Power BI

If there’s one thing we have learned from Microsoft, it’s that ruthless efficiency wins, and that’s the case for Microsoft Power BI. However, Power BI has been more or less a legacy software used by organizations with a good purse. College students and other learners might therefore be turned off from using it.

That shouldn’t stop you from tinkering with PowerBI’s trial version. You will learn how to connect to data, shape the data with queries, use data models for visualization, and share reports.


This is an open-source tool that helps you to create network visualizations and explore deeper relationships between variables. You can import data and explore it in various patterns uncovering hidden relationships.


This is another free option that is an add-in for Microsoft Excel. So, if you have a particular affinity for Excel or find it easier to use than other spreadsheets or great for big data, NodeXL is just what you need to learn.


If you are working with dynamic data such as that from websites updated in real-time, a web scraper comes in handy. Using visualization APIs, you can extract data and integrate them with your own tools.

Kimono also allows users to build custom APIs or use existing ones. So, you can make your data and presentations rich with valuable external information.


This is another web scraping solution that offers a visual interface for building data extractors. You can use the point-and-click functionality to target specific data points on websites and integrate them into your data.

One last pro tip for the college students out there reading this. You might not ever get a shot at perfecting your skills in data grappling and visualization with an exceedingly packed schedule. An expert writing website can help free up that much-needed time and let you work on perfecting your skills. Check out this royalwriter review to see if this is an opportunity you’d dare miss.

Wrapping Up

Data visualization and grappling are valuable tools that everyone can use at whatever level they are. Whether you are a college student, a learner just trying to add a skill or two, or even a career professional, data visualization tools can take you to the next level.

We’ve covered everything from cleaning and transforming jumbled data, coding tools that help make syntax easier, to easy drag-and-drop apps that let you quickly visualize your stories. With these tools, you can become a pro and make your data meaningful to your audiences. See you on the next one.

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