The Top 9 Data Science Tools for Visualization in 2024
Monday, November 4, 2024
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You might feel ready with the numbers. However, you might find others in your team or senior leaders uninterested in understanding rows and columns of data. Instead of letting your hard work go to waste, consider presenting the data in a manner that is presentable and understandable to everyone. You will find many more people taking an interest, appreciating the insights, and even thinking of possible solutions.
While working with Big Data, analysis and interpretation is only one step of the process. Coherent and meaningful visualization of the data is equally essential. Today, most data analysts make use of data visualization tools that can help them present insights more impactfully. While some sophisticated tools can be heavy on the wallet, data visualization techniques can be applied in any context involving data.
Data visualization is a crucial skill set for Data Analysts. That is why several data science courses emphasize this skill. USD Online’s MS in Applied Data Science program has a dedicated course on applied data science for business, covering compelling storytelling and analytical computation. The course focuses on real-world uses of data mining using Python.
Top 9 visualization tools used by data science professionals:
Here are some tools that are frequently used by data professionals across the world:
Tableau
Tableau is a data visualization product by Salesforce Inc. It is used to create impactful dashboards for real-time data interpretation. Since it can be integrated with customer relationship management tools, it provides a powerful experience to data analysts who have to look at customer data regularly and draw insights for the business. This is a sophisticated tool that might require in-depth training and learning.
Power BI
Power BI is a tool by Microsoft that helps data analysts create static and interactive data visualizations. As a part of the Microsoft suite, the tool can be integrated with other MS products like Excel. It has several applications for mobile and desktop. The tool also offers real-time updates and AI-driven insights for users.
D3.js
D3.js is an open-source platform that is used via JavaScript library. One of the unique features of this tool is that it can be used in web browsers as well. Being an open-source tool, it is free for all to use. It requires a strong foundation in coding applications. It can be used for interactive visualizations as well. Before working on high-end data visualization tools, get your basics in data analytics. If you want to elevate your career and become a qualified data analyst, consider pursuing a master’s degree in data analytics from the US. You will learn to become more skilled in programming languages like Python, R, SQL, and AWS.
Qilk Sense
Three features that make Qilk Sense a go-to product for data visualization experts are the active analysis functionality, the AI-based insights, and the visualization dashboard. This product is valuable because it is scalable and has robust data integration capabilities. It is a self-service tool and requires some expertise, but it can produce interesting, hidden data patterns.
Google Data Studio
The Google Data Studio is now known as the Looker Studio product and is a free-to-use product by Google. It provides real-time collaboration and easy reporting sharing. While it offers a user-friendly interface, its customization options, and advanced features are somewhat limited compared to paid tools. Nevertheless, Google Data Studio is an excellent choice for those looking for a cost-effective solution to create and share data visualizations.
Chart.js
Chart.js is a simple yet flexible open-source library for creating various types of charts. It is easy to use and supports a wide range of chart types, making it an excellent choice for developers who need to implement visualizations quickly. However, it needs some of the advanced features and customization options found in more comprehensive tools. Chart.js is ideal for projects that require straightforward and visually appealing charts without the need for extensive customization.
Want to know whether you are ready for the next step in your data science career? Familiarize yourself with USD Online’s MS in Applied Data Science program’s readiness resources.
Sisense
Sisense is known for its in-chip technology, which allows for fast data processing and real-time analytics. It is highly scalable and integrates with numerous data sources, making it suitable for large enterprises. However, Sisense can be expensive, and its setup process can be complex. Despite these challenges, Sisense’s robust analytics capabilities and ability to handle large datasets make it a valuable tool for data-driven organizations.
Zoho Analytics
Zoho Analytics offers a user-friendly drag-and-drop interface and AI-powered insights, making it accessible to users with varying technical expertise. It integrates well with the Zoho suite of applications, providing a cohesive experience for Zoho users. However, it may struggle with performance issues when handling large datasets and offers limited customization options. Zoho Analytics is a cost-effective solution for small to medium-sized businesses looking to enhance their data analysis capabilities.
Infogram
Infogram is designed for ease of use, offering a range of templates and real-time collaboration features. It is ideal for creating visually appealing infographics and reports quickly. However, its customization options are limited, and it needs some of the advanced features found in other tools. Infogram’s free version provides basic functionality, while the Pro version offers more features at a reasonable cost. It is an excellent choice for users who need to create professional-looking visualizations without a steep learning curve.
Still trying to figure out where to start? An online degree in data science from the US will equip you with the right skills needed to become a data analyst.
How to Become a Data Analyst
There are several career pathways to becoming a Data Analyst. While some begin with data entry and organization roles, others consider a specialized degree to develop their skills before they enter the job market.
Here is a typical pathway to becoming a Data Analyst:
Complete your education: While there is no one fixed degree to becoming a Data Analyst, some of the common ones include computer science, information technology, data science, math, statistics, or economics. To gain an edge over others in the market, you can consider a specialized master’s degree in data science from the US.
Build Technical Skills: Some of the commonly used programming languages like Python, R, and SQL are essential for data analysts. If your bachelor’s degree does not equip you with these skills, consider building them through practice on your job. You can also consider earning a degree while you work. USD Online’s MS in Applied Data Science is designed for working professionals.
Work on Real Projects: Build a portfolio of your work through real-life case studies. Consider hackathons and competitions on platforms like Kaggle, which will also give you some exposure.
As businesses become more complex, data-driven insights are crucial for business leaders in their decision-making process.
According to a report by Salesforce, 73% of business leaders believe that data reduces uncertainty and helps them make better decisions. However, many of them need help to work with big data due to its complexities and uncertainties. That’s where a competent data analyst and their data visualization tools can add tremendous value to the business.
If you are ready to take the next step in your journey as a data analyst, apply today to a master’s program in applied data science from the US. Reach out to the USD Online admissions team for more information on our courses.