The Best Data Visualization Tools for Beginners
As per the survey of the American Management Association, professionals can shorten the business meeting time length by 24% only with the use of appropriate data visualization. Their research also proved that while a verbal and simple numerical presentation can convince half of the audience, an effective visualization easily convinces ⅔ of the audience. Certainly, such stats add up extensive significance to the data visualization tools for business decision-making.
For example, the retail industry is thriving by utilizing helpful customer data for specific marketing. This helps the business grow and expand to more customers faster and more efficiently.
Similarly, others are benefitting from data utilization. But using data to gain insights is more challenging than it seems. It takes careful planning and utilization of some tools to help analyze the data effectively.
Data scientists deal with millions of data points present in a dataset. You can imagine the long process of data analyzing it may take. Even after long hours of work, it's nearly impossible not to make any errors during the visualization process. Tools for data visualization are helpful in these situations. Automating the exhausting task of visualizing data makes the job much easier.
What is data visualization?
Data visualization requires you to create visual representations from massive datasets. This is an easy-to-understand visualization of meaningful information available in datasets. The graphical illustration is simple and can be understood by even non-tech professionals, making it helpful in business presentations.
What are data visualization tools?
For the process of visualizing data, we use tools that help automate tasks with efficiency. Data visualization software (tools) helps interpret information immediately. Such software for visualization presents information such as dashboards, yearly reports, marketing and sales resources, and other information in the form of graphs, charts, and maps.
7 best data visualization tools for data analysis
Here I'll cover the seven most used data Visualization tools which you need to make your data analysis faster and more precise at the same time. Not only that, all of these tools offer stunning graph visualization features too.
Tableau can quickly process input data and deliver the output. Data scientists utilize tableau data visualization to analyze data. They are able to create straightforward conclusions using tableau.
It quickly handles security risks as soon as they are discovered. As one of the best data visualization platforms, it can connect to numerous sources to input data and generate several visualization formats, including charts, maps, and more.
It's simple to use and quite strong. They also provide Tableau Public to explore the various possibilities of free data visualization tools.
Cons of Tableau:
You can't expect the automatic report refreshing feature along with the scheduling. So you need to keep your data manually updated at the back end.
2. Zoho Analytics
Professionals who want to visualize business analytics use this software for data visualization. Zoho analytics can build great data visualizations in a short amount of time.
This tool provides the ability to examine company data across multiple departments by combining data from different sources to generate multidimensional data visualizations.
Its most common usage is showing sales records, marketing, revenues, expenses, profit, and pipelines.
Cons of Zoho Analytics:
While its user-friendliness is at the pick from the technical aspect, it lacks a bit in its customer support and tutorials.
Looker is a versatile application that helps us view data from different angles using its plugins. It includes pre-made analysis modules to allow users to easily use templates for specific data or analysis tasks, thereby speeding up analytics.
Looker's at-a-glance tools for visualization let you make data-driven documents more quickly. Through Looker, you can view a list of several visualizations, such as cartoons, aster plots, spider visualization, bar gauges, calendar heat maps, and liquid fill gauges.
It also makes it possible to mix many sorts of charts. A dashboard is present to perform detailed data analysis.
Cons of Lookers:
Although it provides a very high-quality data visualization, I must still mention that it's comparatively harder to use. Also, this tool for data visualization is a bit costly.
Infogram is a useful tool for creating graphs, presentations, and maps. Because of its simple interface, this data visualization software has become a favorite among data analysts.
It is also popular among creative workers since it can be used to generate infographics. The data visualizations you can generate using Infogram are simple, and the training is short.
The application also contains a drag-and-drop editor, which is useful for amateurs. We can use visualizations as pictures and GIFs for inclusion in documents and reports or HTML for online usage.
Cons of Infogram:
Customization of design via adding CSS has a lot of limitations in this data visualization platform.
5. Qlik Sense
This technology is used by businesses that require artificial intelligence skills to grow their data processing. It provides more engagement and insight than other tools for data visualization.
Qlik Sense is a data visualization application that employs AI to assist users in better understanding and utilizing data. The Qlik Sense AI is able to provide observations on data and help you generate analysis in a few clicks.
The platform automatically alters interactive visualizations such as tables or data-charts. It enables lightning-fast computations and also integration from multiple data sources.
Cons of Quick Sense:
The capability of extracting data is not that flexible.
Klipfolio enables users to access and integrate information from several providers without the need to write any code. You can utilize the chosen instant metrics that are all pre-built.
Using its advanced data modeler, you can use the data for daily decision-making. Users may import, update, and analyze data to gain detailed and precise information.
There are various tools in Klipfolio which provides to implement complex computations. These tools can also tackle complex data challenges.
Cons of Klipfolio:
Big data services and auto modeling have earned a lot of negative reviews from users.
This data visualization platform provides visual input analytics for social media marketing, SEO, PPC, and email marketing. This tool is especially beneficial to executives in social media to maintain track of each social network they utilize for marketing. The reports may be tailored to the specific requirements of each user.
Whatagraph is ideal for digital marketers that need to develop visually appealing dashboards for their clients. The data visualizations may also be tailored to your specific brand.
You may use the tool to link with a variety of providers and create stunning customized statistics dashboards.
Users can combine different advertising methods to quickly create reports and dashboards. They can also use connections like Google Analytics and Twitter to build visual analytics.
Cons of Whatagraph:
Frequent disconnection from the data sources is a big headache in this software for data visualization.
Why are data visualization tools necessary?
Data visualization tools provide in-depth analysis of the data. It is extremely useful in finding new hidden insights or patterns to locate errors. Moreover, this new data insight will help create better decisions.
• Helps perform better analysis
The tools help in better understanding the data. Through visualizing the data, business personnel can make decisions in advance, helping them gain an advantage. Understanding the present growth within the organization is essential in assessing the performance of business decisions.
• Provides efficiency
These tools help save time and money. Big data visualization tools make the visualization process of a dataset effective. They start plotting graph visualizations as soon as they read the dataset. The tools find out errors in the dataset which helps take appropriate actions.
• Locates sensitive information
The data visualization tools generate visuals that are easy for humans to comprehend. It helps find out sensitive data that cannot be found easily. The information is present in an unstructured, complex data format. This makes visualizing the data difficult. We can discover useful information through the right tools.
Which tool is best for data visualization?
The use of data visualization tools totally depends on the user's perspective and needs. Although below are the few attributes that are of utmost importance:-
The first feature is their simplicity of usage. Some visualization tools are incredibly complex. Tools that provide helpful tutorials and documentation for easy navigation are better as they feel more user-oriented.
The greatest tools can also deal with large amounts of data. These can manage multiple data sets in the exact visualization. Some tools may create multiple maps, graphs, and charts (line charts, bar charts).
Some tools can work well on a specific map or chart. These are also among the best data visualization tools out there.
We can find dozens, even hundreds, of apps, tools, and scripts to produce visuals of enormous data sets. Many offer simplicity and contain several overlapping features.
Yet, there are several amazing options also. Those that offer great visualization power or are substantially easier to use than their alternatives.
Selecting the best out of the list should depend upon your usage criteria. Find the specific need of the data visualization tool, and you can find the best option based on the specification.
Where to learn industry-standard data visualization tools?
Utilizing the ongoing technological developments to your advantage has never been easier. The challenging aspects are being lifted to provide a simple approach to problem-solving. Similarly, data visualization tools provide an easier and more efficient way to get results.
These tools are a reliable option for data scientists to save time and money. Data visualization tools help you perform better and more efficient analysis. However, one must first learn about the tools and determine which can help them in their business process.
The right mentor will assist you in making the correct decisions. You can enroll in the data science program to benefit from the live classes taught by industry experts. Additionally, you can also work on live projects where you'll perform the practical implementation of data visualization tools and more.