Data Visualization: Benefits, Types, Use Cases
What is Data Visualization?
Data is a characteristic of information usually represented in numbers that can be collected through various means. However, it is important to ensure the data collected is utilized efficiently - In order to do so, we can perform data visualization that is a graphical representation of data, usually in the form of a graph, map, or chart. Data visualization is a crucial tool point as it gives meaning to the data by understanding the trend and patterns in the data.
The Benefits and Types of Data Visualization
Visualization allows enormous amounts of data to be presented to owners and stakeholders in an understanding manner. Visualizations make use of colors that help tremendously in identifying and differentiating patterns. Visual perception allows the brain to process information easily and internalizes it quickly.
Trends can not be seen in a massive spreadsheet of data, however, with visualization, those trends can be easily identified - this shows how effective visualization is.
Types of Visualization
Some different types of visualization are:
- Heat maps
- Scatter plots
Data Visualization Use Cases
Some use cases of data visualization are:
Sales and Marketing
Research from media agency Magna forecasts that half of the global advertising dollars will be spent online in 2020. Therefore, identifying trends is extremely vital in the field of sales and marketing as it helps the suppliers identify what the consumers require and traffic trends on their online services.
Due to the ongoing pandemic, data visualization plays a critical key in helping to identify clusters or the number of cases in specific areas.
Finance professionals make use of data visualization to track the performance of their investment decisions. By analyzing how the prices have changed over time, finance professionals can identify trends.
Shipping companies make use of visualization tools to determine the best possible shipping routes for their products.
Some other use cases of data visualization are - politics, education, sports, and scientists.
Data Visualization Tools Usage
There are various types of data visualization tools such as:
- Microsoft Excel
- Microsoft Power BI
- Google Charts
- IBM Cognos Analytics
These tools can be used as business intelligence tools to generate dashboards for companies in order to keep a track of the performance across key performance indicators (KPIs) and then visually interpret the results.
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Data Visualization Emerging Trends
Data visualization has been around for a long time. However, a handful of trends are coming up. These changes are going to change data visualization in the long run. These trends are highlighted below.
The difficulty of data handling has brought the development of data democratization. This process is a non-programming aspect of data analysis. Therefore, it gives anyone the ability to visualize data without expert data analysis or data science. Behind data democratization, processes and tools are being simplified to provide room for people that are not good with coding. Doing this has opened a lot of opportunities for people within businesses. It has also reduced stress on the few data people within any institution.
Research has shown that people tend to respond more to video than static images. As a result, many users are moving towards video visualization to maximize impact. The use of visual moving parts that tell a story effectively conveys the required information to the listeners. As the internet gets faster and more accessible, it is expected that many more people will make the push towards video visualization.
The use of remote access technology has changed how people perceive things. Now more than ever, employers and the management of businesses want access to the latest information about their enterprises. These needs gave rise to real-time data presentation. As a result, more visualization systems that accommodate input from live feeds are being made. For example, many businesses include a customer feedback feed onto their data visualization system. Doing this gives experts the ability to monitor client feedback as it occurs.
Use of Advanced Technologies
Machine learning and artificial intelligence (AI) slowly creep into data visualization. The capabilities of these tools make their use appealing to data visualization experts. With the help of machine learning and AI, current and projected values of data can be presented with ease. Similarly, the accuracy of such projections increases with the aid of these technologies. Likewise, customer feedback is quickly integrated and categorized into the data pool.
Mobile Data Visualization
More than 50% of internet users access the web through mobile devices. As a result, these statistics cannot be ignored. The need to cater to mobile phone users has forced many businesses to prioritize mobile data visualization over web-based. Therefore, more data visualization specialists are developing solutions that make data viewing on mobile devices easier.
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