What Is Data Visualization?

The visual representation of data is known as Data Visualization. In order to make data more accessible, it uses visual elements such as charts.

What is the biggest challenge of big data? Clearly, the delivery of new knowledge and insights from huge amounts of data. It often feels like looking for the proverbial needle in a haystack. Find the needle you need with Data Visualizations. We’ll tell you how it works.

What is Data Visualization?

Data visualization allows you to visualize relationships, patterns, and trends in data and derive new insights from them. This data influences business decisions and should therefore be part of the business intelligence measures so that companies can act accordingly. The visualization of data works using data points. Graphics, diagrams, plots, and other images can be derived from it.

Why is Data Visualization Important?

Data visualization leverages big data and the cloud to provide decision-makers with new and meaningful insights. Visualizing data is an efficient way to discover new knowledge and share it with other people. Once the data is part of the business intelligence, decision-makers can make recommendations for action.

Data visualization is one of the most powerful ways to extract insights from data and communicate them clearly to other stakeholders. Because images tell a story and help build a narrative around data, data visualizations are essential in supporting the understanding and use of data.

How does data visualization work?

Data visualization works best in a self-service environment, where the data architecture is configured to deliver data to decision-makers.

In general, self-service means the following:

Various internal and external data systems generate reports by combining data in an Excel spreadsheet, for example, and searching through it for new insights. In a modern self-service environment, data architects then design pipelines to transfer the data into a visualization platform. In this way, data analysts automate manual work and gain access to more data sources. With self-service analytics, analysts can quickly source, combine, and analyze data.

If you, for example, are processing a large amount of data, you can use a correlation matrix to quickly see the strength of relationships between variables. This allows you to discover fascinating insights that may not be obvious when analyzing data in a spreadsheet.

Before you deal with new knowledge, you should make sure that the knowledge you already have is presented correctly. Data analysts generally have a good understanding of their data and will spot obvious signals. If these signals are not evident, the data may not provide a complete picture. In that case, it’s time to contact the data architects to ensure the data is coming from the right sources.

What are the benefits of data visualization?

With the right data, companies can leverage the many benefits of data visualization. Here are four benefits of data visualization:

1) Delivery of important insights

2) Acceleration of decision-making processes

3) Development of a narrative around the data

4) Optimization of corporate success

 

1. Data visualization provides important insights

Data visualization simplifies the process of data analysis by turning large amounts of data into insightful graphs and charts. For decision-makers, these are much more meaningful than a text or mere numbers. A single chart can visualize complex datasets and uncover undiscovered relationships, patterns, and trends. In this way, deviations and special cases can also be identified.

2. The visualization of data accelerates decision-making processes

Companies have to make business decisions faster and faster in order to get results quickly. Data visualization accelerates the analysis processes. Companies that use data analysis, therefore, have a decisive competitive advantage over the competition – because the faster you understand your data, the faster you can act.

3. Data visualization turns data into a narrative

Computers are great for processing large amounts of data, but the human brain is not. Our brain loves colors and patterns. It can process visual representations much faster than monotonous rows and columns filled with cluttered data because a picture is worth a thousand words (or numbers).

When you let your data tell a story through visualizations, your audience—whether they be executives, supervisors, or potential buyers—will digest the information faster and be won over.

4. Data visualization contributes to the success of your company

Almost every area of ​​business uses data to make important decisions. The requirements for data-based business processes are constantly evolving. Thanks to big data tools, data analysis is no longer just the domain of IT, but can also be carried out by business professionals. The ability to understand data is therefore becoming increasingly important. Anyone who understands the art of data visualization can play at the top.

The History of data visualization

Turin Papyrus: The oldest example of data visualization

The history of data visualization is unexpectedly long. It extends to ancient Egypt. Around 1160 BC BC Ramses IV had a map made on which he located quarries, mines, and other resources on a 15 km long strip of land. The Turin Papyrus is probably the oldest known example of data visualization. The map is annotated and shows the blocks extracted from the quarries, the distribution of the different stone types (in black and pink), and the variety of local boulders using brown, green, and white dots.

With data visualization against death

Florence Nightingale was the inventor of modern nursing and one of the first data analysts. During the Crimean War in the 1850s, people believed that the high death rate among soldiers was due to combat. But Nightingale collected data and showed that many deaths were related to nursing practices. She used data visualization to illustrate her point.

Each wedge shows the number of deaths per month: red represents the wounded, black represents “all other” causes, and blue represent preventable/curable disease deaths.

Napoleon as a data analyst

Another famous example of historical data visualization is Minard’s map of Napoleon’s Russian campaign. Napoleon began his campaign against Moscow on the Polish-Russian border with 470,000 soldiers. However, he returned with only 10,000 soldiers. A thick red line shows the march to Moscow. It is diluted to represent the loss of troops en route to Moscow. A thinner black line shows the loss of soldiers returning to Poland. Below the map, a line connects winter temperatures to specific times during the march. Apparently, as the temperatures dropped, so did the soldiers.

The distance covered as well as the latitude, longitude, and location of the march at specific times can be seen.

Data visualization and the cloud

The cloud exists to handle large amounts of data. So it makes sense to do data visualization there. Because data integration is faster and easier in the cloud, many vendors add more data visualization tools to their cloud-based versions than to their on-premises versions.

Extensive self-service analyses and data visualization is only possible thanks to the cloud. It’s the only viable platform for sourcing and analyzing real-time data. In addition, the cloud contains a central storage location that ensures that there are countless copies of data in different places. If companies store everything in one place, they can access the same data at any time, regardless of location.

A lot of data is unstructured and archiving it requires a large amount of disk space to organize and store it. Cloud storage is far cheaper than purchasing on-premises hardware that companies have to maintain themselves. In this way, companies can store their data more easily and quickly and scale their storage package if necessary.

Big Data Visualization – What do you need to know about tools?

Visualization tools are used to illustrate big data. Companies can choose the graphic forms in which data is presented. However, more powerful data visualization tools also offer algorithms that automatically select the best format for the data at hand. Many tools offer both variants.

The tools for data visualization differ in their properties, their complexity, and the associated costs. If the goal is self-service analysis or visualization, it’s worth exploring cloud-based options. The best thing to do is to look for the right tool for big data visualization according to your individual requirements and research it in depth.

Is the dashboard customizable?

The heart of every tool is the dashboard. This should be easy and intuitive to customize so users can view the data from different perspectives. For example, C-level users tend to need an overview view, while those in the data analysis department tend to need more in-depth insights into specific areas.

It’s best to look for drag-and-drop interfaces that allow you to both add and delete data quickly and easily. You can also find out about the latest insights and test different visualizations.

Can the tool create interactive reports?

Reports are a common way to share information. The best data visualization tools allow you to constantly add new information to a report. By being able to format your report in different datasets and visualizations, you make it stand out from the crowd.

Is local data available?

If geographic locations are important to your business, location information should be built into your visualization tool. The best tools provide powerful ways to compare:

1) Internal sales data

2) Internal data regarding operational procedures

3) General Business Data

It should always be possible to include location-specific factors such as the economic climate, cost of living, level of education, etc. in the analytical comparison.

Can the tool also be used on mobile devices?

Decision-makers are constantly on the move. Access to business intelligence on a tablet, smartphone, or another device can therefore be crucial. Check the tool’s mobile functionality to make sure it meets your needs.

Can you access the data in real-time?

Accessing and analyzing data in real-time is a must for many companies. If you’re using real-time data, you need to look for cloud-based tools that can process it.

Big Data Visualization: Move businesses forward

Businesses process data to gain insights. Data visualization is a powerful way to quickly identify and communicate undiscovered relationships, patterns, and trends. In a modern data environment, visualizing data is the fastest way to search for hidden knowledge.

Conclusion

You must have had a feeling after reading the article about how important data is today as well as how much important it will be in the future. If you are thinking of making a career in the data field, you can choose to join Skill Shiksha  Online Data Science Course to start your career as a Data Scientist.

Read More- What Does A Data Scientist Do In 2022?