Beginning With Data Visualization – Where should you start?

With so much information being gathered in the business world today through data analysis, we must have a way to paint a picture of that data so that we can interpret it. By giving it visual context through maps or graphs, beginning with data visualization gives us a clear idea of what the data means.

To analyze massive amounts of information and make data-driven decisions, data visualization tools and technologies are essential in the world of Big Data. Colours and patterns are attracted to our eyes.

We can identify red from blue, square to a circle, quickly. Our culture, including everything from art and advertising to TV and film, is visual.

Another type of visual art that catches our attention and holds our eyes on the message is data visualization. We easily see patterns and outliers when we see a map.

If there is something we can see, we internalize it easily. For a reason, it’s storytelling.

You know how much more powerful visualization can be if you’ve ever stared at a huge data spreadsheet and couldn’t see a pattern. 

Why is it so important?

Data visualization can help by presenting data in the most effective way possible, no matter what company or profession you have chosen. Data visualization takes the raw data and models it.

Then it delivers the data as one of the key steps in the business intelligence process so that conclusions can be drawn. Data scientists are designing machine learning algorithms in advanced analytics to help compile important data into visualizations that are simpler to understand and interpret.

In particular, visualization of data uses visual data to convey information in a way that is universal, rapid, and efficient. This approach will help businesses determine which areas need to be changed.

It also helps determine which factors influence customer loyalty and disappointment, and what to do with particular goods (where should they go and who should they be sold to).

The increasing popularity of data visualization

Visualized data gives a clearer prediction of revenue volumes and potential development for customers, company owners, and decision-makers. On the rise is the idea of the citizen data scientist.

To meet a data-driven environment, skillsets are evolving. To be able to use data to make decisions and use visuals to tell stories about when data tells who, what, when, where, and how is increasingly important for professionals.

While traditional education generally draws a distinct line between imaginative storytelling and technological research, those who can cross between the two are often respected by the modern professional world. Data visualization sits right in the center of analysis and visual storytelling.

Visualization is an increasingly important method for making sense of the trillions of rows of data produced every day as the ‘Epoch of Big Data’ kicks into high gear. Visualization of data helps tell stories by curating information in a way that is easier to understand, illustrating patterns and outliers.

A good visualization tells a story, eliminates the noise from the information, and highlights useful details. 

It’s not just as easy, however, as simply dressing up a graph to make it look better or slapping on an infographic’s “info” part. A delicate balancing act between form and function is effective data visualization.

To catch any notice or make it tell a powerful point, the plainest graph could be too boring. The most stunning visualization could completely fail to convey the correct message or volumes could be spoken.

It is necessary to work together with the data and the visuals. There is an art to combine great analysis and great storytelling. 

Benefits of Visualizing Data

For both SMEs and large enterprises, data visualization tools can bring many advantages. Visualization of data positively influences the decision-making process of an organization with interactive visual representations of data. 

Businesses can now more quickly recognize patterns because they can interpret information in graphical or pictorial forms. Data visualization is not just a throwaway phrase that industry experts and business professionals use to make you feel inadequate.

Nowadays, companies generate a significant amount of data, regardless of size and industry. Back in 2015, the global annual data production rate was estimated at 5.6 Zettabytes.

Its almost double the growth rate of just three years earlier.

Here are some more specific ways that an organization may benefit from data visualization:

• They can store data faster and more efficiently in visual form.
• Access to significant market knowledge more rapidly and conveniently.
• With data visualization, teams may share results in more efficient ways.
• Tools for data visualization recognize insights that could otherwise be overlooked in conventional methods of reporting.
• Identifying the new industry trends quickly and easily.
• Boost profits with predictive analysis of sales. 

The various types of visualizations

Your first thought will probably go immediately to simple bar graphs or pie charts when you think of data visualization. While these can be an important part of data visualization and a common basis for several graphs of data, the correct visualization must be combined with the correct information collection.

Just the tip of the iceberg is basic graphs. To display data in useful and fascinating ways, there is a whole variety of visualization methods. 

Infographics:

Infographics take an extensive set of information and offer you a detailed visual representation. Unlike a single visualization of data. 

An infographic for discussing complicated and highly subjective topics is excellent.

Heatmap Visualization:

This technique uses a graph to show if the data is a high-value or low-value point with numerical data points outlined in light or warm colours. This method of data visualization allows the audience to recognize the details mentally since studies have shown that people perceive colours much better than numbers and letters.

Histogram:

Histograms, instead of looking at patterns over time, calculate frequencies instead. Using an automated data visualization formula, these graphs show the distribution of numerical data to represent a set of values that can be easily interpreted.

Fever Charts:

A fever graph displays data changes over some time. As a marketing tool, to get a reliable prediction of next year, we might take the results from the previous year and equate them to the previous year. This will allow decision-makers to easily understand large and conflicting sources of knowledge.

Area Chart (or Graph): To visualize the time-series relationship of the data, area charts are excellent. If you’re looking at the earnings on a month-to-month basis for individual departments or the success of a product since the 1980s, this relationship can be visualized by area maps.

EndNote

Know that particular instruments and goods can be transcended by strong data visualization theory and skills. When you are learning this ability, when it comes to visualizations and dashboards, concentrate on best practices and explore your own style.

Visualization of data is not going away any time soon, so it is necessary to create a base for research and storytelling, and discovery that can be taken with you regardless of the tools or applications you end up using.