What are the fundamental of data Visualization?

How do we focus on the data that is important Get that data in the right hands at the right time in the right way to make more informed, real-time business decisions

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Data visualization means to view data in a proper and easy way. and get the solution where the problem is occurring.

Use of Data visualization Device. They can send Data through SMS, Email. Because of this data is secured.

At any time problem occurs. At that time it’s send the data to the owner or manager to handle the situation.It work with real time.

@vinay I will suggest you to go with training once , since IOT and ML is specially used for it only. For example the “Integromat” is used only for sending messages , alerts to right person we just need to set the data and all things will be taken care by Intergromat . It works 24 hours, 7 days in a week ,means it works all the time. In this way you can get right data and send it to right person with IOT and ML .

Data visualization is creating something that allows people to quickly and easily consume and understand something about a data set by looking at it.
I have termed it as “something” here, because how you visualize your data dictates what most people will see in it.

Data Visualization makes it really easy to get a clear idea of a dataset and visualize maybe millions of points into one single picture which helps u learn about various trends which happened over time. It basically helps you get the relation between the information you have plotted in a very concise way.

It also makes the data more natural for us to understand and hence makes it easier for us to identify various trends, patterns, and even anomalies within huge or even small data sets.

This helps the people who make decisions to learn from their mistakes or growth and they can further improve their businesses or projects so that they profit or improve more. It basically helps then gain more insights and make important decisions faster.

Data visualization is a way to represent information graphically that highlights patterns and trends and enables viewers to get quick insights. Color, brightness, size, shape, and motion of visual objects are used to present data, which aid interpretation in ways that just text or numbers or simple graphs do not. The visualization options include scatter plots, Mekko charts, heat maps, bubble clouds, Venn diagrams and more along with traditional pie-charts, bar and line graphs.
Sales forecasts made using data visualization tend to be more accurate than others. When it comes to consumer behavior, visualization helps to see a number of different factors and how they are related to each other, leading to a better understanding.
We can also use data visualization to understand our own operations, identify bottlenecks and pinpoint areas that need improvement. For instance, let’s say there are spikes in customer complaints. When the data is seen in conjunction with certain changes in the support staff, you may find correlation and possibly causes.

Data visualization is the presentation of data in a pictorial or graphical format. It enables decision makers to see analytics presented visually, so they can grasp difficult concepts or identify new patterns.
Machine learning makes it easier to conduct analyses such as predictive analysis, which can then serve as helpful visualizations to present.

Visualizations are tools that can make complex concepts easier for humans to understand. In the words of engineer “a tool doesn’t just make something easier—it allows for new, previously-impossible ways of thinking, of living, of being.”

The utility of data visualization can be divided into three main goals: to explore, to monitor, and to explain. While some visualizations can span more than one of these, most focus on a single goal.
To explore

When users are looking for an open-ended tool that helps them to find patterns and insights in data, a data visualization focused on exploration and fast iteration can help. Exploration tools should have strong connections to other tools that collect (extract), clean (transform), and curate (load)
To monitor

When users need to check on the performance of something, a data visualization focused on monitoring is best. Monitoring tools, such as dashboards, should focus on leading indicators and showing information that is connected to useful and direct actions.

To explain

When users want to go beyond the “what” of a problem and dig into the “why,” a data visualization focused on explanation is ideal. Explanatory visualizations are often hand-crafted to help a broad audience understand a complex subject, and usually are not able to be automated.

Thanks for helping with this!

Right at the onset credit unions should internalize the three most important principles of good visualization, the 3 s’s: simple, standard and scalable . Simple refers to the ease with which the visual reports can be interpreted.