This is a unique part of our data science journey, and it is so important that we spend some time and effort looking through it and understanding what this process is all about. We can understand the importance of data visualization when it comes to our data analysis. It can take all of the complex relationships that we have been focusing on in our analysis and puts them in a graph format, or at least in another visual format that is easier to look through.
Sometimes, looking at all of those numbers and figures can be boring and really hard to concentrate on. It can take a long time for us to figure out what relationships are present, and which ones are something that we should ignore. But when we put the information into some kind of graph form, such as a graph, a chart, or something similar, then we will be able to easily see some of the complex relationships that show up, and the information will make more sense overall.
Many of those who are in charge of making decisions based on that data and on the analysis that you have worked on will appreciate having a graph or another tool in place to help them out.
Having the rest of the information in place as well can make a difference and can back up what you are saying, but having that graph in place is one of the best ways to ensure that they are able to understand the data and the insights that you have found.
To make it simple, data visualization is going to be the presentation of data that shows up in a graphical or a pictorial format of some kind or another. It is going to enable those who make the big decisions for a business to see the analytics presented in a more visual manner so that they can really grasp some of the more difficult concepts or find some new patterns out of the data that they would never have known in any other manner.
There are a lot of different options that you are able to work with when it comes to data visualization, and having it organized and ready to go the way that you like, using the right tools along the way, can make life easier. With an interactive type of visual, for example, you will be able to take this concept a bit further and use technology to drill down the information, while interactively changing what data is shown and how it is processed for you.
History
As we can imagine, the process of visualization, and using pictures to help us understand the data in front of us is something that has been around for a long time. Whether we look at the pictures that show up in our books or even maps and graphs that were found in the 17th century and before, we have been using images and more to help us make sense of the world around us and all of the data that we have to sort through can really be understood with some of these visuals as well.
However, it is really a big boost in technology that has helped to make data visualization something that is as popular as it is today. For example, computers are really making it possible for us to process a large amount of data, and we are able to do this at faster speeds than ever before. Today, the data visualization and all that comes with it is an industry or a field that is rapidly evolving. Add to it that this is now something that needs a nice blend of science and art and that it can go a long way in helping us to work with our own data analysis, and it is no wonder that these visuals are as popular as they seem.
Why Is Data Visualization So Important?
The next thing that we need to take a look at here is why data visualization is so important to us or the importance of data visualization. The reason that data visualization is something that we want to spend our time and energy on is because of the way that someone is able to process information. It is hard to gather all of the important insights and more on a process when we have to just read it off a table or a piece of paper. Sure the information is all right there, but sometimes it is still hard to form the conclusions and actually see what we are doing when it is just in text format for us.
For most people, being able to look at a chart or a graph or some other kind of visual can make things a little bit easier.
Because of the way that our brains work and process the information that we see, using graphs and charts to visualize a large amount of complex data is going to be so much easier compared to pouring over some reports or spreadsheets.
When we work with data visualization, we will find that it is a quick and easy way to convey a lot of hard and challenging concepts, usually in a manner that is more universal. And we are able to experiment with the different scenarios by using an interactive visual that can make some slight adjustments when we need it the most.
This is just the beginning of what data visualization is able to do for us though, and it is likely that we will find more and more uses for this as time goes on. Some of the other ways that data visualization will be able to help us out will include:
- Identify areas that will need the most attention when it comes to improvements and attention.
- Help us to figure out which of our products we should place where.
- It can clarify which factors are the most likely to influence the behavior of a customer.
- It can make it easier to tell and make predictions about our sales volumes, whether these volumes are going to be higher or lower at a specific time period.
The process of data visualization is going to help us change up the way that we can work with the data that we are using. Data analysis is supposed to respond to any issues that are found in the company in a faster manner than ever before.
And they need to be able to dig through and find more insights as well, look at data in a different manner, and learn how to be more imaginative and creative in the process. This is exactly something that data visualization is able to help us out with.
How Can We Use Data Visualization?
The next thing that we need to take some time to look at is how companies throughout many industries are able to use data visualization for their own needs. No matter the size of the company or what kind of industry they are in, it is possible to use some of the basics of data visualization in order to help make more sense of the data at hand. And there are a variety of ways that this data visualization will be able to help you succeed.
The first benefit that we can look at is the fact that these visuals are going to be a great way for us to comprehend the information that we see in a faster fashion. When we are able to use a graphical representation of all that data on our business, rather than reading through charts and spreadsheets, we will be able to see these large amounts of data in a clear and cohesive manner.
It is much easier to go through all of that information and see what is found inside, rather than having to try and guess and draw the conclusions on our own.
And since it is often much faster for us to analyze this kind of information in a graphical format, rather than analyzing it on a spreadsheet, it becomes easier for us to understand what is there. When we are able to do it in this manner, it is so much easier for a business to address problems or answer some of their big questions in a timely manner so that things are fixed without issue or without having to worry about more damage.
The second benefit that comes with using data visuals to help out with the process of data science is that they can really make it easy to pinpoint some of the emerging trends that we need to focus on. This information is within the data, and we are going to be able to find them even if we just read through the spreadsheets and the documents.
But this takes a lot of time, can be boring, and often it is hard for us to really see these correlations and relationships, and we may miss out on some of the more important information that we need.
Using the idea of these visuals to handle the data, and to discover trends, whether this is the trends just in the individual business or in the market as a whole, can really help to ensure that your business gains some big advantages over others in your competition base. And of course, any time that you are able to beat out the competition, it is going to positively affect your bottom line.
When you use the right visual to help you get the work done, it is much easier to spot some of the outliers that are present, the ones that are more likely to affect the quality of your product, the customer churn, or other factors that will change your business. In addition, it is going to help you to address issues before they are able to turn into much bigger problems that you have to work with.
Next on the list is that these visuals are going to be able to help you identify some relationships and patterns that are found in all of that data that you are using. Even with extensive amounts of data that is complicated, we can find that the information starts to make more sense when it is presented in a graphic format, rather than in just a spreadsheet or another format.
With the visuals, it becomes so much easier for a business to recognize some of the different parameters that are there and how these are highly correlated with one another. Some of the correlations that we are able to see within our data are going to be pretty obvious, but there are others that won’t be as obvious. When we use these visuals to help us find and know about these relationships, it is going to make it much easier for our business to really focus on the areas that are the most likely to influence some of our most important goals.
We may also find that working with these visuals can help us to find some of the outliers in the information that is there. Sometimes these outliers mean nothing. If you are looking at the charts and graphs and find just a few random outliers that don’t seem to connect with each other, it is best to cut these out of the system and not worry about them.
But there are times when these outliers are going to be important and we should pay more attention to them.
If you are looking at some of the visuals that you have and you notice that there are a substantial amount of them that fall in the same area, then you will need to pay closer attention. This could be an area that you can focus your attention on to reach more customers, a problem that could grow into a major challenge if you are not careful, or something else that you need to pay some attention to.
These visuals can also help us to learn more about our customers. We can use them to figure out where our customers are, what kinds of products our customers would be the happiest with, how we can provide better services to our customers, and more. Many companies decide to work with data visualization to help them learn more about their customers and to ensure that they can really stand out from the crowd with the work they do.
And finally, we need to take a look at how these visuals are a great way to communicate a story to someone else. Once your business has had the time to uncover some new insights from visual analytics, the next step here is to communicate some of those insights to others. It isn’t going to do you much good to come up with all of those insights, and then not actually show them to the people responsible for key decisions in the business.
Now, we could just hand these individuals, the ones who make some of the big decisions, the spreadsheets and some of the reports that we have. And they will probably be able to learn a lot of information from that. But this is not always the best way to do things.
Instead, we need to make sure that we set things up with the help of a visual, ensuring that these individuals who make the big decisions can look it over and see some of the key relationships and information at a glance.
Using graphs, charts, and some of the other visuals that are really impactful as a representation of our data is going to be so important in this step because it is going to be engaging and can help us to get our message across to others in a faster manner than before.
As we can see, there are a lot of benefits that come in when we talk about data visualizations and all of the things that we are able to do with them. Being able to figure out the best kind of visualization that works for your needs, and ensuring that you can actually turn that data into a graph or chart or another visualization is going to be so important when it is time to work with your data analysis.
We can certainly do the analysis without data visualization. But when it comes to showcasing the findings in an attractive and easy to understand format, nothing is going to be better than data visualization.
How to Lay the Groundwork
Before we try to implement in a brand new technology of any sort, there are going to be a few types of steps that we need to take and go through to see the results.
Not only is it important for us to have a nice solid grasp on the data that we want to use which is something that should happen during the data analysis part of the process, we also need to understand three other important things including the needs of the company, the goals of the company, and the audience of your company.
Some of the things that have to happen before you can prepare and organize all of the data that you have and complete this kind of data visualization will include:
- Understand the data that we need to visualize in the first place. This means that we need to know how much cardinality is present in the data, meaning how much uniqueness is going to show up in the columns, and we need to know the size of the data. Some of the algorithms that we will use to work on the data visualization are not going to do as well when it comes to very large sets of data.
- Determine what you would like to visualize, and the kind of information that we want to be able to communicate with this. This will make it a bit easier to figure out which type of visual we want to be able to go within this process.
- Know the audience that we are working with and understand how they are going to process the visual information that you want to show off. Management may need a different visual than a team. Those in manufacturing may need a different visual than someone in a more creative role. Being able to make the visual fit to the audience so that they can actually utilize the information is going to be a critical step.
- Use a visual that is able to convey the information in the form that is not only the best but also the simplest, for your audience. There are a lot of cool visuals out there that you can work with, and they can offer a lot of different ways to show your data. But if the visual is too difficult to understand, it is not going to make anyone happy. Put away some of the neat gadgets and find the best way to showcase that information that makes the most sense to your audience.
Once you have been able to go through and answer all of the initial questions that we had about the data type that we would like to work with, and you know what kind of audience is going to be there to consume the information, it is time for us to make some preparations for the amount of data that we plan to work within this process.
Keep in mind here that big data is great for many businesses and is often necessary to make data science work. But it is also going to bring in a few new challenges to the visualization that we are doing. Large volumes, varying velocities, and different varieties are all going to be taken into account with this one.
Plus, data is often going to be generated at a rate that is much faster than it can be managed and analyzed so we have to figure out the best way to deal with this problem.
There are factors that we need to consider in this process as well, including the cardinality of the columns that we want to be able to work with.
We have to be aware of whether there is a high level of cardinality in the process or a low level. If we are dealing with high cardinality, this is a sign that we are going to have a lot of unique values in our data. A good example of this would include bank account numbers since each individual would have a unique account number.
Then it is possible that your data is going to have a low cardinality. This means that the column of data that you are working with will come with a large percentage of repeat values. This is something that we may notice when it comes to the gender column on our system. The algorithm is going to handle the amount of cardinality, whether it is high or low, in a different manner, so we always have to take this into some consideration when we do our work.
Different Types of Data Visualization Available
As you go through and start to work on adding some visualizations to your own project, you will quickly notice that there are a lot of choices that you are able to make. And all of them can work well depending on the kind of data that you are working with, and the way that you would like to present it.
Sometimes the question that you are asking out of the data will help to determine which type of visualization is going to be the best for your own needs.
There are options like bar graphs, line graphs, histograms, pie charts, and more that can all show the information if you are trying to separate information into groups and see where your customers lie or which decision is the best for you, something like a scatterplot could be the best option to work with.
There are a lot of options when it comes to working with visuals, and we have to just figure out which one is the best for our needs.
When you are first exploring some of the new data that you have collected, for example, you may find that something like an auto-chart is the best option for your needs. This is because they can give you kind of a quick view into a large amount of data, in a way that other options just are not able to do. It may not be the final step that you take, but it is going to make a difference in how well you are able to understand the data in the beginning, and can lead you on the right path to picking out models and algorithms to work with later on.
This kind of data exploration capability is going to be helpful, even to those who are more experienced in machine learning, data science, and statistics as they seek to speed up the process of analytics because it is going to eliminate some of the repeated samplings that has to happen for each of the models that you are working on overall.
None of the visual options are necessarily going to be bad ones, we just have to learn which one is the best option for the data we have, and for the uses that we want to do with the data. Each set of data is going to lend itself well to one type of visual or another, and having a good understanding of what you are expecting out of this data, and what your data contains in the end, can help us to figure out which visual we are most interested in.
Data visualization is definitely a part of data science that we do not want to forget about.
Being able to make this work for our needs, and understanding some of the process that comes with it, as well as why we actually need to work with a visual overall, can be important. Make sure to figure out which visual is going to be the best for your needs to ensure that you will get the best way to understand the complex relationships in your data in no time.
