Dynamic data is an enormous part of Big Data. Dynamic data is also known as transactional data. it denotes the information that is asynchronously changed. It is the information that is constantly updated. It changes over time as new information and data becomes available. This means that the patterns here change. The model accuracy can degenerate over time as that data changes.
Static Data vs. Dynamic Data
Static Data, once it has been created, can’t change. For example, static data can be a newspaper. Once the newspaper has been printed out, it can’t be changed.
On the other hand, dynamic data comes in the forms of websites, audio and images. It can be changed and updated. WebPages are categorized as dynamic data because the information can be changed and updated. For example, let’s take a sports website. It shows live scores of some sport. It can be updated in real time as the scores change.
Another reason why websites are classified as such data is because of the fact that they can interact with their users. And of course, the users can interact with the website as well. The user experience they provide for their visitors makes them the perfect fit for this category.
However there are problems with this as well. When you’re using dynamic data, rather than static data, it can be not as accurate and trustworthy. For instance, not all information on the internet/ websites is truthful or accurate. This is because nowadays anyone can create a website.
Although limited, static data provides and enables a much easier access to information.
Data has grown enormously in size over the past few years. This is the reason why many companies have to increase their efficiency in handling this data. However, those same companies don’t transfer from static to dynamic data because it seems like a daunting job to do. This has enormous consequences. For example, almost 50% of the enterprises don’t survive because of their inaccurate data. This false, bad data costs them millions in the U.S. only.
As the market is growing more competitive than ever, the customers’ needs are growing as well. And, if their needs aren’t met instantly, they will simply go elsewhere. They want a brand that will give them a positive user experience.
If the data is static, it will decay the moment it is collected. This is because we as people are not static and the data we generate is not static as well. It changes constantly. This is why dynamic data is so important. It updates in almost real-time as these changes happen. You can freely analyze your audience and create personalized user experience.
Dynamic data is also an excellent method for profiling personas. It identifies what the buyer personas are, why they are needed and how you can create them. To make the buyer personas come to life, progressive persona profiling is used.
It is a process similar to creating the buyer personas. The difference here is that this system now mimics the fluid nature of human decision-making and behavior.
It is obvious that dynamic data is the key to a successful company or business. If you have a business it is important for you to adapt to continuous changes. This is the only way you will preserve the integrity of your brand and grow in size on the market.