Shulou(Shulou.com)06/03 Report--

The word "information explosion" must not have much freshness for everyone, but big data, caused by the information explosion, has increasingly become the darling of enterprises, and more and more enterprises have gradually realized the importance of big data. But most enterprises often only look at the surface, blindly follow the trend, collect a large amount of data, useful and useless, the industry of the enterprise I am afraid that failing to grasp big data's tuyere will lead to my backwardness and launch various information projects. as a result, although enterprises have a lot of data, they cannot play the role that the data should play, and even form isolated islands of information one after another. not only can it not become a resource to assist the development of enterprises, but even become a burden for the development of enterprises.

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At the same time, with the advent of big data era, information is growing at an explosive rate every day, and its form and content are also constantly changing. from the initial text to the Internet, various forms of information emerge in endlessly; secondly, with the demand for more and more data visualization, maps, 3D physical structures and other technologies will be more widely used. Therefore, when human cognitive ability is more and more limited by the traditional visualization form, the value hidden behind big data will be difficult to play. If the limitation of the display form reduces the readability and timeliness of the data, thus affecting the rapid implementation of users' understanding and decision-making, then big data will lose its value. Visualization is the only way to give full play to big data's value. But how exactly should it be applied?

When it comes to data visualization, first of all, we need to know the characteristics of data visualization.

1. Intuitive-showing the complicated big data directly in front of the decision-making can save time and make the work more efficient.

2. Interaction-- use data to better analyze users, provide targeted services for users, and increase the interaction with users behind the data.

3. Real-time-in the era of explosive growth of data, only when we have a good grasp of the time limit, can we grasp the opportunity more acutely.

After understanding the features, how should big data's visualization be realized?

Result display

Data visualization refers to organizing and displaying data manually or otherwise in graphic or chart format, so that the audience can view the analysis results more clearly, simplify the complexity of the data being used, and understand and master the data production methods being used. Visualization is not a new concept, and the concept of using pictures (typesetting, color, contrast, and shape) to convey or understand data is not new. Nowadays, computers can be used to process large amounts of data quickly, making visualization more valuable. Looking to the future, one can expect the process of data visualization to continue to develop, perhaps more of a mixture of art and science than digital computing technology.

Real-time satisfaction

An exciting example of the evolution of data visualization is how the industry shifts the process of data visualization to the process of generating and publishing charts and graphs for audience review and careful consideration, thus setting expectations for interactive visualization.

Through interactive visualization, people can make more use of the concept of data visualization, and further make use of technology to enable viewers to interact with data and provide users with self-service capabilities. Interactively drill down into the generated pictures, charts, graphics (access to more or specific details) in real time (or near real time) to change the data displayed (which may be different time frames or events) and how to handle and / or render (bar charts instead of pie charts may be selected). This makes visualization more efficient and personalized.

Instrument panel

As discussed earlier, people actually collect and accumulate large amounts of data every day, and organizations rely on that information for a variety of reasons.

This data uses a variety of reporting formats, including data dashboards. Like everything, there are all sorts of concerns about the definition of data dashboards.

Regardless of its definition, if properly designed and built, any dashboard has the ability to provide timely and important information to the audience for use by decision makers.

With the maturity of technology, more and more companies have launched visualization tools, such as Aliyun, Baidu Cloud and Jerry Digital V-Nice Date. The richness of tools has increasingly enhanced the data visualization ability of enterprises.

Operational intelligence

Operational Intelligence (OI) is an analytical method that attempts to provide visibility and insight through (usually machine-generated) operation or event data, running queries fed against data streams in real time to produce analysis results as operation instructions, which can be performed immediately by manual or automatic operations (a clear example of transforming a dataset into value).

Of course, today, with the rapid development of science and technology, big data's ways of visualization will never stop at the above. I believe that with the passage of time, more and better ways will continue to emerge. Big data's real charm and value will also gradually unveil the mystery and become the real wealth of the enterprise.

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