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What is the necessity of building big data's analysis platform?

2025-02-22 Update From: SLTechnology News&Howtos shulou NAV: SLTechnology News&Howtos > Internet Technology >

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This article will explain in detail the necessity of building a big data analysis platform. The content of the article is of high quality, so the editor will share it with you for reference. I hope you will have a certain understanding of the relevant knowledge after reading this article.

In the era of big data, almost every enterprise flocked to the data analysis platform, especially after the outbreak of the epidemic this year, more business owners realized the great commercial value of data. And it as an intangible asset to support the intelligence of enterprise information.

Generally speaking, the internal operation and business systems of enterprises accumulate a large amount of historical data every day, and some enterprises analyze some scattered data at the shallow level at most. In fact, the real massive data has not been analyzed and utilized effectively.

At the same time, with the continuous increase and accumulation of the system, the data deposited in the depths of the system is more difficult to extract and integrate, and the later report display and visual analysis has become a shell application.

Therefore, the construction of the data analysis platform is very necessary. On the one hand, it can connect the various business systems of the enterprise and open up the data resources from the source. On the other hand, it can also achieve one-stop analysis from data extraction, integration to data cleaning, processing and visualization to help enterprises really extract value from the data and improve their business ability.

1 what is the mysterious data analysis platform?

To put it more popularly, the data analysis platform is to collect and organize all the data of the company, including system data, business data and so on, to mine and analyze the data under a unified data framework. finally, the data is displayed by means of visualization.

Because the data analysis platform involves many components and complex functions, how to combine it organically is the most critical core in its construction process. We might as well take a group's data analysis platform as an example to see what the specific data analysis platform architecture looks like:

Before building a data analysis platform, it is necessary to clarify the business demand scenarios and user needs. Through big data's analysis platform, what valuable information you want to get and what data you need to access? clarify the basic functions of the data platform based on scenario business requirements. The above figure as an example can be divided into four levels from bottom to top:

Data acquisition layer: the bottom layer is a variety of data sources, mainly collecting and analyzing the underlying data of the enterprise, integrating scattered data, including enterprise core business data, user data, log data, group data and so on. There are usually two traditional ways of ETL offline collection and real-time collection.

Data storage and processing layer: with the underlying data, the data is preprocessed according to different requirements and scenarios, and stored in an appropriate persistent storage layer, such as OLAP, machine learning, database, etc.

Data analysis layer: here we will use BI analysis system, such as FineBI, if it is the traditional data mining and SPSS, this layer is mainly to process the data, and then carry out in-depth analysis and mining.

Data application layer: different types of applications are divided according to different business needs, mainly to display and visualize the final data, such as the data report above, dashboard, digital big screen, timely query and so on.

To sum up, the gradual improvement of enterprises' requirements for data and efficiency also provides big data with a platform to show their ability. in the final analysis, the construction of big data platform is to build the enterprise's data asset operation center and give full play to the value of data. support the development of the enterprise.

2 is the data analysis platform really necessary?

Before the enterprise carries on the data analysis platform construction, there is often a question: the enterprise data system is running data normally every day, and the business system is normal and stable, so do we still need the data analysis platform?

The answer is, of course, in the actual enterprise data management, business systems are often not single, but multi-source. Business people seem to use business data every day, but in fact, each other's data are separated from each other and cannot be connected. If you want to achieve data analysis, you have to take data from multiple systems, and then integrate the analysis manually. Obviously, this can not be done by manpower.

This is called data isolated island, and the difficulty of this problem is that it needs to be analyzed across data sources, and the docking between different data sources is very difficult to get through. secondly, the data of enterprises must be massive, and some of them need secondary processing. It is difficult to achieve without the support of the data analysis platform.

In addition, from the perspective of the enterprise business system, if we put the work of data analysis directly on the business system, on the one hand, the performance of the system cannot support such a resource-consuming thing, and the pressure on the system will be great; second, with the accumulation of data, it is difficult for a separate business system to withstand a large amount of data processing, so it is necessary to rebuild a big data processing platform.

Therefore, the emergence of a data analysis platform can not only bear the pressure of data analysis, but also integrate business data, but also improve the performance of data processing to achieve richer functional requirements based on the data platform.

3The construction process of data analysis platform.

The construction process of the data analysis platform can basically be understood from the data analysis process, such as data collection, data integration, data processing, data visualization and so on. The general big data platform will include these processes, which is called one-stop big data platform.

It should be noted here that many enterprises usually mistake the construction of basic data platform for an one-stop data platform. The biggest difference between the two is whether business exploratory analysis is implemented in architecture.

There are many types of one-stop data platform architecture, and now the more popular is self-service analysis, that is, active enterprise data analysis platform, which allows business personnel to directly participate in data analysis, fully explore and analyze data with the help of BI platform, and can decompose huge tasks into small tasks.

On the necessity of building big data analysis platform is shared here, I hope that the above content can be of some help to you, can learn more knowledge. If you think the article is good, you can share it for more people to see.

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