Smartbi: Why are self-service BI tools so favored by enterprises?

Time:2022-8-9

In recent years, with the continuous improvement of enterprises' awareness of data-driven value, BI tools have received unprecedented attention and have been favored by more and more enterprises. But there are also some people who don't know much about BI tools. Now I will take you to understand what BI tools are and what are very popular with enterprises now.Self-service BI toolsWhat are the advantages compared with traditional BI tools, so that everyone can accurately choose the BI tool that suits them.

1. What is BI?

BI, that is, business intelligence, is the process of collecting, managing and analyzing business information, with the purpose of enabling decision makers at all levels of the enterprise to gain knowledge or insight, so as to enable them to make decisions that are more beneficial to the enterprise. Business intelligence generally consists of data warehouse, online analytical processing, data mining, data backup and recovery and other parts.

Smartbi: Why are self-service BI tools so favored by enterprises?

2. What is a self-service BI tool?

Self-service BI is self-service business intelligence. In response to the problems that traditional BI tools cannot cure and the urgent needs of the business environment, self-service BI tools emerge as the times require.

3. The difference between self-service BI tools and traditional BI tools

The point of self-service BI tools is to be available to everyone, faster and more efficiently. Self-service BI is aimed at business analysts who do not have an IT background. Compared with traditional BI, it is more flexible and easy to use, and to a certain extent, it can get rid of the heavy dependence on the IT department. Different from the previous "IT-led reporting model", it has turned to a "business-led self-service analysis model".

4. Why are self-service BI tools so popular?

Before the birth of self-service BI tools, traditional BI tools have been the mainstream of the market. Traditional BI tools use large data warehouses as the basis for data analysis, which can help enterprises build large-scale comprehensive data analysis platforms. However, it is mainly aimed at IT personnel, and adopts the mode that business departments provide IT technical response to data analysis requirements. Usually, IT personnel first model according to analysis requirements, build analysis topics, and analyze reports and dashboards. Business personnel Use reports according to a fixed report style.

In this way, most of the business personnel view static reports, and the analysis dimensions and metric calculation methods have been preset during modeling and cannot be changed. As a result, the implementation of traditional BI tools faces the problems of technical difficulty, long deployment and development cycle, and high product cost.

Self-service BI is aimed at business personnel without IT background. By building a data integration platform, IT centrally manages and controls data and distributes data. Business personnel can understand self-service modeling based on business through easy-to-use front-end analysis tools. , Easily carry out exploratory analysis, so as to quickly mine effective information, predict data trends, and achieve data-driven business development.

Smartbi: Why are self-service BI tools so favored by enterprises?

Self-service BI tools greatly reduce the threshold for business personnel to conduct data analysis, and transfer the task of data analysis from IT to business, enabling business departments to quickly realize data analysis requirements according to their own needs, shortening the data analysis cycle, Accelerated data-driven decision making is the main reason behind the rising demand for self-service BI tools.

Through the use of self-service BI tools, the operation and management personnel of enterprises can do data analysis without spending a lot of time on data processing and data mining, but only need to use self-service BI tools to visualize data. Smartbi has good reputation and practicality, and can be used flexibly by beginners and data analysts to improve work efficiency.