Big data engineers tell you the difference between big data and BI.

When analyzing the big data in the reading guide, analysts need to directly analyze the data from different channels and formats through different algorithms, find the relevant data, and then further analyze and draw more accurate conclusions. In recent years, the big data industry is very popular, and the number of applicants is increasing, which requires us to fully understand. Today, let's take a look at the difference between big data and BI.

1, from the perspective of thinking mode

For traditional BI, big data has both inheritance and development. In Tao's view, the difference between BI and big data is that the former is more inclined to make decisions, and the description of facts is more based on the group * * *, which helps decision makers to grasp macro statistical trends and is suitable for supporting business and operational indicators. Big data has a wider connotation, tends to portray individuals, and more lies in personalized decision-making.

2. From the perspective of tools

Traditional BI uses ETL, data warehouse, OLAP and visual report technology, which belongs to application and display layer technology. At present, it is on the verge of being eliminated because it cannot solve the problem of massive data (including structured and unstructured). The application of big data is a complete technical system, including the use of Hadoop, stream processing and other technologies to solve the ETL problem of massive structured and unstructured data, the use of Hadoop, MPP and other technologies to solve the calculation problem of massive data, the use of redis, HBASE and other ways to solve the problem of efficient reading, the use of Impala and other technologies to achieve online analysis and other issues. Therefore, it is a brand-new industry.

3. From the perspective of data sources

The data sources of big data applications include not only unstructured data, but also various system data and database data. Among them, unstructured data is mainly concentrated on the Internet, some social networking sites and some machines and equipment, which constitutes the data source of big data applications. For big data analysis tools, there are many unstructured data analysis at this stage.

BI system is becoming more and more mature in data integration technology. For data extraction and various data mining requirements, the data integration platform will help enterprises to realize the circulation and interactive use of data, and the implementation of BI application within enterprises is to better share and use data.

4. From the development direction.

The development of business intelligence should start from the traditional business intelligence model. For enterprises, BI is not only an IT project, but also a way of management and thinking. From technology deployment to business process planning, BI has ushered in new development. For big data, at this stage, more big data focus on unstructured data, the emergence of different data analysis tools and the continuous expansion of application scope in the industry. For big data applications, how to deeply integrate with the application industry is the most important.

Regarding the difference between big data and BI, I will share it with you here. If you are interested in big data engineering, I hope this article can help you. If you want to know more about the skills, methods and courses of big data engineers, you are welcome to come and consult.