Operational data analysis includes key indicator analysis, data collection, data dimension analysis, application scenarios, and data analysis software.

1, key indicator analysis:

Key indicators are important data to measure business performance and operational effectiveness, such as sales, user growth rate, conversion rate, etc.. Through the analysis of key indicators, you can understand the overall operation of the enterprise and business development trend, so as to adjust the operation strategy in a timely manner.

2. Data Collection:

Data collection is the foundation of operational data analysis, including the process of collecting data from various data sources (e.g., websites, mobile apps, social media, etc.), as well as cleaning, organizing and storing data. Accurate and complete data collection is a prerequisite for effective analysis.

3, data dimension analysis:

Data dimension refers to the division and analysis of data from different perspectives and dimensions, such as time dimension, geographic dimension, user attribute dimension and so on. By analyzing different data dimensions, you can gain insight into user behavior, product performance, market trends and other aspects of information to provide a more accurate basis for decision-making.

4, application scenarios:

Operators big data first began as a result of operators through the user's actions to use the Internet, define the needs of the enterprise to provide a way to provide customer leads, while the establishment of a bridge between the enterprise and the user, after continuous evolution and innovation, added a lot of new modes, the development of the way it is today.

Back in 2019, Telecom was the first to put forward the concept of "carrier big data", when Telecom developed a modeling platform to provide outbound seats to users, but due to the Telecom user base compared to the other two big brothers, is really too small, and soon died, and then Unicom stepped in to build the The "carrier big data 2.0" version, which is the prototype of the dpi we are using today.

5, data analysis software:

In the wave of big data, a large amount of historical data is generated every day within the enterprise. Although some companies will carry out preliminary analysis of these scattered data, but the real effective data has not been fully mined and analyzed.