逻辑运算才能形成画像，因此，电力客户标签体系统建设的关键是设计一种高效

Logical operations can form a portrait. Therefore, the key to the construction of the power customer tag body system is to design an efficient data storage technology to ensure the effective management of customer tags. In terms of the realization of big data technology, Hadoop data warehouse and Hive can be combined. They are common big data processing tools in the business field and can efficiently manage, analyze and store massive data. By analyzing the distribution characteristics, missing values, outliers and other indicators of the research data, the data problems found are fed back to the original business system, so as to facilitate the inspection and correction of data problems and improve data quality

Logic operation can form a portrait, therefore, the key to the construction of power customer label body system is to design an efficient data storage technology to ensure the effective management of customer labels. In the implementation of big data technologies, you can combine Hadoop Data Warehouse and Hive, the most common large data processing tools in the business world, to efficiently manage, analyze, and store massive amounts of data. By analyzing the distribution characteristics, missing values and outliers of the data, the data problems found are fed back to the original business system, the inspection and correction of data problems are promoted, and the data quality is improved.

Therefore, the key to the construction of the system is to design an efficient data storage technology to ensure the effective management of customer tags. In the implementation of big data technology, we can combine Hadoop data warehouse and hive, which are common big data processing tools in the business field, and can efficiently manage, analyze and store massive data. By analyzing the data distribution characteristics, missing values, outliers and other indicators, the data problems found are fed back to the original business system, which promotes the inspection and correction of data problems and improves the data quality