A study on multisource heterogeneous data integration methods based on ETL technology
When processing the heterogeneous data over the years in the multi-source big data fusion stage,multi-index and multi-dimensional problems are involved,and cleaning,transformation,mapping and alignment operations are needed.Related data processing tools and methods are gradually emerging,but it is still difficult to solve the problem of cross-fusion of a large number of data.Multi-source heterogeneous data fusion methods were studied based on ETL technology,the common ETL tools and data fusion techniques were analyzed,including data extraction,conversion,loading tools,and the data-processing algorithms.This paper analyzes the heterogeneity of data sources,data structure difference,difficulty of data update frequency,and studies the methods of modular extension and repeated use of ETL tools from modular design,logical and parameter separation,standardized component library,configuration file in lightweight JSON format,so as to better handle large-scale heterogeneous data.It solves the problem of cross-fusion in the multi-source big data fusion stage,which is of great significance to improve data processing efficiency,ensure data quality,and support more in-depth data analysis and decision-making.
NETL
NSTL
万方数据
