CDEF: Conceptual Data Extraction Framework for Heterogeneous Data
Apurva Kulkarni, Chandrashekar Ramanathan · 2022
The rapid growth of data within enterprises accentuates the two virtues of data, i.e. volume and variety. Both these characteristics are tightly coupled. High volume increases the likelihood of data heterogeneity concerning data models, data formats, and database systems. Large amounts of heterogeneous data need to be extracted and engineered before it becomes suitable for data analysis. The extraction of relevant data from the pile of big data reservoir is a very crucial task. Fetching the data across different data sources creates the need for data extraction and transformation.