The Use Cases of Data Virtualization Technology. May 10th, 2018
A discussion about how data virtualization can be used successfully for implementing numerous types of use cases as well as it's strengths and weaknesses. Additional insight into how some can be integrated into one unified data delivery platform.
Data lakes are setup as large physical storage repositories. Data from all kinds of sources is copied into this repository, which is commonly developed with Hadoop. But is this centralized storage approach really feasible and practical? Additionally, the users of data lakes are data scientists and other investigative users.
Not every organization is happy with the reporting and analytical performance of their data warehouse environment. One customer indicated that some of their online reports take at least ten minutes to complete. Ten minutes is a long time if you have to wait for a report to show up on your screen.
The classic data warehouse architecture, consisting of a chain databases and ETL processes, has served may organizations well the last twenty-five years; see Figure 1. But is it the still the right architecture?