![]() ![]() ![]() Then one day, someone wanted to find data not for a given application but for across the entire organization. Soon, there were lots of applications in organizations (DeLone, 1988 VanLommel and DeBrabander, 1975). To expedite the development process, the requirements gathered were very specific to the end user’s immediate needs (Gould, et al., 1991). Applications were created by studying end-user requirements, then tailoring the application to the requirements. ![]() These applications greatly relieved burdensome work (Gould, et al., 1991). In the beginning, there were applications (Jarke, et al. Why not try Integrate.io yourself with a 14-day free trial? Before the Data Warehouse Integrate.io also streamlines the data integration process with ETL, Reverse ETL, and super-fast Change Data Capture (CDC) tools. This data warehouse integration tool can integrate warehouses with lakes to give your business all the benefits of a lakehouse. Integrate.io has seen the evolution of both the data warehouse and data lakehouse. Combining Textual Data and Structured Data.This article describes that evolution and the state of affairs in today’s world. The evolution of data architecture has proceeded at the speed of light. This article examines the architectural transformations occurring today Introductionĭata architecture began innocently enough in the 1960s with the advent of the first application, and it has been evolving ever since. Each of these transformations has had its own similarities and peculiarities. Then, people added text to data warehouses. An evolution of data architecture has been occurring. ![]()
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