Proposed Hybrid Data Warehouse Architecture Based on Data Model

Data warehousing has come a long way from its inception. In the present scenario, data warehousing is evolving into rich system which is capable of furnishing key performance metrics to top-level management, capability of analytical strength to middle-level management and corrective data back to bottom-level based on information derived from the analytical system. The data warehouse market is currently edged by business-driven solutions focussing on domain specific challenges. The present business nuances of the global village crop up innovative and stiffer challenges for the data warehouse designers and architects. Although, there are numerous methodologies available in the market to cope up to this challenges, the evolutions have not created much of an impact in the global environment and the competitive market posed has prompted to venture into newer horizons over and over again. Data warehouse is a repository of an organization’s electronically stored and collected data. Data warehouses are designed to facilitate reporting and analysis.A data warehouse comprises of a standardized, consistent, clean and integrated form of data sourced from various operational systems to be used in the organizational needs, structured in a way to specifically address the reporting and analytical requirements.This definition of the data warehouse primararily focuses on the data storage and acts much like a buffer to absorb continuous collection of data, which gets processed through numerous iterative steps to evolve as information, awaited by all tiers of an organization for various decision-making moves. However, the ways to retrieve and analyze data, to extract, transform and load data, and to manage the data dictionary are also considered essential components of a data warehousing system. Many references to data warehousing use this broader context. Thus, an expanded definition for data warehousing includes business intelligence tools, tools to extract, transform, and load data into the repository, and tools to manage and retrieve metadata, that is, data about data. There are mainly three classifications of data warehouse architecture based on data model given by Inmon and Ralph. There is a fourth classification that has been discussed in a paper named “Comparison of Data Warehouse Architecture Based on Data Model” and it has been compared with the other three existing models. Now, in this paper named “Proposed Hybrid Data Warehouse Architecture Based on Data Model” we have classified a fifth variation to the already existing ones and the pictorial presentation has been ensured to establish it. The model is conceived on the line of Hybrid Architecture and Hybrid Implementation. The architecture and the implementation are bi-directional and the flow is to-and-fro.