Data Warehouse

Data Warehouse

Data Warehouse

A data warehouse can be defined as a store comprising all the databases. It is a centralised database that is prolonged independently from the production system database of a company.
Many companies maintain multiple databases. Instead of some particular business processes, it is established around informational subjects. The data present in this is time dependent and easily accessible. Historical data may also be accumulated in a data warehousing.
Data warehousing is used to support subject-oriented decision-making in a company. When a company joins a supply chain partnership to increase competitiveness, its data warehouse has to be re-designed. The design of data warehouses for supply chain partners has to take into account issues such as data schemas, duplication of data, data security, and homogeneity of data warehouses. This study proposes five approaches to designing data warehousing for supply chain partners: (1) a centralised data warehouse, (2) a coordinated data warehouse, (3) a distributed data warehousing, (4) a federated data warehousing, and (5) a heterogeneous data warehouse. Each approach has different features and provides a high level of data security.

Why Data Warehousing?

Data is the most valuable enterprise asset. A good integrated data management strategy will enhance an organisation’s ability to develop valuable insights that provide greater business value. This strategy is driven by the following needs:
Need Integrated Data: Disparate data sources lead to information silos resulting in decision deficiencies Need Accurate Data: Lack of data standards lead to data quality issues and therefore distorted insights Need Data Governance: Inadequate definitions, unclear ownership and lack of standards can lead to inconsistencies in organisational data management.

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