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Enterprise Data Warehouse: Types, Schemas and Architecture

To stay competitive, modern businesses should be adaptive to make informed decisions based on facts rather than intuitions. However, crucial business data is often distributed across different departments and handled by disparate teams. This leads to siloed thinking and holds back leaders from getting a holistic view of the organization.<br><br>Hereu2019s what this situation could look like The sales team manages data related to customer relationships, sales outcomes, and more. The support team has the customer satisfaction data. Procurement holds information about supply chain management and so on.

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Enterprise Data Warehouse: Types, Schemas and Architecture

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  1. Enterprise Data Warehouse: Types, Schemas and Architecture

  2. Enterprise Data Warehouse: Types, Schemas, and Architecture - C-Metric Solution An Enterprise Data Warehouse (EDW) is a pivotal asset for modern businesses, enabling the consolidation of data from various sources for enhanced decision-making and strategic planning. At C-Metric Solution, we focus on designing EDWs that are robust, scalable, and tailored to meet the unique needs of businesses. Types of EDWs: Primarily, EDWs are classified based on their data storage and management approach. The two main types are: 1.Centralized Data Warehouses: These house all data in a single, central location, offering consistency and unified management. 1.Distributed Data Warehouses: These involve multiple, interconnected data warehouses, ideal for large-scale operations with geographically dispersed data sources.

  3. Schemas in EDWs: Schemas define the structure and design of a data warehouse. The predominant schemas include: Star Schema: This schema is characterized by a central fact table connected to dimension tables. It streamlines queries and enhances performance. Snowflake Schema: Building upon the star schema, this design normalizes dimension tables, thereby minimizing data duplication. Regarding architecture, an EDW's structure comprises multiple elements, including data sources, ETL (Extract, Transform, Load) processes, metadata, and tools for front-end reporting. At C-Metric Solution, we emphasize a layered architecture approach, ensuring data integrity, security, and accessibility. By integrating these elements, C-Metric Solution’s EDW solutions offer businesses a powerful tool for data analysis, reporting, and strategic insight generation, propelling them towards data-driven decision making.

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