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1. Role of Database
Management System in
A Data Warehouse

2. Table of Content
• What is Data Warehouse
• Example of Data Warehouse
• Data Warehouse System is also
Known By
• How Data warehouse works
• Types of Data Warehouse
• General stages of Data Warehouse
• Components of Data Warehouse
• Five Different Groups of Data
Warehouse
• Who needs Data Warehouse
• Application Areas of Data
Warehouse
• Steps to Implement Data
Warehouse
• Key Steps in Data Warehouse
• Role of Database Management
System in A Data Warehouse
• Our Relevant Services
• Why You Need Data Warehouse
Assignment Help
• Why Choose Us
• Contact Us

3. What is Data Warehouse
• A Data Warehousing (DW) is a system for receiving and handling data from
different origins
• It provides meaningful business insights
• It is typically utilized to combine and examine business data from various origins
• It is the core of the Business Intelligence system that is developed for data
analysis and presentation
• It is a combination of technologies and parts that aids the important use of data
• It is the automated warehouse of a huge amount of data by a business
• It is designed for query and analysis rather than transaction processing
• It is a transforming data process into information
• To make a difference, it makes available to users

4. Example of Data Warehouse
• Product information
• Sales data
• Customer
• Supplier details
• Amazon Redshift: it is a petabyte-scale data warehouse cloud solution
• AWS Data Pipeline: it is web service designed for transporting
data between existing AWS data services
• Elastic MapReduce: It is an easily managed Hadoop solution. It runs
on top of the AWS services platform

5. Data Warehouse System is also Known By
• Decision Support System (DSS)
• Executive Information System
• Management Information System
• Business Intelligence Solution
• Analytic Application
• Data Warehouse

6. How Data warehouse Works
• A Data Warehouse acts as a primary repository where data arrives
from one or more data sources.
• From the transactional system and other RDBMS, Data flows into a
data warehouse.
Data may be:
• Structured
• Semi-structured
• Unstructured data
• The data is prepared, modified, and inserted so that users can obtain
the prepared data in the Data Warehouse through BI instruments

7. Types of Data Warehouse
• Enterprise Data Warehouse (EDW)
• Operational Data Store
• Data Mart

8. General stages of Data Warehouse
• Offline Operational Database
• Offline Data Warehouse
• Real time Data Warehouse
• Integrated Data Warehouse

9. Components of Data Warehouse
• Load manager
• Warehouse Manager
• Query Manager
• End-user access tools

10. Five Different Groups of Data Warehouse
• Data Reporting
• Query Tools
• Application development tools
• EIS tools
• OLAP tools and data mining tools

11. Who needs Data Warehouse
• Decision-makers: They handle huge amount of data
• Users: They focus on complex methods to get information from various
data sources
• It is necessary for those characters who need a systematic method for
making choices
• It will help the user to get fast performance on a massive amount of data
• It is a necessity for news, grids, or plans that a Data warehouse proves
useful
• The data warehouse is the first step to discover hidden patterns of data-
flows and groupings

12. Application Areas of Data Warehouse
• Airline
• Banking
• Healthcare
• Public sector
• Investment and Insurance sector
• Retain chain
• Telecommunication

13. Steps to Implement Data Warehouse
• Enterprise strategy
• Phased delivery
• Iterative Prototyping

14. Key Steps in Data Warehouse
• Define project scope
• Determine business requirements
• Define Operational Datastore needs
• Obtain or develop Extraction devices
• Define Data Warehouse data specifications
• Document missing data
• Maps Operational Data Store
• State Data Warehouse Database design
• Citation Data from Operational Data Store
• Load Data Warehouse
• Maintain Data Warehouse

15. Role of Database Management System in A
Data Warehouse
• A data warehouse is a relational database
• It is intended for query and report instead of transaction processing
• It normally includes historical data obtained from transaction data
• However, it can incorporate data from other sources
The principal difference is
• Databases are combined sets of stored data
• Data warehouses are information systems created from various data
sources like servers
• Data warehouses are utilized to interpret data

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