Total Page Preview: 000000009596
Data Warehouse Three Tier Architecture
In this acticl I am going to explain Data warehouse three tier architucture
Data warehouse adopt a three tier architecture,these are:
These 3 tiers are:
-
Bottom Tier (Data warehouse server)
-
Middle Tier (OLAP server)
-
Top Tier (Front end tools)
1. Bottom Tier:
Data warehouse server fatch only relevant information based on data mining (mining a knowledge from large amount of data) request.
-
It is a warehouse database server.
-
Data is fed using Back end tools and utilities.
-
Data extracted using programs called gateways
-
It also contains Meta data repository.
Bottom Tier Contains:
-
Data warehouse.
-
Metadata Repository.
-
Data Marts.
-
Monitoring and Administration.
Data Warehouse:
It is an optimized form of operational database contain only relevant information and provide fast access to data.
Metadata repository:
It figure out that what is available in data warehouse.
It contains:
-
Structure of data warehouse.
-
Data names and definitions.
-
Source of extracted data.
-
Algorithm used for data cleaning purpose.
-
Sequence of tranformation applied on data.
-
Data releted to system performance.
Data Marts:
Subset of data warehouse contain only small slices of data warehouse Example: Data partaining to the single department.
Data Marts is two types:
-
Dependent - sourced directly from data warehouse
-
Independent - sourced from one or more data sources
Monitoring And Administration:
-
Data Refreshment
-
Data source synchronization
-
Disaster recovery
-
Managing data growth, database performace
-
Controlling the number & range of queries
-
Limiting the size of data warehouse
2. Middle Tier (OLAP Server):
It presents the users a multidimensional data from data warehouse or data marts.
Typically implemented using two models:
-
ROLAP(Relational OLAP) Model - Present data in relational tables.
-
MOLAP(Multidimensional) Model - Present data in array based structures means map directly to data cube array structure.
3. Top Tier:
It is front ent client layer. Query and reporting tools:
Reporting Tools: Production reporting tools and Report writers
Managed query tools: Point and click creation of SQL used in customer mailing list.
Analysis tools: Prepare charts based on analysis.
Data Mining Tools: mining knowledge, discover hidden piece of information, new correlatons, useful pattern
Thank You
About Author
Brijesh Kumar
Database Developer
I have more then 6 years Experience in Microsoft Technologies - SQL Server Database, ETL
Azure Cloud - Azure SQL Database, CosmosDB, Azure Data Factory, PowerBI, Web Job, Azure Function, Azure Storage, Web Apps, Powershall
and Database Migration On-Premise to Azure Cloud.
LinkedIn : https://www.linkedin.com