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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:
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Bottom Tier (Data warehouse server)
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Middle Tier (OLAP server)
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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.
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It is a warehouse database server.
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Data is fed using Back end tools and utilities.
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Data extracted using programs called gateways
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It also contains Meta data repository.
Bottom Tier Contains:
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Data warehouse.
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Metadata Repository.
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Data Marts.
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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:
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Structure of data warehouse.
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Data names and definitions.
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Source of extracted data.
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Algorithm used for data cleaning purpose.
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Sequence of tranformation applied on data.
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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:
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Dependent - sourced directly from data warehouse
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Independent - sourced from one or more data sources
Monitoring And Administration:
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Data Refreshment
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Data source synchronization
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Disaster recovery
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Managing data growth, database performace
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Controlling the number & range of queries
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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:
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ROLAP(Relational OLAP) Model - Present data in relational tables.
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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