2. Data Warehousing & Data Mining
PEC-IT 6028(6584)
Name: Sk Akram
University Roll No: 12500220008
Year: 3rd
Branch: IT
3. Content:
โ Introduction to 3 tier Data Warehousing Architecture?
โ 3 tier Architecture
โ Bottom tier(Data Warehouse Server)
โ Middle tier(OLAP Server)
โ Top tier(Front end tools)
โ Conclusion
โ Reference
4. Introduction to 3 tier data Warehouse
Architecture:
Data warehousing is a process of collecting, storing, and managing large
amounts of data from different sources. It is used to analyze and report
on data to create meaningful insights. A 3 tier data warehouse
architecture is a popular approach to data warehousing that separates
the data warehouse into three distinct layers: the data source layer, the
processing layer, and the presentation layer.
5. 3 tier data Warehouse Architecture:
1. Top Tier
2. Middle Tier
3. Bottom Tier
6. Top Tier (Front End Tool)
โ A top-tier that contains front-end tools for displaying results provided by OLAP, as
well as additional tools for data mining of the OLAP-generated data.
โ It is front end client layer. >Query and reporting tools
โ Reporting Tools: โProduction reporting tools
โ Report writers Managed query tools: Point and click creation of
โ SQL used in customer mailing list. Analysis tools: Prepare charts based on analysis
โ Data mining Tools: mining knowledge, discover hidden piece of information, new
correlations, useful pattern
7. Middle Tier (OLAP Server)
โ A middle-tier which consists of an OLAP server for fast querying of the data
warehouse.
โ Middle Tier: OLAP Server
โ It presents the users a multidimensional data from data warehouse or data marts.
โ Typically implemented using two models:
โ ROLAP Model Present data in relational tables
โ MOLAP Model Present data in array based structures means map directly to data
cube array structure.
8. Bottom Tier (Data Warehouse Server)
โ A bottom-tier that consists of the Data Warehouse server, which is almost always an
RDBMS. It may include several specialized data marts and a metadata repository.
โ Data Warehouse server fetch only relevant information based on data mining (mining a
knowledge from large amount of data) request. Eg: customer profile information
provided by external consultants.
โ โData is feed into bottom tier by some backend tools and utilities.
9. Conclusion:
โ A 3 tier data warehouse architecture is a popular approach to data
warehousing that separates the data warehouse into three distinct layers:
the data source layer, the processing layer, and the presentation layer. Each
layer is responsible for different tasks and it is important to ensure that
each layer is implemented correctly to ensure that the data warehouse is
secure, efficient, and easy to use.
โ By Implementing a 3 tier data warehouse architecture, businesses can
ensure that their data is stored, managed, and accessed in an organized and
secure manner. This will allow businesses to make better decisions and gain
insights from their data.
