TIỂU LUẬN MÔN CƠ SƠ DỮ LIỆU BUILDING SMALL DATA WAREHOUSE

What is Data Warehouse? Introdution about data warehouse..  “A data warehouse is a subject-oriented, integrated, time-variant, and nonvolatile collection of data in support of manageme

BUILDING SMALL DATA WAREHOUSE

Giảng viên hướng dẫn: Nguyễn Hà Nam Sinh viên thực hiện: Nguyễn Đức Bình.

Phùng Thị Hương.

 What is Data Warehouse

 Dimensional Modeling

 Data Warehouse Architecture

 Building Data Warehouse for Puncia

What is Data Warehouse?

 Introdution about data warehouse

 “A data warehouse is a subject-oriented,

integrated, time-variant, and nonvolatile collection

of data in support of management’s

decision-making process.”—W H Inmon

What is Data Warehouse?

Data Warehouse—Subject Oriented

 Data is organized in major objects or business processes

 Example of subject oriented data are customer, product, vendor and sale transaction

Data Warehouse—Integrated

Data Warehouse — time variant

Data Warehouse — nonvolatile

Dimensional Modeling

 Is a database design technique to support

business users to query data in data warehouse

 There are two important concepts: facts and

dimensions

 The dimensional data model is built based on

star schema

Conceptual Modeling of Data Warehouses

 Star schema: A fact table in the middle connected to a set of dimension tables

 Snowflake schema: A refinement of star schema where some dimensional

hierarchy is normalized into a set of smaller dimension tables, forming a shape similar to snowflake

 Fact constellations: Multiple fact tables share dimension tables, viewed as a

collection of stars, therefore called galaxy schema or fact constellation

Example of Star Schema

Example of Snowflake schema

Example of Fact constellations

Popular Data Warehouse Architectures

 Enterprise data warehouse architecture

 Dimensional data warehouse architecture

 Federated data warehouse architecture

 Data Mart

Enterprise data warehouse architecture

Dimensional data warehouse architecture

Kimball vs Inmon

 Bill Inmon recommends to build data

warehouse that follows top down approach In Inmon’s philosophy, it is starting with building a big centralized enterprise data warehouse.

 Ralph Kimball recommends to build data warehouse that follows bottom up

approach It is first start with mission critical data marts that serve analytic needs of departments Then it is

integrating these data marts for data consistency through a so called

information bus

Kimball vs Inmon

Data Warehouse For Punica

 Introduction Punica Company and Punica’s OLTP

 Reporting requirements punica

 Building Data warehouse with windows 7, SQL server 2008

Introduction Punica

 Is company domain name owner punica.vn

 Provide services broker, customer through 03 site

Interface for broker site

Interface for customer site

Reporting requirements punica

 The number of postings each week, month,

quarter With group user, location, demand & type for real estate

 Average Price for real estate with time, location, type for real estate

Punica – Subject Area

Choose architecture approach for building

Dimensional Modeling

 Dim_time: Dữ liệu được chiết xuất từ bảng Node

và sử dụng các hàm biến đổi thời gian

 Fact_tinbds: được tổng hợp từ dữ liệu các bảng Dim_user, Dim_loaitin, Dim_location, Dim_time

Dữ liệu sau khi lấy ra sẽ được tổng hợp bằng các hàm tính toán và đẩy vào kho dữ liệu

Thanks you!