Chapter 1 : INTRODUCTION

CHAPTER 1 

Introduction of Data-ware house

 

(i) Definition of Data-ware house

(ii) Characteristics of Data-ware house

(iii) Data-ware house Usage

(iv) DBMS vs Data-ware house

 

 

(i) DEFINITION OF DATA WAREHOUSE

"Data-warehouse is a digital storage system that connects large amount of data from many digital sources."

• It stores current and historical data in one place and act as single source of an organization.
• Its goal is produced statistical result that may help in decision making.

Description of Diagram: - 

1. Data source: - 

• It collects the data from various sources/locations.

                 ロ                      ロ                            ロ                    ロ

              shop1          organization              city 1                shop2   

2. Dataware house: - 

• It stores all the data from data sources.
• It stores data in form of subjects.
• It removes inconsistencies from data.
• Analyse the whole data (past, present, future). 
• Generate report of data.

 (ii) CHARACTERISTICS OF DATAWARE HOUSE

          1. SUBJECT-ORIENTED

          2. INTEGRATED

          3. TIME- VARIENT 

          4. NON-VOLATILE

1. SUBJECT-ORIENTED: - 

• Data is stored by subjects, not by application.
• It provides straightforward view around particular subject.

2. INTEGRATED: -

• Main purpose is removing inconsistencies.
• It comes from several operational system.

      Several operational systems: - 

                       1. remove inconsistencies: - (i) naming

                                                                            (ii) codes 

                                                                            (iii) data attributes

                                                                            (iv) measurement

                         2.Transformation

                         3. Integration of source data

EXAMPLE: -      

3. TIME-VARIENT DATA: -

• It stores historical data in data warehouse.
• With the help of past data, we can enable to take decision for future.
• It contains the time element. 

EXAMPLE: - 

4. NON-VOLATILE DATA: -

• Data is not updated/delete from data warehouse.
• Used for queries & analysis of data.
• Stored in read-only format.

5. SUMMARIZED: -

• In decision- usable format.
• enable to take strong decision for future.

(iii) DATAWARE HOUSE USAGE

Three kind of data warehouse applications: 

1. Information Processing: - 

• Support querying basic statistical analysis & reporting using crosstabs, tables, charts & graphs.

2. Analytical Processing: - 

• Multi-dimensional analysis of data warehouse data.
• Support basic OLAP operations, slice-dice, drilling, pivoting.

3. Data Mining: - 

• Knowledge discovery from hidden patterns.
• supports association, constructing analysis model, represent mining result using visualization tools.

(iv) DIFFERENCE B/W DBMS AND DATAWARE HOUSE

LOGICALLY DIFFERENCE: - 

CHAPTER 2 

https://datawarehousestudywithchanda1179.blogspot.com/2023/01/chapter-2-developing-data-warehouse.html

CHAPTER 3