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By- By- Ms.Vishakha Agarwal Ms.Vishakha Agarwal (B-tech 3 (B-tech 3 rd rd yr , CSE) yr , CSE) Roll no:1035210106 Roll no:1035210106

Data Mining and WareHousing

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Page 1: Data Mining and WareHousing

By-By-

Ms.Vishakha AgarwalMs.Vishakha Agarwal

(B-tech 3(B-tech 3rdrd yr , CSE) yr , CSE)

Roll no:1035210106Roll no:1035210106

Page 2: Data Mining and WareHousing

Data Warehousing and its need. Data Warehouse DBMS Vs. Data Warehouses Architecture Data Warehouse Components Data Warehouse -data characteristics Data Warehousing tools Advantages Disadvantages

We will discuss We will discuss about… about…

Page 3: Data Mining and WareHousing

Definition :- It is a technology that allows us to gather , store & present data in a form suitable for human exploration.

Need:- It was needed by big organizations for data analysis.

Data Warehousing and its Data Warehousing and its needneed

Page 4: Data Mining and WareHousing

It is a –

Subject-oriented Integrated Time-variant Non-volatile collection of data to support decision-making

process of an enterprise. It is a multi-dimensional model.

Data WarehouseData Warehouse

Page 5: Data Mining and WareHousing

DBMS Vs. Data DBMS Vs. Data WarehousesWarehouses

DBMS Focuses on present.

Use of atomic data. Each transaction

accesses only small amount of data.

Supports day-to-day operations.

Changing ,incomplete data.

Data Warehouse

Focuses on past , present and future.

Use of aggregate data. Most analysis targets

large amounts of data. Supports information

analysis. Static ,historic data.

Page 6: Data Mining and WareHousing

ArchitectureArchitecture

Page 7: Data Mining and WareHousing

There are four characteristics of data in data warehouses.

Subject-oriented Data

Integrated Data

Time-variant Data

Non-volatile Data

Granular Data

Data Warehouse-Data Data Warehouse-Data characteristicscharacteristics

Page 8: Data Mining and WareHousing

Extract transform load tools(ETL)

Data Warehousing Data Warehousing toolstools

Data cleaning

Page 9: Data Mining and WareHousing

Integration tool

Quality-management tool

Query tool

Reporting tool

Other tools…Other tools…

Page 10: Data Mining and WareHousing

Very large storage. Enhances end-user access to a wide variety of

data. Potentially lower computing costs and

increased productivity. Providing a place to combine related data from

separate sources. Security: data and access. Query processing: multiple options.

AdvantagesAdvantages

Page 11: Data Mining and WareHousing

It is a costly method.

Data warehouses can get outdated relatively

quickly.

Lack of flexibility.

Data warehouses are not the optimal environment

for unstructured data.

Difficult to accommodate changes in data types and

ranges, data source schema, indexes and queries.

DisadvantagesDisadvantages

Page 12: Data Mining and WareHousing