Dr. Panjabrao Deshmukh Polytechnic, Amravati

Presented By :Ku. Devyani B.Vaidya

Guided By :Prof. R.H.Rathod

Seminar On Data warehousing

and OLAP Technology

•The data can be stored in many different types of databases. One data base architecture that has recently emerged is the “data warehouse”, a repository of multiple heterogeneous data sources. Data warehouse technology includes data cleansing, data integration and online Analytical processing

•OLAP stands for analysis techniques with functionalities such as summarization, consolidation and aggregation, as well as the ability to view information from different angles.

INTRODUCTION

DATA WAREHOUSE

•A data warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management’s decision making process. So, data warehouse can be said to be a semantically consistent data store that serves as a physical implementation of a decision support data model and stores the information on which an enterprise needs to make strategic decisions.

DATA WAREHOUSE ARCHITECHTURE

Data warehouse models

•Enterprise warehouse

•Data mart

•Virtual warehouse

•Present the organization's information consistently.

•Provide a single common data model for all data of interest regardless of the data's source.

•Restructure the data so that it makes sense to the business users.

BENEFITS OF DATA WAREHOUSING

What is OLAP??

•OLAP (online analytical processing) is computer processing that enables a user to easily and selectively extract and view data from different points of view.

•OLAP allows users to analyze database information from multiple database systems at one time.

•OLAP data is stored in multidimensional databases.

•The term OLAP was created as a slight modification of the traditional database term OLTP (Online Transaction Processing).•Databases configured for OLAP employ a multidimensional data model, allowing for complex analytical and ad‐hoc queries with a rapid execution time. •They borrow aspects of navigational databases and hierarchical databases that are speedier than their relational kind.

HISTORY OF OLAP

•An OLAP Cube is a data structure that allows fast analysis of data.•The arrangement of data into cubes overcomes a limitation of relational databases.•It consists of numeric facts called measures which are categorized by dimensions.•The OLAP cube consists of numeric facts called measures which are categorized by dimensions.

THE OLAP CUBE

•A multidimensional cube can combine data from disparate data sources and store the information in a fashion that is logical for business users.

OLAP CUBE

• Slice• Dice• Drill Down/Up• Roll‐up• Pivot

OLAP OPERATIONS

Features of OLAP

1. Multidimensional views of data

2. Calculation-intensive capabilities

3. Time Intelligence

ConclusionOLAP applications are found in the area of financial modeling (budgeting, planning), sales forecasting, customer and product profitability, exception reporting, resource allocation, variance analysis, promotion planning, and market share analysis

•A data warehouse is a subject-oriented, integrated, time-variant and non volatile collection of data in support of management’s decision making process. Data warehousing is the process of constructing and using data warehouses. Data warehousing is very useful from the point of view of heterogeneous database integration.