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Data warehouse
Introduction
system that pulls together data from many different sources within an organization for reporting and analysis. The reports created
from complex queries within a data warehouse are used to make business decisions.
warehouses Vs databases
Data warehouses Vs databases
are both relational data systems, but were built to serve different purposes.
Typical Functionality of a Data Warehouse
Functions
- Data warehouses exist to facilitate complex, data-intensive, and frequent ad hoc queries.
- Data warehouses must provide greater and more efficient query support than transactional databases.
- The data warehouse access component supports enhanced spreadsheet functionality, efficient query processing, structured queries, ad hoc queries, data mining and materialized views.
preprogrammed functionalities
- Enhanced spreadsheet functionality includes support for spreadsheet applications like MS Excel & OLAP applications programs.
These offer preprogrammed functionalities such as the following:
- Roll-up:Data is summarized with increasing generalization.
- Drill-down: Increasing levels of detail are revealed.
- Pivot: Cross tabulation is performed.
- Slice and dice: Projection operations are performed on the dimensions.
- Sorting: Data is sorted by ordinal value.
- Selection: Data is available by value or range.
- Derived attributes: Attributes are computed by operations on stored and derived values.
efficiency
Data warehouses has an increased efficiency in query processing. Among the tools and techniques used are:
- Query transformation.
- Index intersection and union.
- Special ROLAP (relational OLAP) and MOLAP (multidimensional OLAP)functions.
- SQL extensions.
- Advanced join methods.
- Intelligent scanning.
What is Building Data Warehouse?
Building
-Data Warehouse is nothing but relational database management system which is used for Querying the data for the purpose to do some analysis and to take some managerial decisions.
-The definition for Data Warehouse (DWH) is collecting/Integrating data from different sources and converting that data into Information format.
Problem
Problems in Building a Data Warehouse?
- Maintenance costs outweigh the benefits
- Hidden problems of the Source
- Increased demands of the users
Critical Success Factors ?
- time saving .
- Enterprise Information Architecture.
- Information Quality.
Data
Modeling
Data Modeling
-Dimensional modeling is preferred technique for presenting analytic data because it addresses two simultaneous requirements:
- Deliver data that’s understandable to the business users
- Deliver fast query performance
-The dimensional storage model involves two types of tables dimension tables and fact tables.
-common dimensional schema are the star schema
fact tables:
The fact table in a dimensional model stores the performance measurements result- ing from an organization’s business process events.Because measurement data is overwhelmingly the largest set of data
dimension tables:
have many columns or attributes
Each dimension is defined by a single primary key
CONTACT US
CONTACT US
Characteristic
FEATURES
What about the nature of the data in the data warehouse ?
1 - Subject-Oriented Data
2 - Integrated Data
3 - Nonvolatile Data
4 - Time-Variant Data