Introduction
A data warehouse is a collection of data marts representing historical data from different operations in the company.
It collects the data from multiple heterogeneous database files (flat, text etc.)
This data is stored in a structure optimized for querying and data analysis as a data warehouse.
A warehouse is a subject oriented, integrated, time variant and non-volatile collection of data in support of management's decision-making process.
Subject oriented :- data that gives information about a particular subject instead of about a company's ongoing operations.
Integrated:- data that is gathered into the data warehouse from a variety of sources and merged into a coherent whole.
Time variant:- All data in the data warehouse is identified with a particular time period.
Non-volatile:- data is stable in a data warehouse. More data is added, but data is never removed.
It can be :-
Used for decision support
Used to manage and control business
Used by managers and end-users to understand the business and make judgements
Enterprise data warehouse:-
It collects all information about subjects (customers, products, sales, assets, personnel) that span the entire organization.
Decision support system (DSS) :- Information technology to help the knowledge 📚 worker 👷 (executive, manager, and analyst) makes faster & better decisions.
Operational and informational data:-
Operational data:-
* focusing on transactional function such as bank card withdrawals and deposits.
* detailed
* updatable
* reflects current data
Informational data:-
* focusing on providing answers to problems posed by decision makers
* summarized
* non-updatable
Data warehouse characteristics
* it is database designed for analytical tasks
* its content is periodically updated
* it contains current and historical data to provide historical perspective of information.
Overall architecture
* the data warehouse architecture is based on the database management system server.
* the central information repository is surrounded by a number of key components
* management system that functions as the central repository for informational data.
* the transformation process involves conversion, summarization, filtering, and condensation.
* the data warehouse must be capable of holding and managing large volumes of data, as well as different structure of data structures over the time.
Key Components:-
* data sourcing, cleanup, transformation, and data migration tools.
* metadata repository
* warehouse / database technology
* data marts
* data query, reporting, analysis, and mining tools.
* data warehouse administration and management
* information delivery system.
1.1.1. Data sourcing, cleanup, transformation, and migration tools
* they perform conversions, summarization, key changes, structural changes.
* the data transformation is required to use by decision support.
* it moves the data into data warehouse from multiple operational systems. Functionalities of these tools are listed below:
- to remove unwanted data from operational db
- converting to common data names and attributes
- calculating summaries and derived data.
1.1.2 Metadata repository
It is data about data. It is used for maintaining, managing, and using the data warehouse. It is classified into two:-
Technical metadata:- it contains information about data warehouse data used by warehouse designer, administrator to carry out development and management tasks. It includes:
- info about data stores.
- transformation descriptions. That is mapping method from operational db to warehouse db.
- warehouse object and data structure definitions for target data
- the rules used to perform clean up, and data enhancement
- data mapping operations
- access authorization, backup history, info delivery history, data acquisition history, data access etc.
Business metadata:- it contains info that gives info stored in data warehouse to users. It includes,
- subject areas, and info object type including queries, reports, images 🖼, videos 🎥, audio 🔊 clips etc.
- internet home pages
- info related to info delivery system.
- data warehouse operational info such as ownership, audits trails etc.
Metadata helps the users to understand content and find the data. Metadata stores which is known as informational directory or metadata repository which helps to integrate, maintain, and view, the contents of the data warehouse. The following lists the characteristics of info directory / metadata:
- it is the gateway to the data warehouse environment
- it supports easy distribution and replication of content for high performance and availability
- it should be searchable by business oriented keywords.
- it should act as launch platform for end user to access data and analysis tools.
- it should support the sharing of info
- it should support scheduling options for request
- it should support and provide interface to other applications
- it should support end users monitoring of the status of the data warehouse environment.
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