In my previous article , I explained you about the need of Data Warehouse in today’s competitive world. I also told you the benefits of Data Warehouse. If you have not got a chance to read it yet , please go through this – Why is Data Warehouse Required ?
I know the readers here are very curious. By now you must have started thinking about what is a Data Warehouse ? What are the properties of Data Warehouse ? How we create Data Warehouse ? So my friends , all your question will be answered here.
What is a Data Warehouse ?
Data warehouse is a concept. It is a relational database or a repository of an enterprise’s data which is designed to improve query performance and analyze large amount of data for reporting purpose.
- It is a collection of corporate information, derived from operational systems and some external market data for proactive business decisions.
- It is designed for easy user access.
- It is a combination of powerful hardware and software configurations to process huge islands of information.
Definition of Data Warehouse :
Different people have different definition for a data warehouse. The most popular definition came from Bill Inmon, who provided the following:
A data warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management’s decision making process.
Properties Of Data Warehouse :
Subject Oriented –
The data warehouse world is organized around major subjects such as customer, vendor, product, and activity. The alignment around subject areas affects the design and implementation of the data found in the data warehouse.
The very essence of the data warehouse environment is that data contained within the boundaries of the warehouse is integrated. A data warehouse integrates data from multiple data sources.
The integration shows up in many different ways –
in consistent naming conventions, in consistent measurement of variables, in consistent encoding structures, in consistent physical attributes of data, and so forth.
Time Variant –
The time variancy of data warehouse data shows up in several ways.
- Data warehouse data represents data over a long time horizon.
- Every key structure in the data warehouse contains – implicitly or explicitly – an element of time, such as day, week, month, etc.
- data warehouse data, once correctly recorded, cannot be updated.
Non Volatile –
Data is loaded in Data Warehouse and accessed there. But once data is in the data warehouse, it will not change. So, historical data in a data warehouse should never be altered.
Data in Data Warehouse :
Till now we have discussed the definition of Data Warehouse and properties of data warehouse. Now we will discuss about the most important aspect of Data Warehouse. Most important thing in Data Warehouse is data.
Below are the properties of data in Data Warehouse –
- Separate DSS data base
- Storage of data only, no data is created
- Integrated and scrubbed data
- Historical data
- Read only (No recasting of history)
- Various levels of summarization
- Meta data
- Subject Oriented
- Easily Accessible
Features Of Data Warehouse :
Following are the features of Data Warehouse –
- Strategic Enterprise level decision support
- Multi dimensional view on the enterprise data
- Caters to the entire spectrum of management
- Descriptive, standard business terms
- High degree of scalability
- High analytical Capability
- Historical Data only
Application areas of Data Warehouse :
Once the data warehouse is created , we need to know what are the application area where data warehouse will be used . Following are some business application of Data Warehouse :
- Risk Management
- Financial Analysis
- Marketing Programs
- Profit trends
- Procurement Analysis
- Inventory Analysis
- Statistical Analysis
- Claims Analysis
- Manufacturing Optimization
- Customer Relationship Management
So this was a brief overview of Data Warehouse – definition, properties, features , benefits etc . Hope your understanding will become more clear about Data Warehouse after reading this article.