Data warehouse|Advantage&Disadvantage|Design-Datacloudy

In this blog we are going to see about Datawarehouse , its advantages and disadvantages. Also we are going to see about Approaches to design data warehouse .This is going to be a crisp and clear blog. Datawarehouse is an important topic for Engineers who are working in Data Domain. And it is very important in the interview point of view as well. Lets get started,

Now a days, businesses are generating very large amounts of data every day. However, this data is stored in multiple systems, making it challenging to use effectively. This is where a data warehouse comes into picture.

A data warehouse is a centralized repository of data that is designed for analytical use cases. It allows organizations to integrate data from various sources and store it in a single location, which can be accessed by authorized users to gain valuable insights and make data-driven decisions. And it maintains the historical data.

Data warehouse are designed by the Extracted, Transformed and loaded data from various sources such as Traditional databases, CRM etc. This transformed data is structured and it is optimized for querying and analysis purpose.  Therefore which makes it easier for business analysts, data scientists, and other downstream users to explore and get insights from the data.

Advantages of Datawarehouse are:

    i)Improved data quality and consistency

    ii)Greater flexibility and scalability to handle increasing volume of data

    iii)Better decision making through accurate reporting and analysis

    iv)Higher data security, due to centralized management of data.

Disadvantage of Datawarehouse are:

The main disadvantage of datawarehouse is it can only handle structured data and cannot handle unstructured data.

For that reason only we are going to Data lake. And that is a separate topic. Now let us come to our topic.

When we are taking about datwarehouse we need to talk about Datamart as well. Datamart is nothing but the subset of larger data warehouse.  That is designed to serve the needs of specific business unit within the organization. To know about datamart click here. That blog will give u you brief explanation of data mart and its types. It is highly recommended topic.

Approaches to data warehouse design:

There are three main approaches to design Datawarehouse. They are,

1) Kimball Approach

2)Inmon Approach

3) Hybrid Approach

Let us see one by one in simple manner,

1)Kimball Approach:

• The Kimball approach is a bottom-up approach to data warehouse design.
  
  
• Datawarehouse is build using a dimensional data model.  
  
  
• Focused on easy to understand concept

2) Inmon Approach: 

• The Inmon approach is a top-down approach to data warehouse design.
  
  
• Data warehouse is build using  normalized data model.
  
  
• Focused on optimized data integration and consistency.

3) Hybrid Approach: 

• The hybrid approach is a combination of the Kimball and Inmon approaches. 
  
  
• Data warehouse is build using both dimensional data model and normalized data model. 
  
  
• Focused on both, easy to understand concept and optimized data integration and consistency

Thus in this blog we looked about datawarehouse, its advantages and disadvantages. Also we saw about different approaches the create datawarehouse. Hope it is a crisp and clear explanation and i feel this will be very helpful to you.

Thank you !!!