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A data warehouse consists of highly structured data that is collected from various sources and combined using different methods. Types of Data warehouse are the ways to implement data in a structured manner. You can also learn about what is data science, data engineering, scope and future of data engineering, data analytics, and much more.
A data warehouse is a centralised archive of old and new data, which is being collected and stored with a purpose to be used in the future.
Whereas Data Warehousing is the process of compiling and administering the collected data to help your organisation answer important business questions and gain key insights.
It is a combination of various technologies that will help you achieve your data’s efficient and strategic use.
A data warehouse architecture helps in establishing a complete data communications system. There are three important types of data warehouse architecture:
Once you know which data warehouse architecture is best suited for your organisation you can move onto building your data warehouse.
Before we discuss the different types of data warehouse understanding the different data warehouse basic concepts is an important step towards building and efficient data warehouse. There are four main basic concepts of a data warehouse that your organisation should be familiar with:
Along with the knowledge of the basic concepts of data warehouse your organisation should also have a basic understanding of how a data warehouse functions. This is where data warehouse schemas come into play.
Similar to how a database uses relational models, a data warehouse uses schemas. A schema in simple words is the logical description of the all the data sets available, such as the name and description of all data records.
There are three types of schemas in data warehouse.
There are 3 types of Data Warehousing:
An Enterprise data warehouse is a database that combines several functional areas of an organization in a unified way. It helps in storing data from various sources and categorizes them accordingly, so it is easily accessible across your organization. An enterprise data warehouse will have inbuilt procedures for extracting, converting and analyzing data.
An operational data store, also known as an Operational Decision Support system (ODS), is a database used when neither Online Transactional Processing (OLTP) nor data warehouse can satisfy your organization’s requirements. The data warehouse is refreshed in real-time, and the redundancies present are accounted for and resolved. For example, ODS is used for employee information database.
An independent data mart can gather data directly from the source. It is built for a specific field of business, such as finance, marketing, or sales.
Data marts are further classified into three categories:
A data mart is also much more cost effective compared to a full data warehouse.
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