Data Warehouses
When we talk about data in the modern businesses, Data Warehouses are one of the most important things. We need to store data with mainly two purposes.
1. Operational Record Keeping
2. Analytical Decision Making
There we need data warehouses for Analytical decision making. In this article it will briefly discuss about what is a data warehouse, its advantages, cloud-based data warehouses and many more things.
What is a Data Warehouse?
In simple words, it is a kind of data management system which will help to business intelligence activities specially in analytics.
From Wikipedia:
In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis, and is considered a core component of business intelligence. DWs are central repositories of integrated data from one or more disparate sources. They store current and historical data in one single place that are used for creating analytical reports for workers throughout the enterprise.
Characteristics of Data Warehouses
· Subject-Oriented
Data warehouses gives the information or analyze the data related to a particular subject. It may be marketing, sales, payments etc.
· Integrated
A data warehouse is developed integrating data from different sources. It needs to create consistency for those different data types.
· Non-volatile
Once the data is entered to the data warehouse it is stable. They will not delete when new data is entered.
· Time-Variant
Once the data is inserted to the data warehouse, it cannot be updated or changed. Data warehouse analysis looks at change over time.
Why need Data Warehouses?
· Analyze data from different sources.
· Separated analytical from transactional data.
· Improve the query performance.
· Original data source might not be able to query.
· Foundation for data mining, data visualization, advanced reporting and OLAP tools.
OLTP (Online Transaction Processing) is used with the primary objective of data processing, while OLAP (Online Analytical Processing) or else we can say Data warehouses are used with the primary objective of data analysis. So, I think it is important have a small comparison of OLTP and OLAP (Data Warehouses). The below diagram is a comparison of that.
Main components of Data Warehouse
· Data Warehouse Database
· Sourcing, Acquisition, Cleanup and Transformation Tools
· Meta data
· Access Tools
· Data Warehouse Administration and Management
· Information Delivery System
Data Warehouse Architectures
This is depending on the organization’s need and its other situations. However, we can find three common architectures of data warehouses.
- Basic Architecture
2.With Staging Area
3. With Staging Area and Data Marts
Cloud Data Warehouse
On premises data warehouses might offer more security, improved governance, and speed. However, in most cases they are not easy to scale for the future needs and managing the data warehouses is a complex task. So, cloud data warehouses come to the scene. Following are some advantages of cloud data warehouses.
· Elasticity, with separate compute and storage
· Scale-out abilities, to handle compute or storage requirements.
· Ease of use
· Ease of management
· Cost savings
This is a brief introduction about data warehouses. In a next article I hope to discuss about Azure Data Warehouses. Hope you have gain something from this article
