Data warehouse: Concepts, model, Features of data warehouse

In today's highly competitive business environment, companies are turning to cloud-based solutions for effective data collection, reporting, and analysis. Data warehousing plays a key role in business intelligence in order to help the organization improve its performance. Understanding what a data warehouse is and how it is changing in the industry today is important.

What is Data Warehousing

A data warehouse is a type of data management system that organizes current and historical data from various sources for better reporting and insights. Data warehouses are extensively used for reporting, data processing, and business intelligence (BI). Business data that is transferred from operational systems, such as point-of-sale systems, supply chain management systems, and marketing and sales databases, can be quickly analyzed using data warehouses. Data may transit through operational data storage before being used in the data warehouse for reporting, and it must be cleaned to ensure data quality.

Purpose of Data Warehouse                            

Data warehouses are used in business analytics, reporting, and data analytics to collect and organize data from database applications. If getting the information directly from transactional databases is difficult, we can obtain it through a data warehouse. For example, if management wants to understand the total monthly revenues produced by each salesperson for each product category, although transactional databases might not do so, the data warehouse does.

Database vs Data Warehouse

There are some similarities between a data warehouse and a traditional database. The major difference is that information is gathered for numerous transactional purposes in databases. In a data warehouse, to do analytics, data is gathered on a large scale. Data warehouses store data to be used for large analytical queries; databases provide real-time data.

Types of Data Warehouse

There are three primary categories of data warehouses (DWH):

Enterprise Data Warehouse (EDW):

The Enterprise Data Warehouse (EDW) is a centralized warehouse. It provides services for enterprise-wide decision support. It provides a standardized methodology for compiling and presenting the data. Moreover, it provides the capability of categorizing subject-based data and provides access in accordance with such divisions.

Operational Data Store:

The Operational Data Store, which is also called ODS, is required when data warehouse systems do not support the reporting needs of the business. In the Operational Data Store, the data warehouse is refreshed in real-time. It is, therefore, widely used for everyday tasks like maintaining employee records.

Data Mart:

A data mart is a subset of the data warehouse. It is designed specifically for a business, like sales, finance, or banking. Data is collected directly from the sources and stored in the data mart separately.

Benefits of data warehouses

• Consolidate data gathered from various sources; serve as a central hub for all data, preventing users from having to connect to dozens or even hundreds of individual data sources. 
• Historical intelligence; Data from many sources is combined in a data warehouse to demonstrate historical trends.
• Separate the analytics process from transactional databases to boost both systems' performance.
• Provides data quality, reliability, and accuracy. Data warehouses use a standard set of semantics around data and consistently employ naming conventions, and codes for different product categories, languages, currencies, and so on.

Examples of data warehousing in various sectors 

Below are a few examples of how many businesses use data warehousing to carry out their regular operations:

Investment and Insurance: 

Data collection is crucial in the insurance sector since it enables the business to generate more leads that will help them acquire more clients. Data warehousing is employed in this industry to examine/analyze customer, market, and other data patterns. To build a composite view of each customer, client information from various business lines can be integrated into a data warehouse.

Healthcare: 

A data warehouse is used to forecast treatment outcomes, generate reports, and transmit the data to different units. It functions as a central repository for all medical data gathered from many resources, including radiography and laboratory databases, business resource planning systems, digital health records, and electronic medical records.

Retail chain:

Data warehouses are frequently utilized in retail chains for marketing and distribution. By processing and integrating data from many internal and external sources, it provides retailers with a centralized source of information. Additionally, it supports keeping track of products, consumer buying patterns, promotions, and price structures. 

Telecommunication:

In the telecommunications sector, a data warehouse is an effective resource for managing huge amounts of information. It helps telecommunications firms get a competitive edge and generate more revenue. In this field, distribution decisions, sales decisions, and product marketing decisions are all made using a data warehouse.

Discover the power of the data warehouse.

Every organization should have access to a proper data integration platform in a data-driven business environment.  An organization suffers a great loss when vast amounts of generated data fail to be sustained in a market. Data warehousing can help with this. It not only saves time and has a high return on investment, but also enhances the consistency and quality of data. Additionally, it provides better business analytics and enables firms to predict outcomes confidently.