Types and Applications of Data Warehouse-Explanation of Types and Applications of Data Warehouse

Types and Applications of Data Warehouse-

Here we discuss the brief information about applications of data warehouse and the types of data warehouse.

Types of Data Warehouse-

1.Information Processing-

In data warehouse lots of data saved. The data can be processed by means data analysis about statistical analysis, report, chart and graph.

2.Analytical Processing- 

In Analytical Processing data can be analyzed with basic OLAP operations. In that operation include-

1.Slice and Dice Operation

2.Drill Down

3.Drill Up

4.Pivoting

3.Data mining-

The data mining is important factor for analysis data from data warehouse . If data extract from data mining tool then data mining algorithms apply on that with user requirement. The result show in the form of patterns and that all patterns show to user with GUI tools mainly.

Applications of Data Warehouse-

Data warehouse basically used to business organizers for maintain historical data. the data warehouse used in

1.Banking industry

2.Financial Services

3.IT Sectors

4.Retail Sector

5.Manufacturing Sector

Explanation :

A data warehouse is a centralized repository that stores large volumes of structured data from multiple sources to support decision-making, reporting, and analysis. It helps organizations transform raw data into valuable business insights. Data warehouses are classified into several types based on their architecture, purpose, and data management approach. The main types include Enterprise Data Warehouse (EDW), Operational Data Store (ODS), and Data Mart. Each type serves specific business needs and analytical goals.

1. Enterprise Data Warehouse (EDW):

An EDW is a large-scale, centralized warehouse that integrates data from across the entire organization. It provides a unified and consistent view of all business operations. EDWs are used for enterprise-wide analytics, strategic decision-making, and long-term data storage. They enable complex queries and data mining across multiple business domains, such as finance, marketing, and operations.

2. Operational Data Store (ODS):

The ODS is a type of data warehouse that stores current or near-real-time transactional data. Unlike an EDW, it is frequently updated and used for operational reporting rather than long-term analysis. ODS serves as an intermediary between operational systems and the data warehouse, ensuring that decision-makers have access to the most recent data. It is commonly used for short-term decisions, monitoring, and real-time analysis.

3. Data Mart:

A data mart is a smaller, subject-oriented version of a data warehouse designed for a specific department or business function, such as sales, human resources, or finance. Data marts improve performance by providing focused, user-friendly access to relevant data. They can be dependent (sourced from an EDW) or independent (built directly from operational systems).

Applications of Data Warehouses:

Data warehouses are used extensively across industries. In business, they support performance analysis, sales forecasting, and market segmentation. In healthcare, they assist in patient record analysis and treatment optimization. Banks and financial institutions use them for fraud detection, risk management, and customer analysis. In education, data warehouses help track student performance and institutional growth.

Read More-

1. What Is Data Warehouse
2. Applications of Data Warehouse, Types Of Data Warehouse
3. Architecture of Data Warehousing
4. Difference Between OLTP And OLAP
5. Python Notes