Data Warehouse

Data Warehouse (DW) stores a huge amount of data, which is typically collected from multiple heterogeneous data sources such as CSV, txt,xls files, and various databases such as Oracle, Microsoft SQL, etc.It is diffrent from DBMS.DBMS is a Database Management System (DBMS) that stores data in different tables based on ER Model and ACID properties.
It helps in generating meaningful insights for the respective business, which is used for decision-making.

Data Warehouse

 

Why Data Warehouse

The ordinary database doesn’t offer the analytical data required for understanding business growth. The organization keeps a central Data Warehouse to study its business by understanding, organizing, and using its historical data for taking strategic decisions and analyzing the trend of business. The Data Warehouse environment contains an extract, transform, and load (ETL) solution.

Features

Integrated:
It integrates various data sources like RDBMS, flat files (txt,xls,csv), and online transaction records. It requires performing data cleansing and integration during data warehousing to ensure data consistency shared data and data warehouse data against different data sources.

Subject Oriented:
It focuses on data modeling and analysis for decision-makers. The data warehouses provide a view of particular subjects, such as retail, banking, health, HR, etc.

Non Volatile:
The updates of data don’t occur in the data warehouse, which means data insert, update, and delete operations are not performed. It usually requires data loading and transaction processing Non-Volatile defines that once data is loaded into the warehouse, It should not change.

Time-Variant:

Historical data is kept in a data warehouse. For example, we can retrieve files from 1 month, 3 months, 12 months, or given regular intervals. All these files are kept for a specified duration.

Data Mining:
Data warehousing provides data mining capabilities, which allows the organization to identify hidden patterns and relationships in their data. This helps to new opportunities, define trends, and mitigate risk.
Data Security:
It provides data security features, such as data encryption, data backups, and access controls, which ensure data security and protection from unauthorized access.

Advantages

  1. helps to understand business trends and make better decisions.
  2. It is designed to store enormous amounts of data
  3. We can store normalized or denormalized data.
  4. It helps to reduce data redundancy and inconsistencies.
  5. We can scalable data warehouse and can handle huge amounts of data from different sources.

Disadvantages

  1. Implementing a DW can be expensive, it requires investment in hardware, software, and resources.
  2. The DW designing is complex it will take time and businesses should have significant time as well as patience.

The data warehouses can be used in many applications in different sectors like E-Commerce, Marketing and Distribution, telecommunications, Transportation Services, Healthcare, and Retail, Banking, Finance.

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