Data warehousing, also known as enterprise data warehousing, is an e-method of shaping, analyzing, and reporting data that are collected periodically having similar in nature. The ability to integrate multiple sources of data is critical in modern companies to make better-informed decisions. Data warehousing, for example, enables data mining, which aids firms in identifying data patterns that might lead to increased sales and profitability.
A data warehouse is a collection of databases that aggregates data from various sources. Data that are retrieved from separate sources are checked and outliers and unnecessary data are deleted to make structured into a query-able format for the processing.
Different Tools for Data Warehouse:
Google BigQuery
Amazon Redshift
Snowflake
Microsoft Azure
Teradata
Amazon DynamoDB
Main Benefits of Data Warehouse:
Product development, marketing, pricing strategy, manufacturing time, historical analysis, forecasting, and customer happiness can all benefit from data warehouses.
Types of Data Warehouse:
Enterprise Data Warehouse (EDW): This type of warehouse is for decision support services(DSS). Basically in this type of warehouse data are collected unified way and separated the data according to the specific subject
Operational Data Store (ODS): A central database used for operational reporting is known as an operational data store (ODS). Operational reporting, controls, and decision-making are all done with an ODS. Because an ODS is updated in real-time, it is ideal for routine tasks like keeping the organization’s employee details.
Data Mart: This type of data warehouse is known to be a subset of a data warehouse that is typically concentrated on a specific group or particular business nature, such as finance or account. It is specific domain-based, allowing a defined group of users to access certain data more rapidly and gain key insights.
Basic Difference Between Data Warehouse and Data Mining
Data Warehouse stored periodically in which makes the easy reporting with the process of mining and keeping data. Technically this is managed and processed by the engineers and IT skilled personnel. In data warehouse data are processed and extracted with the same nature together. Data Mining analyzed data regularly. This is used to find the pattern from the given data. This is basically used by marketing, top-level management, and business users in close coordination with engineers. In data mining data are processed, extracted, and analyzed from a large volume of data sets.