The boost in the tech world opens multiple gateways to advancements on various levels. Data science has become an eminent topic in recent times, as it makes things in the IT sector easier. Organizations are switching to more trusted and handy ways when it comes to data storage. Data warehouses are a fundamental element of market intelligence that aid businesses in catering to their performance and growth systematically. Let’s delve deep into the concept of what is data warehouse and its functionality.

What is a Data Warehouse?

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The word ‘warehouse’ suggests storage. A data warehouse is the principal vault/repository to store large amounts of data for analysis and improve the outcome of the business. In an enterprise, all sorts of data, like customer data, financial data, etc., are in abundance and stored in a data warehouse. It’s the main repository that helps maintain a track record since it’s got all the data safe with it, be it from the past or current. Apart from preservation, it aids in comparison and strategy formation as a result of data mining.


A data warehouse pulls out data from numerous applications in a timely manner and stores it all in one place. Transactional systems tabular or structural databases and other sources provide data into the data warehouse regularly.

Types of Data Warehouse

There are three different types of Data Warehouses. Let’s see below how the different types work and the difference between them.

Operational Data Store (ODS):

This central database is mainly concerned with real-time operational reporting. Here the recording of routine tasks occurs and storage is like employee records since it refreshes in real time.

Enterprise Data Warehouse (EDW):

A Business/Employee data warehouse plays a key role in facilitating decision support services throughout the organization. Numerous databases club together to form an EDW. Through this, one can access inter-organizational information. Besides, it represents the data uniquely, allowing it to run complex queries.

Data Mart:

The sub-set of data warehouses, this kind is architectured for catering to a specific type of business/section. Each unit of business has a dedicated repository or data mart for storage purposes. With this, one won’t have to scroll through all the records and can easily get to the required information. This stores data periodically.

Characteristics of Data Warehouse

After knowing about the data warehouse and its three types, let’s throw light on its key characteristics. Listing below a few of them. 

  • Subject Centered:

Data warehousing is a topic-oriented system as it provides information about a particular topic and not the whole functioning of the organization at a time. The subjects like customer, sales, marketing, finances, assets, etc, Say, if you were to perform analysis on finances, a separate database is created for that. Hence, it becomes easier to track. One doesn’t have to go through a whole storage, instead can look for the concerned topic. Hence, it is subject-oriented.

  • Unified:

Similar to subject orientation, it focuses on integrating data from various sources and clubbing into a unique format. Collecting and storing similar data from different platforms and storing it in a single place justifies this characteristic of the data warehouse. It helps in better analysis of data.

  • Non Volatile:

This means that once that data is stored in a data warehouse, it can only be read but not amended. Besides, there can’t be any modifications taking place after the storage is done. The data can only be refreshed periodically.

  • Time Variant:

Through this, the data is maintained in the various time intervals. The data warehouse has a wider time range than in operational systems. Once data stored here, no modification takes place. The data is always documented with an element of time.

How does Data Warehouse work?

I’m sure it’s clear by now what a data warehouse is. Let’s further dig in on how a data warehouse works. 

The gathering of data and information from multiple sources and putting it under a unified comprehensive database is what comes under data warehousing. The data storage occurs in various layers decided by the type of data and its layout. One may even store confidential data related to the business in the vault, like salaries, workmen details, profit, sales, etc. 

The architecture of Data Warehousing comprises three tiers:

  1. Bottom tier: Here, the data is filled in and stored for further processing.
  2. Middle tier: Here, data analysis takes place to sort the relevant data in respective tables.
  3. Top Tier: This is the one where the result is displayed after data mining, and other analyses are performed with the help of certain data warehousing tools.

Tools for Data Warehousing

The tools for data warehousing play an important role in the procedure. There are several cloud-based warehousing tools available out there. One may decide on the tool as per the respective project.

Naming a few tools:

  • Amazon Redlift
  • Microsoft Azure
  • Amazon DynamoDB
  • Amazon S3
  • PostgreSQL
  • Teradata
  • IBM Db2 Warehouse
  • MariaDB
  • MarkLogic
  • Oracle Autonomous Warehouse

Benefits and Drawbacks

Now that we’re aware of the concept and functioning of data warehousing, find below certain advantages and disadvantages of the repository system.

  • Advantages:
  1. Refined and better results.
  2. Enriched documentation of data.
  3. Improved business analysis and performance track records.
  4. Easy reaching out for the necessary data without any wastage of time.
  5. Less interference
  • Disadvantages:
  1. It’s a hefty investment when it comes to its setup and management.
  2. It is not flexible as no changes can be made whatsoever once the data storage takes place.
  3. The advancements happening in the sector may soon become obsolete.

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The IT industry is certainly taking over, and one should be aware of the advancements that are happening. The article intends to answer the question of what a data warehouse is and its mechanism. I hope the readers get clarity on the topic. Nonetheless, the field of data science is vast, with never-ending technicalities and advancements. One must keep updated as per the latest trends and market requirements.

Frequently Asked Questions

Q1. What is a data warehouse?

Ans. The storage place for abundant data, systematically and consistently, is called a data warehouse. For a detailed answer, you may refer to the article above.

Q2. What are Data Warehouse tools?

Ans. The tools that aid in the data storage procedure in the repository vault are known as the data warehouse tools.

Q3. How does data flow into a data warehouse?

Ans. Here, the data flows inside the warehouse through a chain of business systems, relational databases, and other systems. The data analysis happens before storage.

Q4. What career opportunities would exist if I knew about data science?

Ans. The growing industry provides a plethora of opportunities for people looking to form a career in the Data mining industry. One may become a business analyst, a data warehouse expert, a data analyst, a data engineer, etc.

Q.5 What educational qualifications should one have to become a data warehouse expert?

One may do a diploma program a bachelor’s degree in technology or a bachelor’s degree in computer science as a major from a recognized university.

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