What is a data warehouse?

A data warehouse stores large quantities of structured data from multiple data sources and transactional systems such as CRMs and ERPs.

Think of a data warehouse like an actual warehouse. You can walk down the aisle, go through various sections and look for specific shelves.

Before storage, raw data undergoes the ETL (Extract Transform Load) process for further analysis and reporting.

Data warehouses can be on-premise or on the cloud.

​IBM, Oracle and Teradata offer on-premise data warehousing solutions. Amazon Redshift, Google BigQuery and Microsoft Azure SQL Data Warehouse are some of the popular cloud data warehousing solutions available.

How is it different from the other types of data repositories?

Here's an analogy illustrating the difference between various data repositories such as data lakes, data warehouses and data marts.

The difference between various data repositories. Image courtesy: SQL Hammer

Curious to know more about how data lakes and data warehouses are different from each other? We've got you covered! Read more about it here.

Why should you store data in a data warehouse?

The data stored in a warehouse serves a specific purpose, which is defined before the data engineers begin modeling data and loading it into the warehouse.

After that, raw data is transformed (see ETL) and stored in query-able forms, which is essential for data analysis and reporting.

Since the data present in the data warehouses is cleaned and processed before storage, the data quality and integrity in data warehouses is guaranteed.

It also saves storage space by maintaining only the data required for a specific purpose and gets rid of data considered to be useless.

Data warehouses store data in standardized formats, which makes the data easy to understand and interpret. Even business users without in-depth expertise in data science and analysis can use data from the warehouses for decision-making.

What are the challenges posed by a data warehouse?

Since the data warehouses only store structured and processed data, unstructured data from data sources such as emails, texts, videos, audio recordings, sensor data and surveillance data cannot be directly stored in data warehouses.

Data warehouses are also more expensive (if you wish to scale your storage space quickly). Once the data is stored, it’s complicated and tedious to change, modify or reconfigure it.

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