The data warehouse was born in the early 1980s by Bill Inmon , who coined the concept. It emerged as a response to the need for a fluid and methodical data storage tool .
In short, a data warehouse is a large data store that stores data using historical files .
It also has a very important quality: it is able to analyze and classify information, highlighting that which is of substantial importance.
The data warehouse also has applications in the world of marketing. It functions as a repository capable of compiling all customer information , whether external or internal. This supports all advertising activities.
In any case, this data warehouse is used by corporations to streamline their large volume of information and direct it toward business intelligence (BI). This enables a fluid strategy that aids in decision-making .
If you still have doubts about what a data warehouse is for , the answer is very simple: to collect and classify data, filtering out those that have a certain corporate relevance.
Characteristics that define a data warehouse
If there’s one thing that makes a data warehouse stand out , it’s its ability to store business data. That’s its main quality and competitive advantage.
But beyond that, there are other data warehouse features worth reviewing. We’ll list them below:
- It focuses on a specific topic: it focuses a large collection of information on a central topic. Everything will revolve around that topic.
- It forms an integrated system: all collected information is treated in a comprehensive and stable manner, even if it comes from different sources.
- It’s non-volatile: information is only presented when its usefulness to users has been verified. Furthermore, it’s displayed in read-only mode, so it’s unalterable.
- Historical: It assumes that all information will be requested at some point, so it maintains a faithful file of past data.
Types of data warehouse
Another feature to keep in mind is that there are different types of data warehouses , so we’ll go into detail about each of them below…
- In real time: It’s constantly updated to ensure you always have the latest version of the information. A new compilation will be created every time new data is entered.
- Integrated: It works collaboratively with other information systems, allowing you to expand your range of data sources.
- Offline : This type of storage is updated every certain period of time according to your schedule. This can be daily, weekly, or monthly.
Advantages and disadvantages of a data warehouse
It’s time to talk about the advantages and disadvantages of the data warehouse because, despite being a highly useful business tool, it must be used with caution.
But let’s start with the positive points of this tool:
- It is an easy system to establish as long as the data is accurate.
- Keep information safe .
- Turn information into knowledge .
- Facilitates decision making .
- It allows you to know the current status of the company in terms of operations and risks.
- It is easy for employees to understand .
- Increase productivity .
However, it also has what some may consider disadvantages, but they are not a big deal compared to the aforementioned benefits:
- Its implementation represents a high operating cost .
- It can be complex to use, so inconsistencies often arise in the databases being manipulated.
- It requires constant maintenance to avoid data irregularities.
What is the difference between a data warehouse and a data mart ?
To understand this point, it’s important to talk about the data mart to put it into context. It’s a branch or subsystem of the data warehouse whose function is to query information. It stores small amounts of information that are usually important to a small group or specific department within the corporation.
Now that’s explained, it’s time to discuss the differences. Without a doubt, the most important difference lies in the type of storage each requires.
- A data warehouse requires a storage size of at least 100 gigabytes up to 1 terabyte, while a data mart is limited to 100 gigabytes.
- This is because a data warehouse collects large amounts of data, unlike a data mart , which only contains data that has been previously configured to be specific.
- A data warehouse uses information from across the entire company, while a data mart focuses on a small portion of the company.
