Data Warehouse: what is it and how does it work?

The Data Warehouse is a great ally for organizations working with data. After all, it organizes and stores information, allowing everyone to view it clearly and actively contributing to assertive decision-making.
In practice, the tool works as a data warehouse capable of offering countless alternatives so that leaders and managers can optimize their time and make better use of international assets.
Thanks to this architecture, it is possible to generate value from what is produced in transactional systems to enable a broad overview of the business.

Want to know more about the Data Warehouse and discover how it works in the corporate context? Then, continue reading and check out the article that the CodeBlog team has prepared for you.

Data Warehouse: the definition

Today's reality is basically marked by data. They are everywhere and are generated from the most diverse sources such as systems, CRM, automation softwares, and much more. Often, this information is presented in a completely unstructured way and cannot be analyzed quickly.
In this context, the Data Warehouse arises. A solution that coordinates data, facilitating its use in decision-making and allowing exact answers to important business questions such as: the number of sales of the month, how many customers selected a product in the cart but gave up on the purchase, and much more.
In short, this is a storage structure that keeps data in a structured format to facilitate queries and analysis as a set fully laid out to simplify use by analytical tools. Therefore, it can be an alternative for collecting and processing Big Data, as well as an excellent tool for Data Science projects.

Data Warehouse: the architecture

The Data Warehouse architecture is composed of layers.
The top layer is the front-end client, which presents the results through reports, analysis, and data mining.
Next comes the middle layer, which involves the analysis engines used to access and analyze the information.
And, finally, the bottom layer, which is composed of the database server - the environment where the information is loaded and stored.

Data is stored in two different ways:

1. Very fast storage:

Data that is frequently accessed is kept in very fast storage (such as SSD drives).

2. Cheap object storage:

Data that is accessed occasionally is kept in cheap object storage, such as Amazon S3.

Data Warehouse: main features

Data management:

The Data Warehouse facilitates data management because it offers a deep and historical view of all information, not just limiting itself to the most recent.

Data integration:

The Data Warehouse integrates data from different sources and formats, such as strategic, transactional, and business information, among others. This integration is essential to make the best use of data by simplifying a complex structure, facilitating management and access to information.

Non-volatility of data:

In the Data Warehouse, data remains unchanged, persistent, and stable. This occurs because the DW is an essentially relational tool. That is, the solution operates through simplified and easy-to-understand rows, columns, and tables.

Benefits of the Data Warehouse

Agility in queries

With the integration and organization of data promoted by warehouses, it is easier to perform queries and analyses quickly. In practice, the solution ensures better performance and more productivity for teams, ensuring that employees from different areas answer emerging questions about business processes.

Data quality

It is the obligation of companies to value the quality and security of users' data. The DW is a great alternative for this. After all, the Warehouse structure itself concentrates data cleaning tools, acting to provide clear, clean information in perfect condition. Reaching the desirable standard of data quality is extremely important for an organization to follow internal management and governance rules and establish compliance with external protection and security laws and regulations.

Security

The Data Warehouse also acts in the optimization of the security of corporate processes, helping to improve data administration and reinforce user protection. To do this, the tool integrates access rules, offers total control over the asset lifecycle, in addition to numerous security protocols.

Historical view

The Data Warehouse not only records current data, but also manages the changes that information undergoes over time, allowing users to view temporal trends and analyze how data changes from time to time.
This is a fundamental solution for predictive analysis that can also be used as a basis for training machine learning models and even generating complete dashboards and visualization panels for reports, indicators, and graphs.

Scalability

The Data Warehouse structure is capable of handling growing sets of data generated in real-time, from the most diverse formats, regardless of the volume of information.

Autonomy

The Data Warehouse generates simplified data, so any authorized user can perform analyses and generate reports. Thus, employees gain more autonomy, the IT team is less overloaded, information flows more efficiently, manual work is reduced, as well as bureaucratic processes.

How to implement the Data Warehouse in the cloud?

In the AWS Cloud, regarded as the most reliable in the world - developed by Amazon and made available by CodeBit -, your business can have all the benefits of on-demand computing, such as access to unlimited storage capacity and system scaling according to the volume of collected data.

Get in touch with our team of specialists and learn more about the broad set of seamlessly integrated managed resources, which allows the rapid deployment of a complete analytics and Data Warehousing solution.

Otherwise, keep an eye on CodeBlog. Soon, we will have news here.

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