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What Is a Data Warehouse and How Does It Work?

August 29, 2022

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In the cloud, the data warehouse is a type of data management designed to perform analyses on large amounts of data. It ensures uniform data collection, supports business decisions based solely on numbers, and improves overall business strategies and efficiencies. In this article, we will discover how a cloud data warehouse works, as well as its benefits.

An Overview of the Data Warehouse 

The data warehouse is a centralized system used for reporting and analyzing raw data within a company. The totality of this data, current or archived, is also referred to as the single source of truth (SSOT). It exists to meet companies’ needs to store, filter, aggregate, and analyze large volumes of data. It is an important part of a company’s business intelligence strategy

Top-notch cloud-managed data warehouse solutions include Google’s BigQuery, Amazon’s Redshift, and Microsoft’s Azure SQL Data Warehouse.

The Architecture and Construction of a Data Warehouse  

Due to the fact that data needs to be sorted and refined to be usable, data warehouse architecture is built to find the most efficient way to extract raw information, and to translate it into an understandable structure for optimized value. 

When building such a warehouse, there are three architectural approaches to consider—each with its own benefits and drawbacks.

The single tier architecture is focused on creating a compact data set and minimizing the amount of stored data. This approach will not meet the needs of an enterprise with large volumes of data.

The two-tier architecture works by separating physical resources from the data warehouse resources. While this approach is more efficient for storing and sorting data, it is not scalable and only supports a small number of end users.

The three-tier architecture is the most popular warehouse architecture as it creates a structured and operational workflow with relevant results and insights.

Data Warehouses Versus Data Lakes

Companies can opt for either data warehouses or data lakes, both of which cover different needs. A data warehouse specializes in analyzing large volumes of data, gigabytes or petabytes from different sources, and transactional applications or operational databases. This is the recommended setup for organizations that need advanced analytics, which includes data from company history.

On the other hand, companies can also opt for data lakes that store disparate, unfiltered data in raw form. The structure, integrity and format of these datasets are decided by the developer performing the analysis. Data lakes, such as the Snowflake Cloud Data Platform, can be used in addition to a data warehouse. They are more likely to be associated with companies that need low-cost storage and unstructured data. 

How Does a Cloud Data Warehouse Work?

Cloud data warehouses take advantage of the best features of cloud computing technology, such as flexibility, scalability, agility, low costs for consumed resources only, and security. In addition, cloud services are pay-as-you-go. A data warehouse in the cloud will focus exclusively on the information and data retrieval side—with no resources spent on managing the hardware or software infrastructure.

The functionality of a data warehouse is divided into three stages. The first of these is the server on which the data is uploaded and stored. In the second stage, the analytical part conducts the actual analysis of the data. The last stage is the interface through which the client works, and the results obtained from analyzing, reporting, and mining the data.

Implementing a Cloud Data Warehouse at Your Company

From planning to the design of the repository, this platform helps you get the information relevant to your industry and goals. With the right solution, you can always be one step ahead of your competition with new product development, archive analysis and/or pricing strategies.