In data warehousing, data is collected from multiple sources and stored in one place to analyze, report, and use to make business decisions. Organizations typically have a transactional database with information about every aspect of their daily operations. In addition to these sources of data, organizations may have other sources, such as third-party data or internal operations data.
An ELT or ETL process is used to collate and store all these data sources in a data warehouse. Data from these sources can be combined to make business decisions using the warehouse’s data model. When building your first data warehouse, you should consider the following factors.
Impact of Data Sources
Many decisions in a data warehouse architecture are influenced by the types and formats of data sources. As you implement a data warehousing solution, there are several best practices you should follow related to source data.
Before designing a warehouse architecture, it is essential to obtain detailed information about the data source, the types of data, and their formats. It will be easier to develop the logic for extracting and transforming data if this is done in advance.
ETL frameworks will also be chosen based on data sources. The extent to which the ETL framework integrates with the data sources determines whether it is customized or purchased from a third party.
The Choice of Data Warehouse
Choosing between building and maintaining an on-premise data warehouse or using a cloud-based system is one of the most important decisions when designing a data warehouse system. The pay-as-you-use model is available for various options for data warehouses as a service. In the same way, organizations can deploy an array of open-source and paid data warehouse systems.
On-Premise Data Warehouse
Customers who deploy on-premise data warehouses install one of the available free or paid systems on their own servers.
Advantages of using an on-premise setup
- Your data is ultimately under your control, which is the most significant advantage. An on-premise system is the best solution for enterprises with strict data security policies.
- Getting data from a cloud system can sometimes be a hassle, especially since the data is close to where it will be used. The flexibility of having all your systems on your own internal network can solve this problem to some extent with cloud services with multiple regions.
- When most of the data sources are within the organization’s internal network, and the organization rarely uses cloud data from third parties, an on-premise data warehouse may be a better choice.
Disadvantages of using an on-premise setup:
- The development process for an on-premise system is time-consuming and requires significant effort.
- The company has to bear the infrastructure cost of new hardware even if you need a higher capacity for a short period.
- On-premise setups do not allow scaling down at zero cost.
Cloud Data Warehouse
Customers do not have to deploy or maintain a data warehouse using a cloud-based service. As part of the service, the provider builds and maintains the data warehouse, and all the APIs required to operate it are provided by the provider.
Advantages of using a cloud data warehouse:
- In a cloud data warehouse, scaling is effortless, as the provider manages this seamlessly, and the customer only pays for the storage and processing capacity he uses.
- A significant advantage of scaling down is that billing will stop for instances as soon as they are stopped, so organizations with budget constraints can scale down quickly.
- Building and updating highly available, reliable data warehouses are not part of the customer’s responsibilities.
Disadvantages of using a cloud data warehouse
- As a result, high-security industries may be concerned about data security when the organization’s data is contained within the service provider’s data center.
- Since the data isn’t present in the organization’s internal network, there can be latency issues. Fortunately, cloud services offer multi-region support, ensuring information is stored in your chosen region.
- It is best to use an on-premise data warehouse or a cloud-based service early on. If your organization experiences high processing volumes for the day, an on-premise solution might be worth examining since it doesn’t require seamless scaling up or down.
To remain competitive, businesses need data and analytics. Users rely on reports, dashboards, and analytics tools to monitor business performance, extract insights from data, and support decision-making. To minimize data input/output (I/O), data warehouses are designed to store data efficiently, allowing hundreds and thousands of users to quickly receive query results.