What is a Data Warehouse and is it the right option for your organization?

In today's data-driven world, organizations are inundated with information from diverse sources. Effectively harnessing this data can be a daunting task, leading many organizations to turn to data warehousing solutions. But what exactly is a Data Warehouse, and what are the advantages and disadvantages of adopting one? In this blog post, we hope to shed some light on its role as a centralized repository of historical data. You will want to weigh the scalability and powerful analytics capabilities with the challenges of maintenance and cost when deciding whether to leverage this technology. 

What Is a Data Warehouse?

A Data Warehouse is a centralized repository of historical data, usually derived from multiple sources, built and organized to provide analytics and reports on the underlying data. They are often hosted in ‘The Cloud’. You will need to have a deep understanding of your organization's data as well as a high level of data maturity to build, organize, and manage a Data Warehouse. Strong data governance practices are also needed to maintain the integrity of the Data Warehouse. (For more on Data Governance, see our blog series starting here).

Advantages:

They are powerful, scalable, and provide valuable analysis across platforms and over time. Another advantage to hosting your Data Warehouse in the cloud is that security can be partially outsourced to the highly skilled data security engineers at Microsoft, Google, or Amazon. Most data engineers, and certainly most data analysts, do not know how to build a firewall from scratch to protect an on-premise resource or how to develop custom encryption algorithms. If you want that level of protection for an on-premise system, you will need engineers who specialize in data security to protect it for you. The Cloud providers have extremely skilled experts on their engineering teams who build and manage these types of protections that come standard with their Cloud resources. And, your data is more accessible in the Cloud versus when it is stuck in one place. 

You can access data from the Cloud from anywhere in the world (provided security protocols are followed). An on-premise system can often only be accessed while the user is physically on the network of the data system. The exception is an on-premise system with a route for users to remote into their system from outside of the network. But in this scenario, the team would have effectively just built their own Cloud.

Disadvantages:

Data Warehouses can be costly and difficult to maintain, even when you are using services such as Microsoft, Google, or Amazon, though they make it a lot easier. Data Warehouses require engineering skills to build AND manage on these platforms. To take advantage of the robust data security, you need to have someone around who understands the basics of the tools mentioned above and how to implement them. And the skills required to support a Data Warehouse are fairly technical (and can be expensive), whether you hire someone as a staff member to do that work, or partner with a vendor. While there are some direct costs related to hosting a warehouse, it scales fairly well with the amount of data you have, but the skills and expense of the people needed to build and maintain them should still be taken into consideration. 

Data Warehouses play a crucial role in empowering organizations to extract valuable insights from their many data sources. Despite their significance, navigating the realm of Data Warehouses can prove challenging due to their considerable costs and the specialized expertise required for setup and maintenance. However, the benefits they offer, such as scalability and advanced analytical capabilities, outweigh these challenges. As technology advances and data continues to proliferate, the importance of Data Warehouses will only continue to grow.

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