Introduction to Data Architectures
With data quickly becoming an essential asset of any business, the need for cloud data architects has never been higher. The key role these professionals fulfill is to provide the technical blueprints of any cloud data project and expertise on data architectures as a whole. A skilled data architect is proficient in many steps of the end-to-end data processes, such as data ingestion, data warehouses, data transformations, and visualization.
It is of utmost importance that data architects are familiar with the benefits and drawbacks of individual resources as well as platform-wide design patterns. Typically, aspiring data architects have a background as business intelligence (BI) developers, data engineers, or data scientists. They are often specialized in one or more tools but lack experience in architecting solutions according to best practices.
Compared to a developer profile, an architect is more focused on the long term and the bigger picture. The architect must keep in mind the overarching business strategy and prioritize certain aspects of the architecture accordingly. To equip you with the necessary skills to do so, you will be introduced to methods of getting business value from your data, to solidify any long-term data strategy.
This chapter will also introduce you to a wide-purpose referential data architecture. This architecture will be used as a guideline throughout this entire book and will become more and more defined as the chapters go on.
Finally, on-premises data architectures nowadays face a variety of challenges. You will explore these challenges and look at how a business can benefit from either a cloud or a hybrid cloud solution.
In this chapter, we’re going to cover the following main topics:
- Understanding the value of data
- A data architecture reference diagram
- Challenges of on-premises architectures
