{"id":9566,"date":"2025-06-06T09:07:20","date_gmt":"2025-06-06T09:07:20","guid":{"rendered":"https:\/\/weareoakland.com\/?p=9566"},"modified":"2025-06-09T07:56:38","modified_gmt":"2025-06-09T07:56:38","slug":"what-is-data-platform-architecture","status":"publish","type":"post","link":"https:\/\/weareoakland.com\/blog\/what-is-data-platform-architecture\/","title":{"rendered":"What is Data Platform Architecture?"},"content":{"rendered":"\n

What is Data Platform Architecture?<\/h1>\n\n\n\n

Is your data architecture designed to ensure scalability, reliability, and long-term success? We know that organisations are increasingly investing in data platforms to bring their data together in a world driven by data. And while this enables you to gain the insights you need to make better business decisions based on knowledge (not assumption), building a data platform<\/span><\/a> isn\u2019t just about choosing the latest tools or storing massive amounts of data. <\/p>\n\n\n\n

It\u2019s also about choosing data architecture that’s most relevant and applicable to your business. <\/p>\n\n\n\n

If the architecture doesn’t fit in with your overall enterprise, the platform investment risks ending up as a missed opportunity. <\/strong><\/p>\n\n\n\n

Read on for everything you need to know about data platform architecture, from why it\u2019s important when building a data platform<\/span><\/a> to key considerations when choosing the right architecture for your business.<\/p>\n\n\n\n

What is Data Architecture?<\/h2>\n\n\n\n

Data architecture is the strategic design and structure of how data is collected, stored, managed, and used within an organisation. It acts as a blueprint  for how data flows through systems and how different components, like databases, data warehouses<\/span><\/a>, data lakes, and analytics<\/span><\/a> tools, interact with each other. Think of it like constructing a building: without a solid architectural plan, you risk creating something unstable, inefficient, or impossible to live in. <\/p>\n\n\n\n

Read our article to learn more about <\/strong>building or buying a data platform<\/strong><\/span><\/a>.<\/strong><\/p>\n\n\n\n

Why is Data Architecture Important?<\/h2>\n\n\n
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At the very heart of a data platform<\/span><\/a> is a core set of capabilities (ingestion, storage, processing etc). However, understanding your business needs and how these capabilities fit within the wider enterprise is fundamental to success of the platform. <\/p>\n\n\n\n

For example, think about the source systems where your data is held. If 90% of your data is held within a core Enterprise Resource Planning (ERP) solution (such as SAP<\/span><\/a>), there is limited benefit in moving all your data to a separate data solution – especially when you may be driving value from the wider SAP estate, such as SAP Analytics cloud. <\/p>\n\n\n

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Likewise, if most of your use cases require real-time data to support operational decision making, understanding where your data is and how you\u2019d like to use it will immediately shape the platform design. Knowing your business, its data and application estate, and case for change are foundational pieces that must be used to define the architecture of the platform, rather than trying to force the business to adopt something that isn\u2019t fit for purpose.  To continue our house analogy, there is no point having an amazing surround sound 4k home cinema if there are no plug sockets nearby to plug it in!<\/p>\n\n\n\n

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Why do you need a data platform?<\/span><\/a><\/div>\n<\/div>\n\n\n\n

Scalability<\/h3>\n\n\n\n

As data volumes grow, your platform must scale without breaking. A well-architected platform anticipates growth and supports horizontal scaling, distributed processing, and modular components that can evolve independently. Understand what else you need to consider when designing and building your Data Platform<\/span><\/a>:<\/p>\n\n\n\n

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The ultimate guide to building a Data Platform<\/span><\/a><\/div>\n<\/div>\n\n\n\n

Performance<\/h3>\n\n\n\n

Poor data architecture can lead to bottlenecks, slow queries, and frustrated users. Optimising data flow, storage formats, and compute resources ensures your platform performs well under pressure.<\/p>\n\n\n\n

Data Quality and Consistency<\/h3>\n\n\n\n

Investing in architecture and setting out your data architecture roadmap can help enforce data governance<\/span><\/a> and standardisation, not to mention data quality. By defining clear data models, validation rules, and lineage tracking, you ensure that data remains accurate, consistent, and trustworthy. This trust is critical if people are going to use the platform, otherwise, it runs the risk of being a very expensive storage solution. <\/p>\n\n\n\n

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Why invest in data quality?<\/span><\/a><\/div>\n<\/div>\n\n\n\n

Security and Compliance<\/h3>\n\n\n\n

With increasing regulations, like GDPR, and the increased cyber threat, data security is non-negotiable.  It seems like we\u2019re seeing organisations, such as Marks & Spencer<\/span><\/a> and the Co-op, in the press due to a data breach or cyber attack. A strong architecture can help minimise the risk of this.  Considerations in this area includes access controls, encryption, auditing, networking  and compliance mechanisms from the ground up.<\/p>\n\n\n\n

Beyond this, the architecture also needs to think about how these policies & processes work with wider enterprise governance requirements. For example, your platform needs to be able to facilitate a \u2018right to erasure\u2019 request, even though it is not the source system that is generating the data.<\/p>\n\n\n\n

Flexibility and Integration<\/h3>\n\n\n\n

Modern data platforms must integrate with a variety of tools, such as BI dashboards, machine learning models, APIs, and more. Focus on data access both to and from the platform, and do not see the data platform as the end point, merely part of the wider data ecosystem.<\/p>\n\n\n\n

Cost Efficiency<\/h3>\n\n\n\n

Without thoughtful architecture, cloud costs can spiral out of control. In particular, where organisations are moving from on-prem to cloud, this shift from CAPEX to OPEX needs careful consideration. While running your platform, there is a constant need to ensure that you are optimising your services. Efficient data partitioning, storage tiering, and compute resource management help keep costs predictable and manageable. <\/p>\n\n\n\n

Find out the data architecture we used to build a platform for Income Analytics: <\/strong>Creating catalysts for growth with Income Analytics<\/strong><\/span><\/a>.<\/strong><\/p>\n\n\n\n

Key Components of a Good Data Platform Architecture<\/h2>\n\n\n\n