Real-time data is frequently requested and rarely necessary. The cost of genuinely real-time data pipelines - in infrastructure, complexity, and maintenance overhead - is substantial, and the decisions most businesses need to make do not require sub-hour data to be made well.
This whitepaper helps you identify which decisions genuinely require real-time data freshness and which are perfectly well served by hourly, daily, or overnight refreshes - and how to design a refresh strategy that matches the cost to the actual requirement.
Most organisations need right-time data. Very few need real-time.
The actual cost of real-time data infrastructure
Streaming pipelines, low-latency storage, and the operational overhead of maintaining them at a production standard are not cheap. For most mid-market organisations, the cost of a real-time data layer exceeds the value of the marginal freshness it provides over a well-designed batch approach.
Matching data freshness to decision frequency
The right refresh frequency is determined by how often the decision it serves is actually made - not by what would be technically possible. The whitepaper provides a framework for making that assessment for the decisions your organisation actually relies on.
What the whitepaper covers
- A framework for assessing which decisions genuinely require real-time data
- The real cost of streaming pipelines and low-latency infrastructure at mid-market scale
- How to design a data freshness strategy that matches cost to actual business need
- The scenarios where real-time is genuinely justified - and the ones where it is not
- How to have the right-time versus real-time conversation with stakeholders who default to real-time
Who this is for
Data engineers, architects, and analytics leads who are being asked to deliver real-time data and want a framework for evaluating whether that requirement is genuine - and how to push back constructively when it is not.