3 Business Questions to Guide Data Collection, Storage, and Insights

There is perhaps nothing worse than being in the middle of a project, only to find that the requirements and value were not clearly defined. When this happens, momentum is thwarted, and the end result is a choppy mix-match of components, instead of the seamless solution that was initially desired.

With this guide, you will be able to define the business and technical requirements for your data platform, making the implementation process efficient and successful.

The questions are designed to help you and your team think through a new–or improved–data handling platform.

Firstly, every new technology should be built to address a business need and be designed to offer the most possible value. Then, once the business requirements are identified, the technical details can be defined.


Three questions guide you through the solution from a business perspective.

  1. What are the business requirements?
  2. What is the value?
  3. Who is the customer?

In other words, know the problem you are trying to solve and how the ideal solution would function. Understand how the solution will help your company’s larger goals, and define who the end user is and how he/she/they will evaluate the product’s success.


Once the business requirements are defined, it is time to dig into the technical details. A bullet below each questions explains how the answer will define the technical solution.

  1. What amount of data will be ingested daily? 
    – affects size/speed of cluster
  2. What amount of queries will be done against the data daily?
    – affects speed of cluster
  3. What span of the queries will be done against the data daily?
    – affects speed of cluster
  4. Does the data need to be represented in real-time?
    – affects speed of cluster and messaging
  5. Does 100% of the data need to be guaranteed in the cluster?
    – affects messaging and redundancy in cluster
  6. What percentage of time does the database/solution need to be online?
    – affects size of cluster
  7. What length of time will you keep the data?
    – affects size of cluster
  8. How many different sources of data are there?
    – affects time spent writing code to transform data
  9. What alerts are needed to trigger automatically from the data?
    frequency, rate, missing, flatline, new, etc.
  10. How would you like the alerts to notify you/your team?
    – email, Slack, Jira, etc.
  11. Are daily reports needed?
    – affects technology, generally pdf emails used

If you have trouble answering any of the questions, we offer a free consultation to help get you on the right track.


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Dattell - Kafka & Elasticsearch Support

Benefit from the experience of our Kafka, Pulsar, Elasticsearch, and OpenSearch expert services to help your team deploy and maintain high-performance platforms that scale. We support Kafka, Elasticsearch, and OpenSearch both on-prem and in the cloud, whether on stand alone clusters or running within Kubernetes. We’ve saved our clients $100M+ over the past six years. Without our guidance companies tend to overspend on hardware or purchase unnecessary licenses. We typically save clients multiples more money than our fees cost in addition to building, optimizing, and supporting fault-tolerant, highly available architectures.

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