Technical Discovery
Technical Discovery & MVP
We can assess any aspect of your current data management architecture in order to identify opportunities for growth and improvement. As part of this, we can deliver insights and actionable recommendations to help you navigate your data challenges and therefore quickly get started with your solution.
We specialise in designing and building Minimum Viable Product (MVP) data solutions to help you start your data journey. All the stages of a data workflow based on your problem will be created for you. This includes extensible and reusable components that you can further build on and apply to other areas of your data landscape.
Describe the Data Landscape
Describing the landscape involves assessing the relevant parts of the current data landscape by identifying pain points, conducting SWOT analyses and evaluating competitor strategies to subsequently gain a comprehensive understanding of opportunities, challenges and gaps.
Capture the Data Journey Requirements
Capturing requirements involves understanding the specific objectives, key results and stages of the whole data journey for the product, in addition to describing all of the non-functional requirements (NFRs) needed to address essential properties such as performance and security.
Design an MVP
Designing an MVP involves creating a simplified version of the entire data journey of the product with the core features necessary to meet initial user needs, validate assumptions and gather feedback for future development. Key metrics and tests are defined which are be used to measure success at each stage of the data journey.
Iterative Building, Testing, Deploying and Validating the MVP
The process of iterative building, testing, deploying and validating MVP solution involves making incremental improvements, then rigorously testing each iteration using a set of automated tests that capture the core requirements. After the tests pass, the improvements are ready to be released to the users.
Launch the MVP
We launch an MVP data product by firstly developing a streamlined version along with a set of automated tests that capture the core requirements. We then help you plan a repeatable release process that you can use for deploying future updates to production.
Build-Measure-Learn Feedback Loop (BML)
After launching the MVP, the Build-Measure-Learn (BML) feedback loop can be initiated by collecting user feedback and performance metrics, then analysing them to identify areas for improvement. This insight drives iterative development, refining the product based on real-world usage and needs.
Get In Touch
Ready to solve your data challenges? Contact us to find out more about our services and pricing