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- I Am Datapedia!
Others
PVP Approach
Yes, you are right, you might not have heard about this approach. It is something new which Myself is working on.
Let’s decode it…..
Productionizable Viable Product (PVP): A Revolutionary Approach to reduce TTM (Time to Market) of adopting cutting-edge Data & Analytics Technologies while minimizing CAPEX (Capital Expenditure).
‘PVP focuses solely on new data & analytics initiatives rather than enhancements.’
Productionizable Viable Product (PVP) approach represents a distinctive approach in optimizing IT project execution by employing a singular Production environment throughout the project lifecycle. This streamlined architecture is designed to alleviate the complexities associated with managing multiple environments. To address data privacy concerns, the PVP architecture integrates controlled measures such as data masking or anonymization during the initial phases of development and testing, ensuring adherence to regulatory standards. The incremental provisioning strategy is a pivotal aspect, commencing with the provision of minimum required services or tools in the Production environment. The architecture emphasizes iterative testing cycles within the Production environment, allowing for continuous validation of integrated code sets through incremental Testing. This cyclic Testing in Production ensures thorough scrutiny before the final release to end users. In essence, the PVP architecture provides a structured and controlled framework, optimizing workflows, reducing complexities, and enhancing the reliability of Analytics project execution.
3 min readMore
- I Am Datapedia!
Others
POC,Prototype,Pilot/ MVP,Testing, andProd
Approaches play a vital role in the failure of many projects in the IT World. We all have heard about POC, Protype, Pilot, MVP, SIT, UAT, and Production implementations, but I am sure, most of us might have not given a thorough thought of aftereffects, if one is interchanged with other.
Let’s try to understand everything in the upcoming topics but to give a broader perspective all above approaches have their own implementation strategies. Most of the projects fail when e.g., started with a POC and once the POC is successful, move the same in Production. One must not do that. This normally happens when business push implementers to achieve tight timelines.
Please note, small level of implementation which in our example, POC might be successful with limited infrastructure or software, but 99% chances are when it goes in Production, it’s bound to fail. Same is true for Prototype, Pilot and MVP environments. One must plan infrastructure and software based on, if plans to be in Production.
1 min readMore
- I Am Datapedia!
Others
Productionized Solution
In MVP stage where actual Tools and Technologies, and SIT, UAT, and PRODUCTION environments are implemented on a small scale.
Once MVP is successful, the next stage is to gather complete business requirements, a complete designed is made, teams are built, project plan is made, end-to-end SOW is signed, development is conducted, testing is done i.e., UT, SIT and UAT, and solution goes live.
On contrast with POC, Prototype and Pilot/ MVP, in this stage a complete Infrastructure, Software and Data is prepared and used.
UT stands for Unit testing and is done by developer during development phase for every piece of code developed. The better the UT is, the better the product will be.
SIT stands for Systems Integration Testing. Now a days, SIT is disappearing, SIT is the first step to save cost which is NOT a good idea. I am sure in a decade, newbies in IT World might not even know what actually SIT is. Once complete solution is ready, it’s moved to another environment which do have all the possible components of the actual solution but in term of size, it is small e.g., if based on data there is 10 servers and 100 licenses are required, SIT can be run with 1 server and with 1 license. In SIT, we make sure code can run end-to-end, user access is properly set, security protocols are in-place, jobs dependencies are in-place etc.
2 min readMore
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