In software development, a proof of concept can be a vital tool to demonstrate the software’s capabilities and its fit with the client’s requirements. But how do you go about creating one? A recent example from our data integration work in the Oil & Gas industry illustrates the steps we take to create a successful proof of concept.
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Step 1: Defining the client’s requirements
Our clients’ needs can range from testing the suitability of the proposed software to sharing knowledge within the client’s organisation. In our recent Oil & Gas proof of concept, the main aim was to demonstrate the effectiveness of our Transformation Manager software in integrating the client’s exploration and production data. Specifically, the proof of concept demonstrated that it is possible to use the software to apply industry data standards to different types of petroleum data files.
In our example, there were two types of files – LAS and DLIS – to integrate using the PPDM and WITSML industry standards. The proof of concept accordingly aimed to deliver three scenarios:
- Embed transforms within near real-time message handling, based on WITSML
- Data migration converting to LAS files to and from the client’s PPDM-based system
- Data migration converting to DLIS files to and from the client’s PPDM-based system.
Step 2: Defining the client’s input
As with any project, defining the input required from the client is an important step to take before starting work on the proof of concept. In this example, the items required before the proof of concept could begin included:
- Business rules to define the required mappings, such as details of field mappings, lookups and error handling
- Samples of the data to be extracted, such as well header and log curve data
- Any relevant information about the source and target models, such as local usage of PPDM
- Sample files in the required format, including LAS 2.0 and 3.0.
Step 3: Review
Each proof of concept we create includes a review of the information received from the client:
- Each source and target data model, including format, connection options and sample data
- Validation rules
- Mapping rules.
Step 4: Design
Our consultants design the workflow of the data through the integration process. They:
- Document the flow of data
- Document the decisions made during the design process.
Then they design the integration for implementation using our data migration software.
Finally, a testing plan is created.
Step 5: Implementation
The consultancy team implements the integration within the software (in our case, Transformation Manager), including testing.
Step 6: Communication
Our team demonstrates the results to the client. They describe the process and usage of Transformation Manager to the client’s users. They also create a set of documentation (see Step 7).
Step 7: Delivery
In the petroleum data management example mentioned above, our team delivered:
- A final, tested, Transformation Manager deployment pack which delivered the data transformation to the client’s specification
- A licensed version of Transformation Manager for internal evaluation
- A proof of concept report
- Knowledge transfer to the client, including the use of Transformation Manager, a review of its capabilities and an overview methodology
- A presentation and demo showing key processes, outcomes and future options.
The result was a software component which can efficiently deploy the client’s data to a range of the most popular petroleum data management file formats.