We understand that deciding which technologies should be adopted and incorporated into your business is not an easy task. It requires a strategic evaluation procedure that relies on proof-of-concept testing. Each PoC requires many steps and involves a network of stakeholders, making the process that much more complicated and time-consuming. Knowing the relevant terminology is imperative to your decision making strategy when evaluating and on-boarding new technology. To ease this process and make things a little less daunting, we created a glossary of all your need-to-know terms regarding proof-of-concepts to enhance your knowledge and help you make informed decisions along the way.
Behavior mirroring mimics the network traffic and other behavioral factors that simulate an enterprise’s production environment under which solutions will later have to perform. By utilizing prooV’s Deep Mirroring technology, enterprises can make more informed decisions based on accurate results.
Like Behavior Mirroring, Data Mirroring uses the same Deep Learning technology to learn the patterns and structure of the data sets to produce synthesized results that can be populated in your PoC environment. Using this process, enterprises can maintain data structures, including table structures, data types and relationships, while preserving the confidentiality of the original data through obfuscation. By masking the data, the enterprise can avoid exposing its data and stay compliant with cyber-security regulations.
There are different approaches to open innovation but the core principle behind it is the exchange of ideas and technologies within an open and permeable system. One approach, the outside-in method, calls for the adoption of new technologies from outside vendors to be integrated within an organization. Whereas the inside-out approach, relies upon in-house resources to create out of the box solutions, rather than exploring solutions with outside vendors.
Running a proof of concept (PoC) involves creating an environment where software and other technology can be tested against predetermined criteria without affecting existing operations. A PoC environment enables companies to see how solutions perform under conditions that replicate their production environment, allowing them to evaluate feasibility and scalability with low risk.
Proof of Concept
A proof of concept is an exercise or experiment that is designed to evaluate whether a software solution is feasible. By designing an environment where solutions can be evaluated on a smaller scale, companies can determine whether or not to commit to a full-scale implementation. This process reduces risk, saves time and money and gives companies the opportunity to accurately evaluate potential solutions.
The PoC lifecycle is the step by step process of running a PoC, which includes defining the objective of the PoC, setting the conditions and environments, inviting the vendors, executing the evaluation process, and analyzing the results. With our PoC platform, we are able to fast-track the tedious PoC process from years to months.
A PoC platform or platform as a service (PaaS) provides a centralized location where enterprises can establish customized testing environments and evaluation metrics that let them to vet several software solutions at once. These platforms enable businesses to connect with vendors and accelerate the evaluation process.
SMART Business KPIs
Business key performance indicators are a set of requirements that are designed by a company to measure the testing results in comparison with their business objectives. KPIs provide a way to specifically measure certain performance categories so that companies can decide where to invest their time and energy. For example, if a company is evaluating AI solutions, they may consider factors like response/accuracy, quickness and data needed as potential KPIs.
While KPIs will vary among departments and companies, the acronym SMART defines the main characteristics of an actionable KPI. When you are building your business KPIs, make sure to consider SMART practices:
- Specific – Is your KPI clearly defined and specific to its objective?
- Measureable -Does your KPI collect specific data that can be measured and evaluated?
- Attainable – Can you reasonably attain the KPI?
- Realistic – Have you established a KPI that can be achieved on a basic, practical level?
- Timely – Can the KPI be measured over a fairly short period of time?
Synthetic data is anonymized data that has been generated to either protect confidential information from being released or extend the testing database to meet specific scenarios that can’t be found in nature. In cases like facial recognition or autonomous driving, the database must be extended to accommodate for a range of phenotypes or provide a virtual environment that can simulate real conditions. By utilizing AI, synthetic data can be created to facilitate these conditions.
Technical key performance indicators are the criteria you establish to evaluate whether a solution meets your technical needs. By establishing these standards ahead of time, you can quickly determine which solutions work best for you. At prooV, we have created hundreds of predefined technical KPIs such as Network Statistics, TCP Metrics, Standard Performance Counters, CPU, GPU, etc.
Are there any terms you’re still wondering about? Let us know what terms you want to see in our next update by sending an email to [email protected]!