in Big Data and Data Science
The world of ‘the internet of things’ (IoT) with its connected devices, appliances, machines and people is growing at the speed of light, creating a Big Data explosion. O2MC I/O is a patented framework for managing data streams, especially built to cope with the complexity of Big Data. It provides companies with the computational capacity to create value and benefit from data in a way that was not possible before.
Our computational framework is deployed as a cloud solution, a so called Framework as a Service (FaaS). In a few words, FaaS falls between SaaS (Software as a Service) and PaaS (Platform as a Service). A Platform as a Service will take more time to implement, it needs to be deployed in the business context. Software as a Service on the other hand provides an ‘off shelf’ ready to go product with its limitations in tailoring it to specific business requirements.
FaaS is best of both worlds. It enables you to implement your application with the speed of light, powered by your business context. Furthermore, it is your foundation for agile IT operations and faster execution of business knowledge. With this seemlessly integrated and interoperable framework, agility and competitive advantage go ‘hand in hand’.
“FaaS vendors may offer solutions by industry verticals (e.g., financial institution or emergency response services applications) or by production environment type (e.g., Web applications).” TechTarget
In a nutshell, Prescriptive Web Computing can be defined as automating a prescriptive instruction in a multidimensional context. Based on this, programmers, scientists and software engineers can easily contribute to transform Big Data into commercial and operational intelligence. Our customers and partners incorporates our technology into their services and data driven applications – as a service or on premise – to empower their business with today’s most efficient Big Data operations.
DimML: our proprietary flow based programming language, connecting anything to everything
EASY AND INTUITIVE BIG DATA PROGRAMMING
Our unfair advantage in creating today’s most efficient data operations is DimML, a unique intuitive programming language. DimML stands for Declarative ‘in motion’ Machine Language. Declarative means that it allows users to express and instruct what the program should accomplish, rather than describing how it should be accomplished. So the genius is in its simplicity; making programming very intuitive and easy to master.
UP TO ANY TASK – BIG DATA SIMPLICITY
Thanks to this language, you can use our technology to build all data driven business solutions you can imagine. Even the most demanding. Get online data collection up and running in just 5 minutes, creating faster and better insights. Be creative and imagine how easy Big Data streams can be of extreme value for your business. Gain insights in the customer journey on the fly and connect the smartest data to any business process quickly, easily and flexibly.
Our technology is applicable to the entire scope of Data Analytics. You can use it to run descriptive solutions to analyze past events and why they happened (diagnostic). But why not use data to predict what will happen next? You can even aim for prescriptive – the most advanced level of analytics – and receive decision options to take advantage of future opportunities or to avoid risks that might turn up. Prescriptive analytics cannot only show future outcomes, but it can also recalibrate algorithms to make better and better predictions for any industry.
Take the next step
Descriptive analytics is the basic level of analytics that helps to establish business context by asking and answering questions like “What happened?” This solution uses Business Intelligence and Data Mining to drill directly into the data to discover trending information about past or current events.
Predictive analytics uses Forecasts and Statistical Models to answer questions like “What could happen?”. This approach helps decision makers to anticipate different scenarios, rather than just react to what happened in the past. Although this level of analytics does not recommend action points, it is a step forward in making better informed decisions.
Prescriptive analytics is the highest level of analytics that uses simulation and optimisation to explore possible actions and suggest future steps. It is based on both descriptive and predictive analytics and supports decision makers to answer questions like “What should be done?”. This approach also takes into account all risks that may result from the action points suggested.