Smart Data Vision
Speed, Expectations, Innovation
Today, speed is a one of the key success for businesses. We must quickly meet customer expectations, innovate and continuously improve manufacturing processes.
Gartner's prediction for 2016
Machine learning gives rise to a spectrum of smart machine implementations — including robots, autonomous vehicles, virtual personal assistants (VPAs) and smart advisors — that act in an autonomous (or at least semiautonomous) manner. While advances in physical smart machines such as robots get a great deal of attention, the software-based smart machines have a more near-term and broader impact. VPAs such as Google Now, Microsoft's Cortana and Apple's Siri are becoming smarter and are precursors to autonomous agents. The emerging notion of assistance feeds into the ambient user experience in which an autonomous agent becomes the main user interface. Instead of interacting with menus, forms and buttons on a smartphone, the user speaks to an app, which is really an intelligent agent.
"Over the next five years we will evolve to a postapp world with intelligent agents delivering dynamic and contextual actions and interfaces," said Mr. Cearley. "IT leaders should explore how they can use autonomous things and agents to augment human activity and free people for work that only people can do. However, they must recognize that smart agents and things are a long-term phenomenon that will continually evolve and expand their uses for the next 20 years."
What Type of Analysis
To exploit those data, four commonly types of analysis can be made:
◾Descriptive: what has happened (report, dashboard)
◾Diagnosis: why has happened (cause of a problem)
◾Predictive: What could happen (learn from experience)
◾Prescriptive: What should we do (optimal suggest actions and recommendations, ...)
When to perform Analysis
With Big Data those analytical types can be made with:
Real Time Analytics data can be sent through filters (Machine Learning) that will enable mathematical predictive or prescriptive models. Models like "Anomaly detection" to detect normalities that can leadfaults in one or more machines. This information will allow to trigger maintenance processes or implement a process to adapt the machine utilization. This is a simple example where speeding up process can be cost saving.
Batch processing for Business Intelligence (or Machine Intelligence), for years data warehouses have been created to study customer behavior, these studies can now take place on one or a set of machines to examine certain behavior, prepare simulations of use or anticipate degradations machines., due to the volume of data these kind of process could not previously be done.
Those data are inexhaustible sources of information for:
- Research & Development
- Testing & Quality Assurance
- Operational and strategic Managers
Why Korigan Services
Big Data technologies can be complex to deal with. Not all companies can afford to hire architects, data scientists, statisticians and so on.This is why Korigan Introduces its subscription which allows companies to exploit the power of Big Data, without hiring new people, consultants and more importantly without having to buy complex software or hardware (They Are all Open Source and in the Cloud).
In just few minutes your platform can be operational, up and running. Our service is based on several steps. We suggest a pragmatic approach and experimentation with concrete results. We want to start small, take the right decision for the next step and be sucessful.
Our goal is to smoothly Introduce Big Data in your company culture, and find values for your customers.