Two powerful Engines drives the solution. The Solution tackles five main challenges:
Data is the essence of an every business decision today. However capture data from various platforms, store and govern structural and unstructural data, validation of the data are some of the challenges. Big Data became awkward to work with using on-hand data base management tools. MyDROIT technology enable the solution to cope with the Big Data in very efficient way. Companies now are capable of recording more data at an ever-increasing rate, but the return of that derived from that data is not efficient at all. They keep track and capture every call, click, purchase-like interactions and data but they all get burdened and all the databases strain under the high volumes. What is called “bigdata” today is an unsolved issue for the IT department of the companies which only stands in there collapsing volume but not being used for business intelligence.
The Engines manages millions of customers and thousands of offers. The computational complexity by using large quantities of data with intolerable elapsed times requires exceptional technologies. MyDROIT Technology applies massively parallel-processing (MPP) databases, data-mining grids, distributed file systems, distributed databases to make the solution salable.
Processing the Big Data to create intelligence is much more challenging if speed of intelligence, agility and adaptability of intelligence, enters the game as a must. The response requirement of a predictive model is approaching real-time. Scoring consumer data in real-time is easy; however building models in real-time is becoming a necessity as business is becoming more dynamic and the shelf-life of a product (a news article, a tweet, a video) can be measured in hours. In-memory analytics technologies, high performance computing technology, dynamic file system management and advanced data replication techniques are the features of MyDROIT Engines that may generate 1.5 million of business decisions in a second.
MyDROIT Engines employ a family of machine learning and statistical algorithms to produce accurate, high performance personalization in real-time. An ensemble model is an ensemble of models that are collectively superior to its individual constituent models. Each model in an ensemble model is the result of application of a speciﬁc algorithm to data. Machine learning and statistical algorithms”learn” the data in speciﬁc ways. An ensemble model combines the knowledge produced by each algorithm into a superior one. Hence, the selection of algorithms that the engines will use in a personalization system is entirely dictated by client requirements and constraints.
The overriding goal to replace human decision makers in programmable decision situations is:
- Increased through put or productivity.
- Improved quality or increased predictability of quality of the intelligence.
- Improved robustness (consistency), of intelligence processes.
An automated decision process occurs without any “human” intervention. End to end intelligence creation process automated by MyDROIT.
Relevant, measurable behavioral analytics. In the regular reports you usually get the sense of what happened, but it doesn’t apparently point why it happened or what should be the reaction or the next action. O4, with evaluating the data and analyzing the behavior of the consumers will present the best to do to them. With multiple combination offers, they consumer will definitely click on one of each to go on. The highest concentration on this is that to increase the visitors, conversion rates, stickiness and definitely gain more revenue.