infoWave develops responsive, cross-Platform/OS/Browser Websites and Apps to for viral network effects and would like to be your Technology partner to deliver Virtualization and Cloud solutions for Big Data, Cognitive Computing, Deep Learning Algorithms and Predictive Analysis.
Stride by stride, infoWave continues to innovate and delivery solutions at the rim of technology, leveraging its historical and current strengths, along with its group company – Silicon Interfaces, in providing services for the Desktop, Apps and Websites, be it a Browser-based, Client-Server and Cloud-based on Microsoft® .Net and Oracle® Java J2EE technologies and, into the exciting world of Mobiles and Devices, like Smart Phones and other Devices, running Microsoft®, Android, Apple® iOS, Microsoft®, Phone, Etc.
The Company offers services to ensure that your applications run on Operating Systems - Windows, Android, Linux, iOS, macOS , Etc and Browsers IE, Firefox, Mozilla, Chrome, Safari, Opera , Etc and Social environments, like Facebook©, Google+©, LinkedIn© and integrate with Twitter©.
So, if your application is Event Driven or Service Oriented, requiring Agile Modeling for vertical domains using Web Services, Ajax or Ruby-on-Rails, XML, SOAP and WSDL, internet, ecommerce or e-business, you will discover an all new company as a one stop solution to ensure that your Applications are ubiquitous in all environments and systems the customer is present in.
Statistical Analysis based Web services on Big Data for Predictive Analysis
Our specialized services are related to BIG Data & Predictive Analysis based on Statistics, especially for Finance/Retail.
We write Web Services and automated the inflow of data and the process and flow on the Cloud by using existing Web Services or we write a series of Web Services, each reflecting a Statistical Analysis procedure or method. Some of the techniques have human/brain interpretation which is mapped for result, using cognitive Computing.
The Application of these techniques are in various domains, like CAPM modeling of Stock prices, Sub-prime lending risks, predicting/comparing Sales Data for Retail in geographical domains, archeological studies on Bone Density, Call Center customer profiling, Etc.
We are looking at Finance/Retail Markets and identify either generic or niche services.
We use Algorithms and process flows to analyze the Data real time and based on one/two/more Samples for the Population.
We estimate the Hypothesis of the mean values expected or the difference of mean values expected using Test Statistics and map it against Critical Values and calculate a Confidence Interval. This permits to do Predictive Analysis if to Accept or Do Not Accept the Hypothesis and accept the Alternatives. There are several techniques to estimate the Estimated or Expected results (based on Correlations) based on one/two/more Sample data and it will depend on the nature of data, like if it is Quantitative or Qualitative as well as if the data is Independent or Paired. Further there are techniques to test to see if we are analyzing tolerance levels on the same data.
Further analysis incorporates Regression and extend the study by introducing Dummy Variables to the Categorical Predictors and are extended to several groups. The Predicted Results (based on Trend Lines) IS further assessed for Residual Error for Independence and Variance and map via transformation in case the Trend Line is not straight.