Data Science

Language, speech, are data, everything can be represented as data. Our researches in data allow our development team to create data science tools, which could be used in big data analysis, predictions, projections. No matter what format the data is, audio speech, video, texts, figures, our tools will dig deep inside, and discover the hidden patterns, insights, trends, and values.

Research Paper

Model and experimental development for Business Data Science

Russell Newman, Victor Chang, Robert John Walters, Gary Brian Wills, Apr. 2016
  ​​While Data Science has become increasingly significant for business strategies, operations, performance, efficiency and prediction, there is little work on this to provide a detailed guideline. We have proposed a Business Data Science (BDS) model that focuses on the model and experimental development that allows different types of functions, processes and roles to work together collaboratively for efficiency and performance improvements. Details with examples have been illustrated to show that BDS model can be a robust model. Future directions have been discussed to ensure that business intelligence, security, analytics and research contributions to BDS can be achieved.

A review and future direction of agile, business intelligence, analytics and data science

Deanne Larson, Victor Chang, Apr. 2016
  Agile methodologies were introduced in 2001. Since this time, practitioners have applied Agile methodologies to many delivery disciplines. This article explores the application of Agile methodologies and principles to business intelligence delivery and how Agile has changed with the evolution of business intelligence. Business intelligence has evolved because the amount of data generated through the internet and smart devices has grown exponentially altering how organizations and individuals use information. The practice of business intelligence delivery with an Agile methodology has matured; however, business intelligence has evolved altering the use of Agile principles and practices. The Big Data phenomenon, the volume, variety, and velocity of data, has impacted business intelligence and the use of information. New trends such as fast analytics and data science have emerged as part of business intelligence. This paper addresses how Agile principles and practices have evolved with business intelligence, as well as its challenges and future directions.