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Background Modern Data Engineering involves creating and maintaining software and systems for accessing, processing, enriching, cleaning data and orchestrating data analysis for business purposes. Data engineers build tools, infrastructure, frameworks, and services....
Background The availability of petabytes scale of structured and unstructured data has lent itself for large-scale harnessing thanks to Data Science and AI. Advances in parallel and distributed computing, and the algorithms to process data of all types including text,...
Background Organisations of all types – be it for-profit, not-for-profit, or Governmental – have all been shaken by the pandemic for over a year now. The need to be in constant touch with the end-users or customers, as well as the key service delivery agents or...
Background The success of a BI and Analytics system or platform is characterised by how well it has been architected and built, by considering a variety of factors. Some of these are listed below: Data access: Does it account for volume, variety, velocity, veracity...
Background Business intelligence (BI) is an umbrella term that combines architectures, tools, databases, analytical tools, applications, and methodologies. It was coined first by Gartner group in the 1990’s. It is a content-free expression, so it means different...
Background The application of mathematical methods and computer science techniques coupled with statistical modelling on industrial data has been around for several decades. However, in their new avatars of Data science and Machine learning, they seem to have garnered...
