42821 Data Analytics Foundations2cp
Anti-requisite(s): 31250 Introduction to Data Analytics AND 32130 Fundamentals of Data Analytics
Data analytics is the art and science of turning large quantities of usually incomprehensible data into meaningful and commercially valuable information. It is the basis of modern computer analytics and intelligence. It includes a number of IT areas, such as statistical methods for identifying patterns in data and making inferences; database technologies for managing the data sets to be mined; a range of intelligent technologies that derive automatically patterns from data; and visualisation and other multimedia techniques that support human pattern discovery capabilities.
Data Analytics Foundations introduces learners to the significance and language of data analytics for business and society and the most common approach to data mining called cross-industry standard process for data mining, known as CRISP-DM. This microcredential offers practice in the foundations of data analytics; identifying data set types and attribute types, data preparation and cluster analysis. Advanced techniques for clustering develop skills in identifying problems for cluster analysis and a range of approaches to address these limitations. Applying these data analytics techniques enables interpretation of a data set and visual data exploration.
Detailed subject description.