Predictive analytics encompasses a variety of
statistical techniques from data mining, predictive
modelling, and machine learning, that analyze
current and historical facts to make predictions
about future or otherwise unknown events
In business, predictive models exploit patterns found in historical and transactional data to identify risks and opportunities.
Models capture relationships among many factors to allow assessment of risk or potential associated with a particular set of conditions, guiding decision-making for candidate transactions.
The defining functional effect of these technical approaches is that predictive analytics provides prediction score such as probabilities.
A predictive score for each individual in order to determine, inform, or influence organizational processes that pertain across large numbers of individuals, such as in marketing, credit risk assessment, fraud detection, manufacturing, healthcare, and government operations including law enforcement.
Software development is the process of conceiving, specifying, designing, programming, documenting, testing, and bug fixing involved in creating and maintaining applications, frameworks, or other software components.
Big data analytics is the often complex process of examining big data to uncover information -- such as hidden patterns, correlations, market trends and customer preferences -- that can help organizations make informed business decisions.
Data analytics technologies and techniques give organizations a way to analyze data sets and gather new information. Business intelligence (BI) queries answer basic questions about business operations and performance.
