Predictive Analytics is a tool capturing processes of data mining in simple routines.
Often referred to as “one-click data mining,” predictive analysis simplifies and automates the process of data mining.
What is prediction algorithm?
Predictive analytics builds profiles, discovers factors leading to certain outcomes, predicts the most likely outcomes, and establishes a degree of predictive trust.
Predictive analytics uses data mining techniques, but the use of predictive analytics does not involve knowledge of data mining.
Predictive big data analytics (PBA) is considered as a data-driven technology that can analyze large-scale data to discover patterns, uncover opportunities and predict outcomes. PBA uses machine learning algorithms that analyze the present and previous data to predict future events (Anagnostopoulos, 2016). Sun et al., 2017, Geneves et al., 2018 indicated that machine learning is a business intelligence tool for predictive analytics to extract valuable information from massive data for a more ambitious effort.
– Myat Cho Mon Oo, Thandar Thein
Simply define an operation to perform on your data, you can use predictive analytics.
How Does Predictive Analytics Work?
Input data are analyzed by predictive analytics routines and mining models are created.
These models are tested and trained to generate the results returned to the user. Upon completion of the project, the models and supporting items are not maintained.
You create a model or use a model generated by someone else when using data mining technology directly.
You usually apply the model to new data (as opposed to the data used to train and check the model). Routines in predictive analytics apply the model to the same data used for training and testing.