Data analysis is the term given to the process of trying to gain insightful information from data sets. This can involve sorting the data, modeling it, and attempting to organize it. Data mining is a branch of data analysis that refers to the process of looking for patterns and anomalies in data sets with the aim of predicting future events. Data visualization is a technique often used in data analysis to make it easier to comprehend. It involves making visual representations of data sets, such as graphs and charts.
But where does machine learning come into all this?
Machine learning is strongly linked to all three of these branches of data science because it gives data scientists a way of working with enormous sets of data that would be completely infeasible for a human alone to do. By ‘feeding’ machine learning algorithms with data we can make sense of far greater amounts of raw information, leading to more reliable insights and predictions.
As with all types of computer and data science, these three fields have all experienced massive advancements in the last couple of decades and they continue to grow in both accuracy and number of applications.