Once the data is collected and appropriately stored, data analysts start using different analysis techniques, or types, to answer questions regarding the performance of their businesses.
Here are the main types of data analytics.
Descriptive analytics is usually the first type of data analytics to be implemented by analysts. It collects past data, and by analyzing them, it tells the analyst where the business has been and whether or not it has made the expected progress.
Descriptive analytics is subdivided into canned and en hoc reports.
Canned reports are created by business users or incorporated into business software. They regularly use and store real-time data regarding various aspects of the business like product performance and sales trends. And they are generally saved to be reused at various stages.
En hoc reports, however, are created to answer a question at the moment. They’re designed to be more concise and to the point, enabling departments or businesses to share them.
Diagnostic analytics is a more sophisticated technique usually done after descriptive analytics. It helps in discovering anomalies in past trends and finding the reasons behind these anomalies.
It’s further divided into two categories: discover and alerts, and query and drill-downs.
Discover and alerts serve to warn of a potential issue before it happens. Say a drop in employee work hours, for example, as this is expected to cause a reduction in productivity.
Query and drill-downs refer to techniques that dig deeper to find the root causes of a problem.
Predictive analytics uses historical and current data to forecast future outcomes depending on the trends discovered. This is invaluable to business owners as it can aid in highlighting future business opportunities and avoiding crises.
Predictive analytics is carried out by implementing artificial intelligence, data mining, machine learning, and predictive modeling and statistics.
Prescriptive analytics uses insights from predictive analytics to predict the outcomes of different business decisions.
This helps businesses know what’s expected to happen with every possible decision they make, which, in turn, helps them make well-informed business decisions.