Data analytics explained

Data analytics is the foundation of modern-day businesses. It arguably represents the only way to make accurate and data-driven decisions, thus helping you to maintain the highest level of business performance in the long run.

The concept of data analytics is complex and comprises of different analytical methodologies, but for purposes of this article we will touch on descriptive, diagnostic, predictive, and prescriptive analytics.

Descriptive analytics: Gathers and interprets historical data to better understand changes that have occurred in a business. Essentially, it searches and summarizes historical data to identify patterns or meaning.

Diagnostic analytics: Examines data or content to answer one simple question, “Why did it happen?”, by making use of techniques such as drill-down, data discovery, data mining and correlations.

Predictive analytics: Uses complex statistical techniques to make predictions based on the existing or historical facts and figures.

Prescriptive analytics: Makes use of machine learning to help businesses decide a course of action based on a computer program’s predictions. Prescriptive analytics works with predictive analytics, which uses data to determine near-term outcomes. Thereby providing you with real-time insights to help you to choose the best solution in any given situation.

If you correctly combine all four of these models, you can optimize business performance and take your business to a whole new level.


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