What is Advanced Analytics?
Advanced analytics leverages sophisticated autonomous and semi-autonomous tools to evaluate large datasets of real-time and historical information. These tools—including artificial intelligence and machine learning algorithms—can process both structured and unstructured data, though text-based unstructured data typically requires preprocessing through text mining before becoming actionable.
Why it matters
Advanced analytics represents the evolution from retrospective reporting toward forward-looking recommendations, giving organizations the ability to anticipate outcomes rather than just explain what already happened.
See how Diwo operationalizes Advanced Analytics.
Read the decision-intelligence playbooks that put this concept to work at Fortune 50 scale.
Related concepts
Descriptive analytics is a type of data analytics that looks at past data to help companies understand what has happened to date. Unlike other analytical approaches, it focuses exclusively on historical insights rather than making predictions or drawing inferences. Results are presented through reports, dashboards, bar charts, and other visual formats designed for easy interpretation.
Predictive analytics employs data, statistical algorithms, and machine learning to assess the likelihood of future outcomes using historical information. Rather than merely documenting past events, it forecasts what will occur next, enabling executives and managers to adopt proactive, data-informed business strategies.
Data analytics is the systemic computational analysis of data. It is used for the discovery, interpretation and communication of meaningful patterns in data. The discipline also encompasses applying discovered data patterns to inform effective business decision-making.
Machine learning represents a data analytics approach that harnesses artificial intelligence to emulate human learning from experience. Rather than depending on preset formulas, machine learning algorithms extract "knowledge" directly from data through computational methods. These algorithms identify inherent patterns within datasets that generate actionable insights and support improved forecasting and decision-making.
