What is Data Analytics?
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.
Why it matters
Organizations leverage data analytics to extract actionable insights from large, heterogeneous datasets—a capability enhanced by modern parallel processing technologies and affordable computational infrastructure. Within a Decision Intelligence platform, analytics findings translate into accelerated business outcomes through improved decision velocity.
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Related concepts
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.
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.
Business intelligence (BI) is an umbrella term for the processes, technologies and strategies used to analyze and present insights derived from data, including everything from simple spreadsheets and graphs to customer satisfaction survey results and resources that make data usable. The primary objective is helping organizations make better and faster decisions.