Big Data Analytics

Simple Definition for Beginners

Big data analytics is the process of examining large and complex sets of data to identify hidden patterns, trends, and insights that can help businesses make better decisions.

Common Use Example

A retail company uses big data analytics to study customer purchase histories and preferences. This helps them to personalize marketing campaigns and improve product recommendations, leading to increased sales and customer satisfaction. (Check comparison table below on Big Data Analytics vs AI)

Technical Definition for Professionals

Big data analytics involves advanced analytical techniques to process and analyze large volumes of diverse data to extract actionable insights. This process leverages tools and technologies such as Hadoop, Spark, NoSQL databases, and machine learning algorithms to handle data characterized by the three Vs (Volume, Velocity, Variety). Big data analytics encompasses several types of analytics, including descriptive (what happened), diagnostic (why it happened), predictive (what will happen), and prescriptive (what should be done). By applying these techniques, organizations can uncover hidden patterns, correlations, and insights that drive informed decision-making and strategic planning.