Big data analytics is the use of processes and technologies to combine and analyze massive datasets with the goal of identifying patterns and developing actionable insights. This helps business leaders make faster, better, data-driven decisions that can increase efficiency, revenue and profits.
The primary steps of big data analytics are goal definition, data collection, data integration and management, data analysis and sharing of findings. The advanced analytics involved in exploring and analyzing large volumes of semi-structured and unstructured data requires either an end-to-end big data analytics platform or a broad set of tools which are applied by data analysts, data scientists, or engineers.
Modern big data analytics involves the use of artificial intelligence (AI) and machine learning to automate processes, provide insight suggestions, perform predictive analytics and allow natural language interaction. Real-time big data analytics involves processing data as it arrives, which can further speed decision making or trigger actions or notifications.