Aspects Business Intelligence Data Analytics
Focus Monitoring business performance and making informed decisions Discovering patterns, trends, and insights in large, complex data sets
Scope Focused on providing specific information for decision-making Broad, encompassing exploratory data analysis, data visualization, and advanced statistical techniques
Techniques Dashboards, reports, visualizations Data mining, predictive modeling, machine learning, advanced statistical techniques
Time period Short-term, tactical view Long-term, strategic view
Audience Managers, executives, front-line employees, business users Analyst and data scientist
Complexity Designed to be accessible to a wider audience Deals with more complex data sets
Data sources Focuses on data from a single source Pulls data from multiple sources
Granularity Works at a higher level, aggregating data Works on a more granular level
Focus Answers specific business questions, provides insights for decision-making Answers open-ended questions, explores data to find patterns and insights
Data volume Deals with smaller volumes of data Deals with large volumes of data, such as big data
Technical skills Requires less specialized technical skills, focuses on data visualization, reporting Requires specialized technical skills such as data mining, machine learning, statistical analysis, programming
Goal Improve business performance and efficiency by providing timely and accurate information. Drive better business decisions by uncovering insights and opportunities in data.
Tools User-friendly tools such as Tableau, Power BI, Excel Tools such as R, Python, SQL