Business Intelligence and Data Science are processes involving big data but have different aims and objectives. Business intelligence focuses on the research and analysis of past events and trends to make better decisions in the future. On the other hand, data science uses data to make predictions about future trends. Therefore, business intelligence is more focused on historical data, while data science is more concerned with making predictions. As a result, business intelligence is better suited for making decisions about what has happened in the past. At the same time, data science is more helpful in deciding what will happen in the future.
There exist some significant distinctions between the two. First, while data science seeks to forecast future patterns, business intelligence focuses on examining the past.
Second, comparatively speaking, data science demands a more technical skill set than business intelligence. While data science employs statistical modeling and machine learning to anticipate future trends, business intelligence primarily produces reports and insights from historical data.
Third, business intelligence analysts need a basic understanding of SQL; however, data scientists must be knowledgeable in programming languages and database technologies. Finally, business intelligence projects typically have shorter schedules and lesser expenditures compared to data science endeavors.
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