Diferencias entre el Big Data, Business Analytics y Business Intelligence 🤨

Summary

This video delves into the key differences between Big Data, Business Intelligence (BI), and Business Analytics (BA). While all three focus on data analysis for better decision-making, their approaches vary. BI analyzes historical data to optimize past decisions, BA looks to the future using predictive models to improve future strategies, and Big Data processes both structured and unstructured data for broader insights. The video explains the different purposes and tools used by each, as well as the distinct teams responsible for their implementation. It's a comprehensive guide for understanding how each contributes to data-driven business success.

Takeaways

• 😀 Big Data, Business Intelligence (BI), and Business Analytics (BA) all analyze data to help businesses make better decisions.
• 📊 Business Intelligence focuses on analyzing past data to identify patterns and trends in historical performance.
• 📈 Business Analytics uses structured data along with macroeconomic indicators to predict future trends and optimize decision-making.
• 🔍 Big Data is all about processing large volumes of structured and unstructured data to uncover hidden patterns.
• 📦 BI stores data in centralized servers, while Big Data relies on distributed file systems for data storage.
• 🕰️ BI is oriented toward historical analysis, whereas BA is focused on future forecasting and preventing future mistakes.
• ⚙️ Big Data involves data scientists, engineers, and other technical teams to manage data capture and processing.
• 💡 The main objective of BI is to correct past operational errors, while BA aims to predict future challenges and strategies.
• 🧠 BI and BA work with structured data, but Big Data can process both structured and unstructured data.
• 👥 BI teams typically consist of strategists and business experts, while Big Data teams are made up of technical specialists.
• 🎯 While BI and BA are more focused on decision-making, Big Data provides the raw data processing necessary for deeper insights.