AEP : Adobe Analytics

The Two Main Disciplines:

• Business Analytics: Focuses on using data (including Big Data) to understand strategic risks and opportunities. It is a key part of Business Intelligence (BI). This is where the "four types" framework is applied.
• Data Analytics: A broader, more technical field concerned with the foundational work of sorting, storing, cleansing, and transforming massive datasets (the work of data scientists).

2. The Four Types of Business Analytics:
This is a maturity model for how organizations use data:

• Descriptive ("What happened?"): Uses historical data to identify trends.
• Diagnostic ("Why did it happen?"): Finds root causes and correlations behind outcomes.
• Predictive ("What might happen?"): Uses historical data and ML/AI to forecast future probabilities (e.g., customer churn).
• Prescriptive ("What should we do?"): An advanced form that uses ML/AI to recommend specific actions to achieve optimal outcomes (e.g., improving retail margins).

3. Adobe Analytics' Role:
Adobe Analytics is the platform that enables this entire workflow.

• It collects data from multi-channel customer journeys (web, mobile, CRM, offline, etc.).
• It provides the tools for analysis (like Analysis Workspace) where marketers perform descriptive and diagnostic analysis to "tell stories" with data.
• It generates actionable outputs (segments, predictive scores) that feed into predictive and prescriptive actions, such as personalization in Adobe Target or advanced attribution modeling.

Conclusion: Analytics is the practice of turning data into insights and actions. Business Analytics provides the strategic framework (the four types), and platforms like Adobe Analytics provide the technical capability to execute that framework from data collection to prescriptive action.