What is Generative AI?

1
Introduction

• Data Analytics has always been about finding
  patterns and insights.

• 2025 marks a major shift with Generative AI
  powering advanced analytics.

• From static dashboards to AI-driven narratives
  and predictions.

2
What is Generative AI?
A subset of AI that can create new content text,
images, code, and data.
Tools ChatGPT, Google Gemini, Claude, DALLE.
In data analytics, it generates
Automated insights
Data visualizations
Predictive models
3
Why is Generative AI a Game-Changer in Analytics?

• Speed Rapid data interpretation.

• Scalability Handles massive datasets
  effortlessly.

• Personalization Delivers tailored insights.

• Accessibility Non-technical users can interact
  with data through natural language.

4
Real-World Applications

• Business Intelligence Auto-generated dashboards.

• Marketing Analytics Customer behavior
  predictions.

• Healthcare AI-assisted diagnostics from patient
  data.

• Finance Fraud detection and risk modeling.

5
BENEFITS FOR BUSINESSES

• Faster decision-making.

• Reduced dependency on data specialists.

• Enhanced data storytelling for stakeholders.

• Democratization of data access.

6
CHALLENGES RISKS

• Data privacy concerns.

• Over-reliance on AI without human oversight.

• Ethical use of generated insights.

• Model bias and inaccuracies.

7
FUTURE TRENDS

• Integration with IoT and Edge computing.

• AI-powered data governance.

• Conversational analytics with virtual data
  assistants.

• Rise of "Citizen Data Scientists.

8
Conclusion

• Generative AI is redefining data analytics.

• Companies embracing this trend gain competitive
  advantages.

• The future is a blend of human expertise and
  AI-powered insights.

9
THANK YOU