Book Image

The Future of Finance with ChatGPT and Power BI

By : James Bryant, Aloke Mukherjee
2.5 (4)
Book Image

The Future of Finance with ChatGPT and Power BI

2.5 (4)
By: James Bryant, Aloke Mukherjee

Overview of this book

In today's rapidly evolving economic landscape, the combination of finance, analytics, and artificial intelligence (AI) heralds a new era of decision-making. Finance and data analytics along with AI can no longer be seen as separate disciplines and professionals have to be comfortable in both in order to be successful. This book combines finance concepts, visualizations through Power BI and the application of AI and ChatGPT to provide a more holistic perspective. After a brief introduction to finance and Power BI, you will begin with Tesla's data-driven financial tactics before moving to John Deere's AgTech strides, all through the lens of AI. Salesforce's adaptation to the AI revolution offers profound insights, while Moderna's navigation through the biotech frontier during the pandemic showcases the agility of AI-focused companies. Learn from Silicon Valley Bank's demise, and prepare for CrowdStrike's defensive maneuvers against cyber threats. With each chapter, you'll gain mastery over new investing ideas, Power BI tools, and integrate ChatGPT into your workflows. This book is an indispensable ally for anyone looking to thrive in the financial sector. By the end of this book, you'll be able to transform your approach to investing and trading by blending AI-driven analysis, data visualization, and real-world applications.
Table of Contents (13 chapters)
Free Chapter
1
Part 1: From Financial Fundamentals to Frontier Tech: Navigating the New Paradigms of Data, EVs, and AgTech
6
Part 2: Pioneers and Protectors: AI Transformations in Software, Finance, Biotech, and Cybersecurity

Python power play – fueling financial analysis with advanced code

In our detailed expedition, we will bring the illustrious Deere & Co to the spotlight. Armed with actual figures extracted from their April 30, 2023 10-Q report, we will use Python to compute ROIC. This calculation, which will be seamlessly handled by Python, entails dividing the net income by the total invested capital, resulting in a percentage form of ROIC.

However, while Python may be a powerful catalyst in financial analysis, remember that it thrives on accurate and current financial data. As we forge forward into this Python-powered financial analysis journey, it’s essential to bear in mind the importance of feeding reliable and up-to-date data into our Python engine. In the world of Python-empowered financial analysis, data integrity is as crucial as the calculations themselves.

So, get ready to dive into a captivating world where Python code and financial analysis intersect, sparking illuminating...