Prashanth Southekal
In recent months, particularly following the release of ChatGPT, there has been an unprecedented surge in interest surrounding artificial intelligence (AI). This heightened attention spans across a multitude of sectors, including business enterprises, technology companies, venture capital firms, universities, governments, media outlets, and more. As the interest in AI is intensifying, some companies have even rebranded their existing software solutions as “AI” products, a phenomenon often referred to as “AI washing.” Furthermore, there is also a growing sense of “FOMO” (Fear of Missing Out) among corporations regarding AI adoption.
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Prashanth Southekal
Delivering successful data analytics solutions that have a strong business impact is dependent on numerous factors such as culture, literacy, governance, technology, quality data, leadership and more. However, one key component that acts as a lynchpin in data analytics — i.e., the pivotal element that is the coherent source of support and stability is the key performance indicator (KPI). What is a KPI? Why does it hold such a significant position in data analytics? Finally, what can organizations do to design and build a robust KPI framework and deliver improved business performance from data analytics?
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Prashanth Southekal and Steve Rosvold
On Rapid Fire Prashanth responds to these questions:
- ⚪ How can data be a liability for a business?
- ⚫ What is the purpose of a data strategy?
- ⚪ Who should be at the center of our Data & Analytics initiatives?
- ⚫ What qualities are required to successfully apply Data & Analytics in your business?
- ⚪ What are the top 3 reason CFOs succeed in their Data & Analytics initiatives?
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Prashanth Southekal
I have been this question asked many times - Is JupyterLab recommended data analytics for FP&A (Financial Planning and Analysis) professionals? Should, a FP&A professional invest his or her time and resources in learning JupyterLab over Microsoft Excel for data analytics needs? This blog answers some critical questions the FP&A professionals have regarding JupyterLab. Let’s start with the fundamental concepts.
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Nathan Bell
The integration of artificial intelligence (AI) into corporate finance is no longer a futuristic concept; it’s a transformative reality reshaping how businesses manage and interpret financial data. This shift is not merely a fleeting trend but a profound evolution that promises to redefine the very essence of financial operations. In this article, we will explore the multifaceted benefits AI offers to corporate finance, the challenges companies may encounter during its integration, and the strategies CFOs, finance leaders, and executives can employ to navigate these hurdles and fully leverage AI’s capabilities.
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