Fatih Nayebi

A Guide to Statistical Experimentation and Testing in Soccer (real football) Analytics

/ By / 9 minutes of reading

Introduction Welcome to the comprehensive guide designed for data scientists eager to master statistical testing and experimentation, specifically applied to soccer, real football 🙂 analytics. This article will guide you through a variety of statistical concepts and techniques, from basic hypothesis testing to complex multivariate analyses. By using real-world soccer data, we’ll explore how statistical […]

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Empowering Enterprise Data Science: Integrating Agile, Product Management, and Design Thinking for Strategic Success

/ By / 4 minutes of reading

Introduction The evolving landscape of data science within the enterprise setting demands a multifaceted approach that encompasses agile methodologies, product management, and design thinking, all tailored to foster innovation and drive business outcomes effectively. This article, in Demystifying Enterprise AI Strategy Series, delves into these critical areas, offering insights and strategies for integrating enterprise data

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Agile Data Governance in Enterprise AI: A Strategic Blueprint

/ By / 12 minutes of reading

Introduction: Steering Through the Data Revolution In today’s data-centric business landscape, Agile Data Governance is indispensable. This article, part of the “Enterprise AI Strategy” series, explores the multifaceted world of data governance and management, underscoring its critical role in navigating the complexities of digital transformation. Unraveling Data Governance Data Governance stands at the forefront of

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Developing a Robust Data Strategy: Navigating the Digital Era

/ By / 12 minutes of reading

Introduction In today’s digital epoch, data reigns as the undisputed currency of business. This transformation has not merely shifted strategies but revolutionized the very essence of decision-making. In the continuation of our “Demystifying Enterprise AI Strategy” series, we unravel how a robust data strategy aligns with overarching business goals to harness data’s true potential for

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Data as a Business: The Core of Modern Business Innovation

/ By / 10 minutes of reading

Introduction In the digital transformation era, data has evolved from a passive byproduct of business activities to a dynamic, strategic asset. This comprehensive exploration, part of the “Demystifying Enterprise AI Strategy” series, delves into the multifaceted concept of ‘Data as a Business & Data as a Product,’ examining its role as a transformative force in

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Demystifying Enterprise AI Strategy: An In-Depth Series Introduction

/ By / 2 minutes of reading

Introduction In a world increasingly driven by data, the importance of an astute Enterprise AI Strategy is undeniable. As we stand at the cusp of a new era in business intelligence, the need for comprehensive understanding and application of AI and data science in business has never been more critical. This introductory article marks the

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OpenAI’s Assistants API for Business

/ By / 3 minutes of reading

Embracing the Future of AI in Business The landscape of business technology is undergoing a seismic shift, thanks to innovations like OpenAI’s Assistants API. This groundbreaking tool is not just a technological advancement; it’s a gateway to new possibilities in customer interaction, process automation, and decision-making. Transforming Interactions: The Power of the Assistants API At

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Leveraging LLMs in Data Science Lifecycle for Demand Forecasting

/ By / 49 minutes of reading

Introduction In the bustling marketplace of modern commerce, navigating the complex currents of demand and supply is akin to a sailor maneuvering through tempestuous seas. The ability to foresee the ebbs and flows of market demand is a lighthouse that guides enterprises safely towards the shores of profitability. However, the lens through which this lighthouse

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Maximizing business value through effective Machine Learning data strategies

/ By / 8 minutes of reading

I would like to highlight the critical role that high-quality data plays in the success of Machine Learning (ML) initiatives. The key to unlocking the full potential of ML applications lies in establishing a continuous cycle of data improvement and model enhancement. High-quality, consistent data is the foundation for building robust ML models that generate

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A Hypothetical Revenue Management System for Retail & Supply Chain Management

/ By / 8 minutes of reading

Theory Revenue management is the practice of optimizing pricing and inventory in order to maximize profits. In the retail and supply chain industry, effective revenue management can be the difference between success and failure. In this blog post, we will discuss a hypothetical revenue management system that can be used to optimize pricing and inventory

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