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AI DATA CLOUDFUNDAMENTALS

Learn about some of the most relevant topics around cloud data warehousing, AI, data lakes, data engineering and other areas of interest related to cloud data analytics, AI and cloud data platforms.

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What Is a Feature Store in Machine Learning?

Feature stores are becoming essential to machine learning success, acting as centralized hubs for storing and managing the features that power AI models. By enabling feature reuse, ensuring consistency across training and inference, and streamlining data governance, feature stores help teams deploy ML pipelines faster and with greater accuracy
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What Is an Enterprise Data Warehouse (EDW)? Benefits & Components

An enterprise data warehouse (EDW) unifies data from across an organization into a single, centralized platform—enabling cross-functional teams to access, analyze, and act on trusted business data to drive smarter decisions, operational efficiency, and strategic growth.
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Regression Models in ML: Examples & Use Cases

Regression models in machine learning help organizations predict continuous outcomes by uncovering the relationships between variables, powering everything from sales forecasting to risk assessment and predictive maintenance.
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What is Data Modeling? A Complete Guide

Data modeling is the foundation of effective data architecture, enabling organizations to visualize relationships, structure systems, and improve data quality for better decision-making and streamlined software development.
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OLAP Cubes in Business Intelligence: A Complete Guide

OLAP cubes are foundational tools for exploring multidimensional data, enabling fast, flexible analysis across key business dimensions like time, geography, or product. While cloud data warehouses have evolved beyond traditional OLAP cube requirements, the concept remains central to advanced analytics and decision support.
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LLM Inference: Optimization Techniques and Performance Metrics

LLM inference is the engine behind generative AI's ability to produce human-like responses. Understanding how large language models process prompts, generate tokens, and optimize for performance is critical for building fast, accurate, and scalable AI applications.
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AI Programming Languages for Modern AI Software Development

Artificial intelligence (AI) development requires more than just picking the right programming language. It involves assembling the right data, compute resources, frameworks, and tools to build scalable, production-ready systems.
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A Complete Guide to Python for Data Engineering

Python for data engineering empowers teams to build scalable pipelines, automate data workflows, and unlock faster insights by combining simplicity with a rich ecosystem of powerful libraries and tools.
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A Guide to AI Models: What They Are and How They Work

Artificial intelligence (AI) is transforming how businesses operate, enabling faster decisions, deeper insights, and scalable automation. This guide breaks down what AI models are, how they differ from machine learning (ML) and deep learning (DL), and how leading companies are applying them to drive real results.
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How Artificial Intelligence Is Revolutionizing Advertising

Artificial intelligence is reshaping advertising by enabling smarter targeting, faster content creation, and more efficient campaign optimization. With AI-driven tools, marketers can personalize experiences at scale and make data-backed decisions that improve performance across channels.
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AI in Business: Impact, Benefits, and Use Cases

Artificial intelligence is transforming how businesses operate by automating tasks, improving decisions, and uncovering new opportunities. As adoption grows, AI is becoming a core driver of innovation and competitive advantage across industries.
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Understanding structured, semi-structured and unstructured data

Explore the fundamental differences between structured, semi-structured and unstructured data, and how to process, store and analyze these types efficiently.
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