Components of a Modern Data Lake to Support Enterprise AI Applications - Penikalapati, Venkata Karthik;Kumar, Lav
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In a world where data is generated at an unprecedented rate, organizations face the challenge of moving beyond conventional databases to store, manage, and derive valuable insights from their data. Data lakes, with their dynamic capabilities, provide a scalable, flexible, and cost-effective solution for the storage and processing of extensive and diverse datasets. They form the cornerstone for AI and machine learning initiatives, serving as the fertile ground for the development, training, and deployment of advanced AI models. We will delve into the monumental importance of data lakes in the…mehr

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Produktbeschreibung
In a world where data is generated at an unprecedented rate, organizations face the challenge of moving beyond conventional databases to store, manage, and derive valuable insights from their data. Data lakes, with their dynamic capabilities, provide a scalable, flexible, and cost-effective solution for the storage and processing of extensive and diverse datasets. They form the cornerstone for AI and machine learning initiatives, serving as the fertile ground for the development, training, and deployment of advanced AI models. We will delve into the monumental importance of data lakes in the AI era and elucidate how they act as enablers for the transformation of raw data into actionable insights.
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Autorenporträt
Venkata Karthik Penikalapati ist ein erfahrener Softwareentwickler bei Salesforce mit mehr als einem Jahrzehnt Erfahrung in der Entwicklung und Verwaltung von Datenpipelines.Lav Kumar ist ein erfahrener Lead MTS bei Salesforce mit 12 Jahren Erfahrung in der Full-Stack-Entwicklung. Er ist ein leidenschaftlicher technischer Innovator, Dateningenieur und AI/ML-Enthusiast.