The Data Lakehouse Revolution

Harnessing the Power of Databricks for Generative AI and Machine Learning

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Paru le : 2025-10-31

We are racing toward a new kind of AI—faster, smarter, and more connected than ever. At the heart of it is the Data Lakehouse, and Databricks is the engine powering the transformation. Whether you're a data scientist training models, an engineer scaling pipelines, or an architect modernizing y...
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Éditeur

Collection
n.c

Parution
2025-10-31

Pages
451 pages

EAN papier
9798868817205

Auteur(s) du livre


Rajaniesh Kaushikk didn't just grow into a data and AI leader—he's been building, learning, and teaching since the days when "cloud" only meant the weather. During the past 23 years, he has helped global teams harness the power of Generative AI, machine learning, data lakehouse platforms, and Apache Spark to turn complex challenges into scalable, intelligent solutions. He thrives at the intersection of technology, creativity, and community—where ideas are shared, innovations are built, and people grow. Rajaniesh has received Most Valuable Professional awards from both Microsoft and Databricks, along with the distinction of Databricks Champion—honors that reflect his deep commitment to sharing knowledge and driving meaningful impact in the field. He's a sought-after speaker at Microsoft and Databricks, regularly connecting with learners around the globe through his blog at RajanieshKaushikk.com and his YouTube channel @RajanieshKaushikk, where he breaks down complex topics into practical, accessible insights. Outside of technology, Rajaniesh finds joy in cooking, listening to music, and spending time with his wife, daughter, and their ever-curious dog. For Rajaniesh, technology isn't just a profession—it's a means to connect, create, and inspire the next generation of builders.

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EAN PDF
9798868817212
Prix
62,11 €
Nombre pages copiables
4
Nombre pages imprimables
45
Taille du fichier
15391 Ko
EAN EPUB
9798868817212
Prix
62,11 €
Nombre pages copiables
4
Nombre pages imprimables
45
Taille du fichier
3768 Ko

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