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  3. Big Data Services on Microsoft Azure
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Big Data Services on Microsoft Azure

This course also explains data transformation activities in Azure Data Factory that you can use to transform and processes your raw data into predictions and insights.

Praba Santhanakrishnan
Praba Santhanakrishnan
Data Science | core | 5 minutes | Apr 29 | 12:39 PM Eastern (USA)

Overview

2.8KSTUDENTS*
95.2%RECOMMEND*

This course includes:

  • 1 hours of on-demand video
  • 2 modules
  • Core level
  • Direct access/chat with the instructor
  • 100% self-paced online
  • Many downloadable resources
  • Shareable certificate of completion
More and more businesses are realizing the power of data and taking on the challenge of analyzing big data to gain deeper insights that gives the competitive advantage in their services and offerings to win more customers and to retain the existing ones. The data is volume is huge and available in multiple variety of formats ranging from structured , unstructured and semi structured and at comes at different velocity  This webinar is an introduction that exposes you to the various techniques available in Microsoft Azure data services and how to work with Azure Technologies like Azure Data Factory, Datalake, Azure Data Warehouse etc. This course also explains data transformation activities in Azure Data Factory that you can use to transform and processes your raw data into predictions and insights. A transformation activity executes in a computing environment such as Azure HDInsight cluster or an Azure Batch.

Skills You Will Gain

Azure Data Factory
Azure HDInsight cluster
Data Warehouse
Datalake

Learning Outcomes (At the end of this program you will be able to)

  • Data ingestion from different sources to Azure Data Lake, using Azure Data Factory.
  • Create data transformation pipelines using Hive and Spark.
  • Processing big data using spark SQL using Scala and deploying and executing on Azure HDInsight spark cluster.

Prerequisites

Who Should Attend

  • Anyone interested in cloud technologies and computing, and interested in Azure, in particular.

Instructors

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*Where courses have been offered multiple times, the “# Students” includes all students who have enrolled. The “%Recommended” shown is also based on this data.
Praba Santhanakrishnan

Praba Santhanakrishnan

With a profound background in Artificial Intelligence and Machine Learning, I bring over two decades of experience from the tech industry to my role as an educator. My journey began with a Bachelor’s degree in Electrical, Electronics, and Communications Engineering, followed by a Master’s in Machine Learning from the University of California, Berkeley. My career includes significant contributions to Microsoft, where I led advancements in cloud migration and developed state-of-the-art NLP systems. I've also co-founded several innovative tech ventures, including Cookr, which harnesses AI to transform the food tech industry. My passion lies in demystifying complex algorithms and data science concepts, making them accessible and practical for students. I specialize in teaching Python, Spark, and advanced machine learning algorithms, focusing on real-world applications that drive meaningful insights and solutions. Throughout my career, I have been committed to bridging the gap between theoretical knowledge and practical implementation, preparing the next generation of data scientists and technologists for the challenges of the digital age. As an educator, I am dedicated to fostering an environment of curiosity and innovation. I enjoy sharing my expertise in data science and AI, drawing from my extensive experience in both academia and industry. My teaching philosophy revolves around practical problem-solving and hands-on learning, ensuring that students not only grasp theoretical concepts but also apply them effectively in real-world scenarios.
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