DataHour: Cloud Dataproc - Migrate and Optimize Spark Workloads

DataHour: Cloud Dataproc - Migrate and Optimize Spark Workloads

23 Jan 202313:01pm - 23 Jan 202314:01pm

DataHour: Cloud Dataproc - Migrate and Optimize Spark Workloads

About the Event

The Hadoop ecosystem is a widely adopted platform for solving big data problems. Implementing Hadoop is easy with big data tools like Apache Pig, Hive, Spark. However, with cost implications of required compute resources and advantages of cloud-based technologies, a lot more enterprises are moving their big data workloads to Cloud.

In this DataHour, Ritika will introduce you to Dataproc - fully managed and highly scalable service for running Apache Hadoop, Apache Spark, Apache Flink, Presto, and 30+ open source tools and frameworks. Dataproc can be used for data lake modernization, ETL and secure data science, at scale, integrated with Google Cloud, at a fraction of the cost. As a noob to Dataproc or Cloud, you get to accelerate your Google Cloud Journey by learning the most popular component for Spark workloads. As an experienced developer, you learn the best practices for migration and optimization of Spark Workloads.


Prerequisites: 
Interest in Data Science and Big Data.

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Who is this DataHour for?

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About the Speaker

Ritika Neema

Ritika Neema

Cloud Data Engineer at Google

Ritika is currently working as a Cloud Data Engineer at Google. She is experienced in building Data Orchestration and Integration Frameworks using Spark and Cloud technologies. She is a Google Certified and Microsoft Azure certified Data Engineer. She has previously worked with clients from various domains such as energy, telecom and fintech on building datalakes, ETL pipelines or validation frameworks or refining data for business decisions.

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