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Wednesday, 07 Oct @ 5:00 PM


This webinar will help you engineer a highly robust, scalable & efficient Data Lake solution using data services in the Google Cloud Platform. We will start with an overview of a data lake solution and then explore the various components of the solution including Batch & Streaming Analytics, Storage, Visualizations, etc.

In the second part of this series, we will go deeper to understand bigquery in detail; how it works, what are the best practises for higher performance and what all ETL tools are available to ingest & transform data in bigquery.

This will be best suited for developers, data engineers, data analysts, data scientists and business analysts. In order to get maximum benifit, basic proficiency with common query language, such as SQL, experience with data modeling, extract, transform and load activities & experience developing applications using a common programming language, such as Python, is recommended.


Key points of discussion
  • BigQuery basics around storage & query
  • How to organise data in BigQuery and improve performance
  • Comparison of ETL tools available in GCP
Who should attend

Ios Developer,android developer,Software Developer,Applications Developer,Mobile Developer,Software Engineer,Backend Developer,Data Engineer,Data Scientist,Application Engineer,Software Test Engineer,Software Engineering Analyst,Big data,Hadoop,business analyst,data consultant,Data Analyst,IT Manager,IT Practitioner


Nitin Khattar

Customer EngineerGoogle Cloud

Nitin Khattar is a Data Analytics Specialist at Google Cloud. He is a data-enthusiast and polyglot programmer who enjoys making things out of code. Prior to Google, he led Data Engineering teams at Astro & Nextag. Most of his work has been around building Data Lake and Data Analytics platforms in a Hybrid environment


Webinar/Workshop organized by: TechGig

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