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Data Engineering With Google Cloud Platform A Practical Guide To Operationalizing Scalable Data Analytics Systems On Gcp Wijaya

  • SKU: BELL-56136828
Data Engineering With Google Cloud Platform A Practical Guide To Operationalizing Scalable Data Analytics Systems On Gcp Wijaya
$ 31.00 $ 45.00 (-31%)

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Data Engineering With Google Cloud Platform A Practical Guide To Operationalizing Scalable Data Analytics Systems On Gcp Wijaya instant download after payment.

Publisher: Packt Publishing
File Extension: PDF
File size: 8.94 MB
Pages: 440
Author: Wijaya, Adi
ISBN: 9781800561328, 1800561326
Language: English
Year: 2022

Product desciption

Data Engineering With Google Cloud Platform A Practical Guide To Operationalizing Scalable Data Analytics Systems On Gcp Wijaya by Wijaya, Adi 9781800561328, 1800561326 instant download after payment.

Build and deploy your own data pipelines on GCP, make key architectural decisions, and gain the confidence to boost your career as a data engineer Key Features: Understand data engineering concepts, the role of a data engineer, and the benefits of using GCP for building your solution Learn how to use the various GCP products to ingest, consume, and transform data and orchestrate pipelines Discover tips to prepare for and pass the Professional Data Engineer exam Book Description: With this book, you'll understand how the highly scalable Google Cloud Platform (GCP) enables data engineers to create end-to-end data pipelines right from storing and processing data and workflow orchestration to presenting data through visualization dashboards. Starting with a quick overview of the fundamental concepts of data engineering, you'll learn the various responsibilities of a data engineer and how GCP plays a vital role in fulfilling those responsibilities. As you progress through the chapters, you'll be able to leverage GCP products to build a sample data warehouse using Cloud Storage and BigQuery and a data lake using Dataproc. The book gradually takes you through operations such as data ingestion, data cleansing, transformation, and integrating data with other sources. You'll learn how to design IAM for data governance, deploy ML pipelines with the Vertex AI, leverage pre-built GCP models as a service, and visualize data with Google Data Studio to build compelling reports. Finally, you'll find tips on how to boost your career as a data engineer, take the Professional Data Engineer certification exam, and get ready to become an expert in data engineering with GCP. By the end of this data engineering book, you'll have developed the skills to perform core data engineering tasks and build efficient ETL data pipelines with GCP. What You Will Learn: Load data into BigQuery and materialize its output for downstream consumption Build data pipeline orchestration using Cloud Composer De

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