English | 2022 | ISBN: ‎ 1800561326 | 440 pages | True PDF EPUB | 28.71 MB

Build and deploy your own data pipelines on GCP, make key architectural decisions, and gain the confidence to boost your career as a data eeer

Key Features

Understand data eeering concepts, the role of a data eeer, 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 Eeer exam

Book Description

With this book, you'll understand how the highly scalable Google Cloud Platform (GCP) enables data eeers 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 eeering, you'll learn the various responsibilities of a data eeer 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 eeer, take the Professional Data Eeer certification exam, and get ready to become an expert in data eeering with GCP.

By the end of this data eeering book, you'll have developed the skills to perform core data eeering 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

Develop Airflow jobs to orchestrate and automate a data warehouse

Build a Hadoop data lake, create ephemeral clusters, and run jobs on the Dataproc cluster

Leverage Pub/Sub for messaging and ingestion for event-driven systems

Use Dataflow to perform ETL on streaming data

Unlock the power of your data with Data Studio

Calculate the GCP cost estimation for your end-to-end data solutions

Who this book is for

This book is for data eeers, data analysts, and anyone looking to design and manage data processing pipelines using GCP. You'll find this book useful if you are preparing to take Google's Professional Data Eeer exam. Bner-level understanding of data science, the Python programming language, and Linux commands is necessary. A basic understanding of data processing and cloud computing, in general, will help you make the most out of this book.

Table of Contents

Fundamentals of Data Eeering

Big Data Capabilities on GCP

Building a Data Warehouse in BigQuery

Building Orchestration for Batch Data Loading Using Cloud Composer

Building a Data Lake Using Dataproc

Processing Streaming Data with Pub/Sub and Dataflow

Visualizing Data for Making Data-Driven Decisions with Data Studio

Building Machine Learning Solutions on Google Cloud Platform

User and Project Management in GCP

Cost Strategy in GCP

D on Google Cloud Platform for Data Eeers

Boosting Your Confidence as a Data Eeer