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Google: Professional Cloud Data Engineer

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This skill path covers all the objectives needed to be a Data Engineer on Google Cloud. You will learn in depth how to use the products and services as well as how to complete the most common tasks with your Data in GCP. Although this path aligns with the topics for the GCP Cloud Data Engineer Professional exam. It is not a cert exam prep course. This is a path to teach the practical on the job skills for Data on GCP.

What You'll Learn

  • Dataproc
  • Dataflow and Apache Bean
  • GCP Pub/Sub
  • BigQuery
  • GCP Cloud SQL
  • GCP Cloud Spanner
  • Cloud Datastore
  • Frestore
  • BigTable
  • Datalab
  • ML Engine
  • Machine Learning APIs
  • Data Architecture on GCP
  • OpenCourser is an affiliate partner of Pluralsight and may earn a commission when you buy through our links.

    From Pluralsight
    Hours 36
    Instructors Janani Ravi, Vitthal Srinivasan
    Language English
    Subjects IT & Networking

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    Careers

    An overview of related careers and their average salaries in the US. Bars indicate income percentile (33rd - 99th).

    Data Engineer (eDiscovery) $67k

    Product Data Engineer $92k

    Data Networking Engineer. $96k

    Data Networking Engineer $101k

    Staff Data Engineer 2 $105k

    Data Communication Engineer 4 $111k

    Voice and Data Engineer $111k

    Data Modeling Engineer $112k

    Data Integration Engineer| Data Warehouse $116k

    Engineer - Data Services $120k

    Software Engineer/Data Engineer $187k

    Data Engineer/Developer $201k

    Courses in this Paths

    Listed in the order in which they should be taken

    Starts Course Information

    On Demand

    Architecting Big Data Solutions Using Google Dataproc

    When organizations plan their move to the Google Cloud Platform, Dataproc offers the same features but with additional powerful paradigms such as separation of compute and...

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    On Demand

    Architecting Serverless Big Data Solutions Using Google Dataflow

    Dataflow allows developers to process and transform data using easy, intuitive APIs. Dataflow is built on the Apache Beam architecture and unifies batch as well as stream...

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    On Demand

    Building Pipelines for Workflow Orchestration Using Google Composer

    Cloud Composer is a pipeline orchestration service on the GCP. Based on the Apache Airflow API, Composer was launched in May 2018 and is fast-emerging as a popular and versatile...

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    On Demand

    Architecting Data Warehousing Solutions Using Google BigQuery

    Organizations store massive amounts of data that gets collated from a wide variety of sources. BigQuery supports fast querying at a petabyte scale, with serverless functionality...

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    On Demand

    Architecting Stream Processing Solutions Using Google Cloud Pub/Sub

    As data warehousing and analytics become more and more integrated into the business models of companies, the need for real-time analytics and data processing has grown. Stream...

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    On Demand

    Building Machine Learning Models in SQL Using BigQuery ML

    This course demonstrates how to build and train machine learning models for linear and logistic regression using SQL commands on BigQuery, the Google Cloud Platform’s serverless...

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    On Demand

    Creating and Administering Google Cloud SQL Instances

    An important component of an organization's on-premises solution is the relational database. Cloud SQL is an RDBMS offering on the GCP which makes the operational and...

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    On Demand

    Architecting Big Data Solutions Using Google Bigtable

    Bigtable is Google’s proprietary storage service that offers extremely fast read and write speeds. It uses a sophisticated internal architecture which learns access patterns and...

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    On Demand

    Designing and Implementing Solutions Using Google Machine Learning APIs

    The Google Cloud Platform makes a wide range of machine learning (ML) services available as a part of Google Cloud AI. Google Cloud Machine Learning APIs are the most accessible...

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    On Demand

    Designing and Implementing Solutions Using Google Cloud AutoML

    Most organizations want to harness the power of machine learning in order to improve their products, but they may not always have the expertise available in-house. In this course,...

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    On Demand

    Creating and Administering Google Cloud Spanner Instances

    Relational Databases have traditionally relied on vertical scaling, but Google’s Cloud Spanner is carefully architected to provide horizontal scaling and global replication with...

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    On Demand

    Architecting Schemaless Scalable NoSQL Databases Using Google Datastore (You were viewing this course)

    A suite of big data technologies is considered incomplete unless it includes a solution optimized for document-oriented data and hierarchical queries, and that can provide the...

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    On Demand

    Leveraging Fully Managed Redis Datastores Using Google Cloud Memorystore

    Due to its in-memory nature, Memorystore features some of the lowest latencies on the platform, down to sub-millisecond levels. This managed-Redis service is hosted on Google’s...

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    On Demand

    Leveraging Google Cloud Firestore for Realtime Database Solutions

    Cloud Firestore is a flexible, scalable, realtime database where users can be notified when data changes in the cloud. Cloud Firestore is often used for mobile and web...

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    On Demand

    Architecting Scalable Web Applications with Firebase on the Google Cloud Platform

    Firebase is Google’s comprehensive mobile and app development platform which has features and integrations with the Google Cloud Platform which allow developers to build...

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    On Demand

    Developing on the Google Cloud Using Datalab and Cloud Source Repositories

    At the core of cloud development is a thorough knowledge of Cloud Source Repositories. In this course, Developing on the Google Cloud Using Datalab and Cloud Source Repositories,...

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    On Demand

    Architecting Production-ready ML Models Using Google Cloud ML Engine

    Building machine learning models using Python and a machine learning framework is the first step towards building an enterprise-grade ML architecture, but two key challenges...

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    On Demand

    Designing Scalable Data Architectures on the Google Cloud

    The Google Cloud Platform offers up a very large number of services, for every important aspect of public cloud computing. This array of services and choices can often seem...

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    Pluralsight

    From Pluralsight
    Hours 36
    Instructors Janani Ravi, Vitthal Srinivasan
    Language English
    Subjects IT & Networking

    Careers

    An overview of related careers and their average salaries in the US. Bars indicate income percentile (33rd - 99th).

    Data Engineer (eDiscovery) $67k

    Product Data Engineer $92k

    Data Networking Engineer. $96k

    Data Networking Engineer $101k

    Staff Data Engineer 2 $105k

    Data Communication Engineer 4 $111k

    Voice and Data Engineer $111k

    Data Modeling Engineer $112k

    Data Integration Engineer| Data Warehouse $116k

    Engineer - Data Services $120k

    Software Engineer/Data Engineer $187k

    Data Engineer/Developer $201k

    Similar Courses

    Sorted by relevance