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Google Cloud Data Engineer Online Training

Google Cloud Certified professional Data Engineer has a great demand and highest value across the globe. This certification states the knowledge on data collection, transformation as well as the data visualization to generate useful insights.

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Course Overview

A Data Engineer is responsible to perform data analysis, and to expect the business outcomes to support the better decision making and build the machine learning models to simplify and automate the primary process of the business. ITGuru Google Cloud Data Engineer Certification training, makes you advance your career in Data Engineering and shows you the better way to become the Google Certified Data Engineer. This GCP Data Engineer Certification gives you hands-on experience on various Google Cloud operations. Hence this training will make you data-driven decision making through collecting, transforming as well as publishing data Moreover, you people can get practical knowledge on all these services on cloud platforms by real time experts with real world use cases through online. This Google Cloud Data Engineer Online Training India emphasizes the crucial aspects of the systems. This includes reliability, scalability, fault tolerance, security, efficiency as well as fidelity. Moreover, this Google Cloud Data Engineer Online Training Hyderabad, makes you prepare for Data Engineering on the Google Cloud platform. ITGuru has designed the syllabus in a way to get certified through frequent assignment according the recent syllabus

Google Cloud Data Engineer Online Training Objectives

  • Who can pursue GCP Data Engineer Certification Course?

    There is no such criteria to enroll into the GCP Data Engineer Certification Course. AnyOne with a basic degree can enroll in this course.

  • What are the prerequisites for Google Cloud Data Engineer Online Training?

    Since the Google Cloud training initiates with the scratch, there are no such prerequisites to enroll in this course. It's good, if the candidate has knowledge on Cloud Basics.

  • Why should you enroll for a Google Cloud Data Engineer online course?

    This Course was designed in such a way to clear certification. Hence this course will show the way to become a Google Cloud Certified Data Engineer.

  • What do you learn in Google Cloud Data Engineer Course?

    This Google Cloud Data Engineer Course will let you know the various services of the Google Cloud platform.

  • What are the benefits in learning Google Cloud Data Engineer online training?

    Since the Course was designed in a way to clear certification, this course will make you get hands-on experience on Google Cloud services by live experts with real world use cases.

Google Cloud Data Engineer Online Training Key Features

  • Lifetime Access

    You get lifetime access to the Learning Management System (LMS) where presentations, assignments, and installation guide on Google Cloud Data Engineer Training.

  • Assignments

    Trainers will assign some assignments soon after the completion of each and every topic that makes you master in the Google Cloud Data Engineer Course and also helps you to Google Cloud Data Engineer Certification.

  • Real-life Case Studies

    ITGuru trainers teach you each and every topic with real-world case studies that makes the learner understand in a better way

  • 24 x 7 Support

    We have 24x7 online support team to resolve all your queries

  • Certification

    IT Guru team has designed the Google Cloud Data Engineer Course in the way to clear Certification as per the latest syllabus to make your dream come true.

  • Job Assistance

    IT Guru supports learners in finding job opportunities with the newly acquired skill set. Online IT Guru has a varied bunch of Clientele around the globe, over 200+ companies in various countries like the USA and India. Soon after the completion of the course, the support team will pass your resumes to the companies and ensure that the learners will achieve 100% placements.

Google Cloud Data Engineer Online Certification Syllabus

  • Module 1
    • Introduction to Google Cloud
    • Compute Engine
    • App Engine
    • Networking and Security
    • GCP account online
  • Module 2
    • Identity Services
    • Cloud IAM
    • Provides administrators the ability to manage cloud resources centrally by controlling who can take what action on specific
    • Understand how IAM works and how rules apply esp. the hierarchy from Organization -> Folder -> Project -> Resources
    • Understand IAM Best practices
    • Make sure you know the Big Query Access roles
    • Storage Services
    • Understand each storage service options and their use cases.
    • Cloud Storage
    • cost-effective object storage for an unstructured
    • very important to know the different classes and their use cases esp. Regional and Multi-Regional (frequent access), Nearline (monthly access) and Coldline (yearly access)
    • Understand Signed URL to give temporary access and the users do not need to be GCP users
    • Understand permissions – IAM vs ACLs (fine grained control)
  • Module 3
    • Relational Databases
    • Know Cloud SQL and Cloud Spanner
    • Cloud SQL
    • is a fully-managed service that provides MySQL and PostgreSQL
    • Limited to 10TB and is a regional
    • Cloud Spanner
    • is a fully managed, mission-critical relational database
    • provides a scalable online transaction processing (OLTP) database with high availability and strong consistency at global
    • globally distributed and can scale and handle more than
    • not a direct replacement and would need migration
    • There are no direct options for Microsoft SQL Server or Oracle
    • NoSQL
    • Know Cloud Datastore and BigTable
    • Datastore
    • provides document database for web and mobile
    • Datastore is not for analytics
    • Understand Datastore indexes and how to update indexes for Datastore
    • Bigtable
    • provides column database suitable for both low-latency single-point lookups and precalculated analytics
    • understand Bigtable is not for long term storage as it is quite expensive
    • know the differences with HBase
    • Know how to measure performance and scale
    • Data Warehousing
    • BigQuery
    • provides scalable, fully managed enterprise data warehouse (EDW) with SQL and fast ad-hoc
    • Remember it is most suitable for historical analysis.
    • know how to access control tables, columns within tables and query results (hint – Authorized View)
    • Be sure to cover the Best Practices including key strategy, cost optimization, partitioning and clustering
  • Module 4
    • Data Services
    • Obviously there is lots of Data and Just Data
    • Know the Big Data stack and understand which service fits the different layers of ingesting, store, process, analytics, use
    • Cloud Storage
    • as the medium to store data as a data lake
    • understand what class is the best suited and which one provides geo-redundancy.
    • Cloud Pub/Sub
    • as the messaging service to capture real-time data esp. IoT
    • is designed to provide reliable, many-to-many, asynchronous messaging between applications esp. real time IoT data capture
    • how it compares to Kafka
    • Cloud Dataflow
    • to process, transform, transfer data and the key service to integrate store and
    • know how to improve a Dataflow performance
    • Google expects you to know the Apache Beam features as well
    • understand PCollections, Transforms, ParDo and what they do
    • understand windowing and triggers
  • Module 5
    • Cloud BigQuery
    • for storage and analytics. Remember BigQuery provides the same cost- effective option for storage as Cloud Storage
    • understand how BigQuery Streaming works
    • know BigQuery limitations with updates and inserts
    • Cloud Dataprep
    • to clean and prepare data. It can be used anomaly
    • does not need any programming language knowledge and can be done through graphical interface
    • be sure to know or try hands-on on a dataset
    • Cloud Dataproc
    • to handle existing Hadoop/Spark jobs
    • you need to know how to improve the performance of the Hadoop cluster as well :). Know how to configure the hadoop cluster to use all the cores (hint- spark executor cores) and handle out of memory errors (hint – executor memory)
    • how to install other components (hint – initialization actions)
    • Cloud Datalab
    • is an interactive tool for exploration, transformation, analysis and visualization of your data on Google Cloud Platform
    • based on Jupyter
    • Cloud Composer
    • fully managed workflow orchestration service based on Apache Airflow
    • pipelines are configured as directed acyclic graphs (DAGs)
    • workflow lives on-premises, in multiple clouds, or fully within
    • provides ability to author, schedule, and monitor your workflows ina unified manner
  • Module 6
    • Machine Learning
    • Google expects the Data Engineer to surely know some of the Data scientists stuff
    • Understand the different algorithms
    • Supervised Learning (labelled data) 
    • Classification (for e.g. Spam or Not)
    • Regression (for e.g. Stock or House prices)
    • Unsupervised Learning (Unlabelled data)
    • Clustering (for e.g. categories)
    • Reinforcement Learning
    • Know Cloud ML with Tensorflow
    • Know all the Cloud AI products which include
    • Cloud Vision
    • Cloud Natural Language
    • Cloud Speech-to-Text
    • Cloud Video Intelligence
    • Cloud AutoML products, which can help you get started without much machine learning experience
  • Module 7
    • Monitoring
    • Google Stackdriver provides everything from monitoring, alert, error reporting, metrics, diagnostics, debugging,
    • remember audits are mainly checking Stackdriver
    • Security Services
    • Data Loss Prevention API to handle sensitive data esp. redaction of PII
    • understand Encryption techniques
    • Other Services
    • Storage Transfer Service allows import of large amounts of online data into Google Cloud Storage, quickly and cost-effectively. Online data is the key here as it supports AWS S3, HTTP/HTTPS and other GCS buckets. If the data is on-premises you need to use gsutil command
    • Transfer Appliance to transfer large amounts of data quickly and cost- effectively into Google Cloud Platform. Check for the data size and it would be always compared with Google Transfer Service or gsutil
    • BigQuery Data Transfer Service to integrate with third-party services and load data into BigQuery
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    11125 12500

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    This course includes
    • 25 hours high-quality video
    • 2 projects
    • 5 downloadable resource
    • Lifetime access and 24x7 support
    • Access on your computer or mobile
    • Get certificate on course completion
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    • High-quality content created by industry experts
    • Lifetime access to high-quality self-paced learning and live online class recordings
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