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Mark Shay

Member since 2020

Badge for #GoogleClout Set 2, 1/10 #GoogleClout Set 2, 1/10 Earned Aug 12, 2022 EDT
Badge for Create and Manage Cloud Spanner Databases Create and Manage Cloud Spanner Databases Earned Aug 12, 2022 EDT
Badge for DEPRECATED Explore Machine Learning Models with Explainable AI DEPRECATED Explore Machine Learning Models with Explainable AI Earned Aug 11, 2022 EDT
Badge for Optimizing Your Google Cloud Costs Optimizing Your Google Cloud Costs Earned Aug 9, 2022 EDT
Badge for Insights from Data with BigQuery Insights from Data with BigQuery Earned Jun 29, 2022 EDT
Badge for Infrastructure and Application Modernization with Google Cloud Infrastructure and Application Modernization with Google Cloud Earned Jun 27, 2022 EDT
Badge for Share Data Using Google Data Cloud Share Data Using Google Data Cloud Earned Jun 27, 2022 EDT
Badge for Using Vault on Google Cloud Using Vault on Google Cloud Earned Jun 24, 2022 EDT
Badge for Exploring and Preparing your Data with BigQuery Exploring and Preparing your Data with BigQuery Earned Jun 23, 2022 EDT
Badge for Achieving Advanced Insights with BigQuery Achieving Advanced Insights with BigQuery Earned Jun 23, 2022 EDT
Badge for Creating New BigQuery Datasets and Visualizing Insights Creating New BigQuery Datasets and Visualizing Insights Earned Jun 23, 2022 EDT
Badge for Cloud Logging Cloud Logging Earned Jun 17, 2022 EDT
Badge for Integrate with Machine Learning APIs Integrate with Machine Learning APIs Earned Jun 14, 2022 EDT
Badge for Innovating with Data and Google Cloud Innovating with Data and Google Cloud Earned Jun 12, 2022 EDT
Badge for Set Up and Configure a Cloud Environment in Google Cloud Set Up and Configure a Cloud Environment in Google Cloud Earned Jun 10, 2022 EDT
Badge for Advanced ML: ML Infrastructure Advanced ML: ML Infrastructure Earned Jun 9, 2022 EDT
Badge for Workspace Essentials Workspace Essentials Earned Jun 9, 2022 EDT
Badge for Workspace: Add-ons Workspace: Add-ons Earned Jun 8, 2022 EDT
Badge for Google Cloud Run Serverless Workshop Google Cloud Run Serverless Workshop Earned Jun 8, 2022 EDT
Badge for Cloud Development Cloud Development Earned Jun 8, 2022 EDT
Badge for Data Science on Google Cloud: Machine Learning Data Science on Google Cloud: Machine Learning Earned Jun 7, 2022 EDT
Badge for DevOps Essentials DevOps Essentials Earned Jun 7, 2022 EDT
Badge for Data Lake Modernization (Hadoop) on GCP Data Lake Modernization (Hadoop) on GCP Earned May 27, 2022 EDT
Badge for Serverless Data Processing with Dataflow: Develop Pipelines Serverless Data Processing with Dataflow: Develop Pipelines Earned May 27, 2022 EDT
Badge for Data Warehousing for Partners: Data Warehouse Migration with BigQuery Data Warehousing for Partners: Data Warehouse Migration with BigQuery Earned May 20, 2022 EDT
Badge for Google Cloud Platform Fundamentals: Core Infrastructure Google Cloud Platform Fundamentals: Core Infrastructure Earned May 19, 2022 EDT
Badge for Data Lake Modernization on Google Cloud Data Lake Modernization on Google Cloud Earned May 18, 2022 EDT
Badge for Inside Track: SQL Server - Advanced Inside Track: SQL Server - Advanced Earned May 17, 2022 EDT
Badge for Smart Analytics, Machine Learning, and AI on Google Cloud Smart Analytics, Machine Learning, and AI on Google Cloud Earned May 17, 2022 EDT
Badge for Building Resilient Streaming Analytics Systems on Google Cloud Building Resilient Streaming Analytics Systems on Google Cloud Earned May 17, 2022 EDT
Badge for Modernizing Data Lakes and Data Warehouses with Google Cloud Modernizing Data Lakes and Data Warehouses with Google Cloud Earned May 17, 2022 EDT
Badge for Google Cloud Big Data and Machine Learning Fundamentals Google Cloud Big Data and Machine Learning Fundamentals Earned May 17, 2022 EDT
Badge for Exploring APIs Exploring APIs Earned May 13, 2022 EDT
Badge for Build LookML Objects in Looker Build LookML Objects in Looker Earned May 11, 2022 EDT
Badge for Applying Advanced LookML Concepts in Looker Applying Advanced LookML Concepts in Looker Earned May 10, 2022 EDT
Badge for Exploring Data with Looker Exploring Data with Looker Earned May 9, 2022 EDT
Badge for Create ML Models with BigQuery ML Create ML Models with BigQuery ML Earned Apr 22, 2022 EDT
Badge for Security & Identity Fundamentals Security & Identity Fundamentals Earned Apr 12, 2022 EDT
Badge for Build and Secure Networks in Google Cloud Build and Secure Networks in Google Cloud Earned Apr 11, 2022 EDT
Badge for Monitor Environments with Google Cloud Managed Service for Prometheus Monitor Environments with Google Cloud Managed Service for Prometheus Earned Apr 11, 2022 EDT
Badge for Enterprise Database Migration Enterprise Database Migration Earned Apr 9, 2022 EDT
Badge for Building Advanced Codeless Pipelines on Cloud Data Fusion Building Advanced Codeless Pipelines on Cloud Data Fusion Earned Apr 6, 2022 EDT
Badge for Deploy and Manage Cloud Environments with Google Cloud Deploy and Manage Cloud Environments with Google Cloud Earned Apr 4, 2022 EDT
Badge for Google Developer Essentials Google Developer Essentials Earned Apr 4, 2022 EDT
Badge for IoT in the Google Cloud IoT in the Google Cloud Earned Apr 3, 2022 EDT
Badge for Applying BigQuery ML's Classification, Regression, and Demand Forecasting for Retail Applications Applying BigQuery ML's Classification, Regression, and Demand Forecasting for Retail Applications Earned Apr 2, 2022 EDT
Badge for Automate Data Capture at Scale with Document AI Automate Data Capture at Scale with Document AI Earned Apr 2, 2022 EDT
Badge for Anthos Service Mesh Anthos Service Mesh Earned Apr 2, 2022 EDT
Badge for VM Migration VM Migration Earned Apr 1, 2022 EDT
Badge for Network Performance and Optimization Network Performance and Optimization Earned Mar 30, 2022 EDT
Badge for Baseline: Deploy & Develop Baseline: Deploy & Develop Earned Mar 30, 2022 EDT
Badge for Cloud Engineering Cloud Engineering Earned Mar 29, 2022 EDT
Badge for Deploying Applications Deploying Applications Earned Mar 29, 2022 EDT
Badge for Intermediate ML: TensorFlow on Google Cloud Intermediate ML: TensorFlow on Google Cloud Earned Mar 28, 2022 EDT
Badge for BigQuery for Machine Learning BigQuery for Machine Learning Earned Mar 28, 2022 EDT
Badge for Managing Cloud Infrastructure with Terraform Managing Cloud Infrastructure with Terraform Earned Mar 28, 2022 EDT
Badge for Baseline: Infrastructure Baseline: Infrastructure Earned Mar 26, 2022 EDT
Badge for Networking in Google Cloud Networking in Google Cloud Earned Mar 26, 2022 EDT
Badge for Google Cloud's Operations Suite Google Cloud's Operations Suite Earned Mar 25, 2022 EDT
Badge for Kubernetes in Google Cloud Kubernetes in Google Cloud Earned Mar 25, 2022 EDT
Badge for Cloud Architecture Cloud Architecture Earned Mar 23, 2022 EDT
Badge for Building Codeless Pipelines on Cloud Data Fusion Building Codeless Pipelines on Cloud Data Fusion Earned Feb 24, 2022 EST
Badge for Getting Started with Apache Kafka and Confluent Platform on Google Cloud Getting Started with Apache Kafka and Confluent Platform on Google Cloud Earned Jan 29, 2022 EST
Badge for Kubernetes Solutions Kubernetes Solutions Earned Jan 19, 2022 EST
Badge for Windows on Google Cloud Windows on Google Cloud Earned Jan 17, 2022 EST
Badge for Baseline: Data, ML, AI Baseline: Data, ML, AI Earned Jan 17, 2022 EST
Badge for Understanding LookML in Looker Understanding LookML in Looker Earned Jan 16, 2022 EST
Badge for Google Cloud Solutions II: Data and Machine Learning Google Cloud Solutions II: Data and Machine Learning Earned Jan 16, 2022 EST
Badge for Sports Analytics: Pitch Perfect BigQuery Sports Analytics: Pitch Perfect BigQuery Earned Jan 15, 2022 EST
Badge for Migrate MySQL data to Cloud SQL using Database Migration Service Migrate MySQL data to Cloud SQL using Database Migration Service Earned Jan 14, 2022 EST
Badge for Migrating MySQL data to Cloud SQL using Database Migration Service Migrating MySQL data to Cloud SQL using Database Migration Service Earned Jan 14, 2022 EST
Badge for Google Cloud Fundamentals: Core Infrastructure Google Cloud Fundamentals: Core Infrastructure Earned Jan 13, 2022 EST
Badge for Scientific Data Processing Scientific Data Processing Earned Jan 13, 2022 EST
Badge for Applied Data: Blockchain Applied Data: Blockchain Earned Jan 12, 2022 EST
Badge for Data Science on Google Cloud Data Science on Google Cloud Earned Jan 11, 2022 EST
Badge for BigQuery for Marketing Analysts BigQuery for Marketing Analysts Earned Jan 10, 2022 EST
Badge for Serverless Data Processing with Dataflow: Foundations Serverless Data Processing with Dataflow: Foundations Earned Jan 10, 2022 EST
Badge for Google Cloud Big Data and Machine Learning Fundamentals Google Cloud Big Data and Machine Learning Fundamentals Earned Jan 10, 2022 EST
Badge for Preparing for the Google Cloud Professional Data Engineer Exam Preparing for the Google Cloud Professional Data Engineer Exam Earned Jan 8, 2022 EST
Badge for Create Conversational AI Agents with Dialogflow CX Create Conversational AI Agents with Dialogflow CX Earned Dec 11, 2021 EST
Badge for Application Development - Python Application Development - Python Earned Jul 27, 2020 EDT
Badge for NCAA® March Madness®: Bracketology with Google Cloud NCAA® March Madness®: Bracketology with Google Cloud Earned Jul 24, 2020 EDT
Badge for BigQuery for Data Analysis BigQuery for Data Analysis Earned Jul 24, 2020 EDT
Badge for BigQuery Basics for Data Analysts BigQuery Basics for Data Analysts Earned Jul 24, 2020 EDT
Badge for Data Catalog Fundamentals Data Catalog Fundamentals Earned Jul 24, 2020 EDT
Badge for Engineer Data in Google Cloud Engineer Data in Google Cloud Earned Jul 24, 2020 EDT
Badge for Data Engineering Data Engineering Earned Jul 24, 2020 EDT
Badge for BigQuery for Data Warehousing BigQuery for Data Warehousing Earned Jul 23, 2020 EDT
Badge for Cloud SQL Cloud SQL Earned Jul 22, 2020 EDT
Badge for Create and Manage Cloud Resources Create and Manage Cloud Resources Earned Jul 22, 2020 EDT
Badge for Google Cloud Essentials Google Cloud Essentials Earned Jul 22, 2020 EDT

Flex your Google Clout! Each day unlocks a new cloud puzzle. Complete all five and you’ll earn the inaugural Google Cloud badge! Share your score on your choice of social networks and join the conversation over in the Google Cloud Community.

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Earn a skill badge by completing the Create and Manage Cloud Spanner Databases quest, where you will learn how to: Create and Interact with a Cloud Spanner Database; Load a Cloud Spanner Database using various techniques; Backup a Cloud Spanner Database; Define Schemas and Understand Query Plans; and Deploy a Modern Web App connected to a Cloud Spanner instance. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge quest, and the final assessment challenge lab, to receive a skill badge that you can share with your network.

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Earn a skill badge by completing the Explore Machine Learning Models with Explainable AI quest, where you will learn how to do the following using Explainable AI: build and deploy a model to an AI platform for serving (prediction), use the What-If Tool with an image recognition model, identify bias in mortgage data using the What-If Tool, and compare models using the What-If Tool to identify potential bias. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge quest and the final assessment challenge lab to receive a skill badge that you can share with your network.

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This is the second Quest in a two-part series on Google Cloud billing and cost management essentials. This Quest is most suitable for those in a Finance and/or IT related role responsible for optimizing their organization’s cloud infrastructure. Here you'll learn several ways to control and optimize your Google Cloud costs, including setting up budgets and alerts, managing quota limits, and taking advantage of committed use discounts. In the hands-on labs, you’ll practice using various tools to control and optimize your Google Cloud costs or to influence your technology teams to apply the cost optimization best practices.

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Earn a skill badge by completing the Insights from Data with BigQuery quest, where you learn about the following basic features of BigQuery: write SQL queries, create and manage database tables in Cloud SQL, query public tables, and load sample data into BigQuery, troubleshoot common Syntax errors with the Query Validator, use Google Apps Script, create a chart in Google Sheets, and export that data to Google Slides, and create reports in Google Data Studio by connecting to BigQuery data. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge quest, and the final assessment challenge lab, to receive a skill badge that you can share with your network.

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'Many traditional enterprises use legacy systems and applications that often struggle to achieve the scale and speed needed to meet modern customer expectations. Business leaders and IT decision makers constantly have to choose between maintenance of legacy systems and investing in innovative new products and services. This course explores the challenges of an outdated IT infrastructure and how businesses can modernize it using cloud technology. It begins by exploring the different compute options available in the cloud and the benefits of each, before turning to application modernization and Application Programming Interfaces (APIs). The course also considers a range of Google Cloud solutions that can help businesses to better develop and manage their systems, such as Compute Engine, App Engine, and Apigee.' This is the third course in the Cloud Digital Leader series. At the end of this course, enroll in the Understanding Google Cloud Security and Operations course

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Earn a skill badge by completing the Share Data Using Google Data Cloud quest, where you will gain practical experience with Google Cloud Data Sharing Partners, which have proprietary datasets that customers can use for their analytics use cases. Customers subscribe to this data, query it within their own platform, then augment it with their own datasets and use their visualization tools for their customer facing dashboards. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the skill badge quest, and final assessment challenge lab, to receive a digital badge that you can share with your network.

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This quest introduces you to Vault and teaches you how to secure, store, and tightly control access to tokens, passwords, certificates, and encryption keys to protect secrets and other sensitive data.

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In this course, we see what the common challenges faced by data analysts are and how to solve them with the big data tools on Google Cloud. You’ll pick up some SQL along the way and become very familiar with using BigQuery and Dataprep to analyze and transform your datasets. This is the first course of the From Data to Insights with Google Cloud series. After completing this course, enroll in the Creating New BigQuery Datasets and Visualizing Insights course.

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The third course in this course series is Achieving Advanced Insights with BigQuery. Here we will build on your growing knowledge of SQL as we dive into advanced functions and how to break apart a complex query into manageable steps. We will cover the internal architecture of BigQuery (column-based sharded storage) and advanced SQL topics like nested and repeated fields through the use of Arrays and Structs. Lastly we will dive into optimizing your queries for performance and how you can secure your data through authorized views. After completing this course, enroll in the Applying Machine Learning to your Data with Google Cloud course.

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This is the second course in the Data to Insights course series. Here we will cover how to ingest new external datasets into BigQuery and visualize them with Google Data Studio. We will also cover intermediate SQL concepts like multi-table JOINs and UNIONs which will allow you to analyze data across multiple data sources. Note: Even if you have a background in SQL, there are BigQuery specifics (like handling query cache and table wildcards) that may be new to you. After completing this course, enroll in the Achieving Advanced Insights with BigQuery course.

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Cloud Logging is a fully managed service that performs at scale. It can ingest application and system log data from thousands of VMs and, even better, analyze all that log data in real time. In this fundamental-level Quest, you learn how to store, search, analyze, monitor, and alert on log data and events from Google Cloud. The labs in the Quest give you hands-on practice using Cloud Logging to maximize your learning experience and provide insight on how you can use Cloud Logging to your own Google Cloud environment.

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Earn a skill badge by completing the Integrate with Machine Learning APIs quest, where you learn the basic features for the following machine learning and AI technologies: Cloud Vision API, Cloud Cloud Translation API, and Cloud Natural Language API. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge quest, and the final assessment challenge lab, to receive a skill badge that you can share with your network.

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Cloud technology on its own only provides a fraction of the true value to a business; When combined with data–lots and lots of it–it has the power to truly unlock value and create new experiences for customers. In this course, you'll learn what data is, historical ways companies have used it to make decisions, and why it is so critical for machine learning. This course also introduces learners to technical concepts such as structured and unstructured data. database, data warehouse, and data lakes. It then covers the most common and fastest growing Google Cloud products around data.

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Earn a skill badge by completing the Set Up and Configure a Cloud Environment in Google Cloud quest, where you learn multiple ways to deploy and monitor applications including how to: explore IAM rols and add/remove project access, create VPC networks, deploy and monitor Compute Engine VMs, write SQL queries, deploy and monitor VMs in Compute Engine, and deploy applications using Kubernetes with multiple deployment approaches. A skill badge is an exclusivedigital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge quest, and the final assessment challenge lab, to receive a skill badge that you can share with your network.

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Machine Learning is one of the most innovative fields in technology, and the Google Cloud Platform has been instrumental in furthering its development. With a host of APIs, GCP has a tool for just about any machine learning job. In this advanced-level quest, you will get hands-on practice with machine learning at scale and how to employ the advanced ML infrastructure available on GCP.

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Workspace (formerly G Suite) is Google's collaborative applications platform, delivered from Google Cloud. In this introductory-level quest, you will get hands-on practice with Workspace’s core applications from a user perspective. Although there are many more applications and tool components to Workspace than are covered here, you will get experience with the primary apps: Gmail, Calendar, Sheets and a handful of others. Each lab can be completed in 10-15 minutes, but extra time is provided to allow self-directed free exploration of the applications.

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This quest of hands-on labs demonstrates the power of integrating Google Cloud services and tools with Workspace applications - like using Node.js to build a survey bot, the Natural Language API to recognize sentiment in a Google Doc, and building a chat bot with Apps Script.

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Twelve years ago Lily started the Pet Theory chain of veterinary clinics, and has been expanding rapidly. Now, Pet Theory is experiencing some growing pains: their appointment scheduling system is not able to handle the increased load, customers aren't receiving lab results reliably through email and text, and veteranerians are spending more time with insurance companies than with their patients. Lily wants to build a cloud-based system that scales better than the legacy solution and doesn't require lots of ongoing maintenance. The team has decided to go with serverless technology. For the labs in the Google Cloud Run Serverless Quest, you will read through a fictitious business scenario in each lab and assist the characters in implementing a serverless solution. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google…

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The hands-on labs in this Quest are structured to give experienced app developers hands-on practice with the state-of-the-art developing applications in Google Cloud. The topics align with the Google Cloud Certified Professional Cloud Developer Certification. These labs follow the sequence of activities needed to create and deploy an app in Google Cloud from beginning to end. Be aware that while practice with these labs will increase your skills and abilities, it is recommended that you also review the exam guide and other available preparation resources.

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This is the second of two Quests of hands-on labs derived from the exercises from the book Data Science on Google Cloud Platform, 2nd Edition by Valliappa Lakshmanan, published by O'Reilly Media, Inc. In this second Quest, covering chapter 9 through the end of the book, you extend the skills practiced in the first Quest, and run full-fledged machine learning jobs with state-of-the-art tools and real-world data sets, all using Google Cloud tools and services.

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Obtain a competitive advantage through DevOps. DevOps is an organizational and cultural movement that aims to increase software delivery velocity, improve service reliability, and build shared ownership among software stakeholders. In this quest you will learn how to use Google Cloud to improve the speed, stability, availability, and security of your software delivery capability. DevOps Research and Assessment has joined Google Cloud. How does your team measure up? Take this five question multiple-choice quiz and find out! Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.

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The Data Lake Modernization course aims to prepare you to lead a Data Lake Modernization engagement through discovery & qualification through the technical considerations & cost modelling. The training is designed to educate on the Migration Journey, Data Lifecycle, Costing & Hands on Technical execution. At the end of the training you will have a deeper understanding of the Data Lake ecosystem, modernizing and migrating to GCP and hands-on experience of building data ingestion, processing & analytics pipelines on GCP.

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In this second installment of the Dataflow course series, we are going to be diving deeper on developing pipelines using the Beam SDK. We start with a review of Apache Beam concepts. Next, we discuss processing streaming data using windows, watermarks and triggers. We then cover options for sources and sinks in your pipelines, schemas to express your structured data, and how to do stateful transformations using State and Timer APIs. We move onto reviewing best practices that help maximize your pipeline performance. Towards the end of the course, we introduce SQL and Dataframes to represent your business logic in Beam and how to iteratively develop pipelines using Beam notebooks.

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In this course, you will receive technical training for Enterprise Data Warehouses solutions using BigQuery based on the best practices developed internally by Google’s technical sales and services organizations. The course will also provide guidance and training on key technical challenges that can arise when migrating existing Enterprise Data Warehouses and ETL pipelines to Google Cloud. You will get hands-on experience with real migration tasks, such as data migration, schema optimization, and SQL Query conversion and optimization. The course will also cover key aspects of ETL pipeline migration to Dataproc as well as using PubSub, Dataflow, and Cloud Data Fusion, giving you hands-on experience using all of these tools for Data Warehouse ETL pipelines.

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This content is deprecated. Please see the latest version of the course, here.

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This course focuses on how you can bring your on-premises data lakes and workloads to Google Cloud to unlock cost savings and scale.

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This course further explores SQL Server on Google Cloud.

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Incorporating machine learning into data pipelines increases the ability of businesses to extract insights from their data. This course covers several ways machine learning can be included in data pipelines on Google Cloud depending on the level of customization required. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions using Kubeflow. Learners will get hands-on experience building machine learning models on Google Cloud using QwikLabs. This is the fourth course of the Data Engineering on Google Cloud series.

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Processing streaming data is becoming increasingly popular as streaming enables businesses to get real-time metrics on business operations. This course covers how to build streaming data pipelines on Google Cloud. Pub/Sub is described for handling incoming streaming data. The course also covers how to apply aggregations and transformations to streaming data using Dataflow, and how to store processed records to BigQuery or Cloud Bigtable for analysis. Learners will get hands-on experience building streaming data pipeline components on Google Cloud using QwikLabs.

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The two key components of any data pipeline are data lakes and warehouses. This course highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud in technical detail. Also, this course describes the role of a data engineer, the benefits of a successful data pipeline to business operations, and examines why data engineering should be done in a cloud environment. This is the first course of the Data Engineering on Google Cloud series. After completing this course, enroll in the Building Batch Data Pipelines on Google Cloud course.

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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.

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Google Cloud Application Programming Interfaces are the mechanism to interact with Google Cloud Services programmatically. This quest will give you hands-on practice with a variety of GCP APIs, which you will learn through working with Google’s APIs Explorer, a tool that allows you to browse APIs and run their methods interactively. By learning how to transfer data between Cloud Storage buckets, deploy Compute Engine instances, configure Dataproc clusters and much more, Exploring APIs will show you how powerful APIs are and why they are used almost exclusively by proficient GCP users. Enroll in this quest today.

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Earn a skill badge by completing the Build LookML Objects in Looker quest, where you will learn how to do the following: design/build new dimensions and measures, views, and derived tables, set measure filters and types based on requirements, update dimensions and measures (change names, use aliases), build and refine Explores, join views to existing Explores, and decide which LookML objects to create based on business requirements. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge quest and the final assessment challenge lab to receive a skill badge that you can share with your network.

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In this quest, you will get hands-on experience applying advanced LookML concepts in Looker. You will learn how to use Liquid to customize and create dynamic dimensions and measures, create dynamic SQL derived tables and customized native derived tables, and use extends to modularize your LookML code.

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Earn a skill badge by completing the Exploring Data with Looker quest, where you will learn how to use the Explore interface to access data published by LookML developers. In this quest, you will learn fundamentals of data exploration in Looker including but not limited to dimensions and measures, filtering and pivoting, merging explores, and using advanced functions. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge quest and the final assessment challenge lab to receive a skill badge that you can share with your network.

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Earn a skill badge by completing the Create ML Models with BigQuery ML quest, where you learn how to use BigQuery ML to: create machine learning models, create a classification model, create a forecasting model, and implement a chatbot using Dialogflow for dynamic real-time responses. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge quest, and the final assessment challenge lab, to receive a skill badge that you can share with your network.

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Security is an uncompromising feature of Google Cloud services, and Google Cloud has developed specific tools for ensuring safety and identity across your projects. In this fundamental-level quest, you will get hands-on practice with Google Cloud’s Identity and Access Management (IAM) service, which is the go-to for managing user and virtual machine accounts. You will get experience with network security by provisioning VPCs and VPNs, and learn what tools are available for security threat and data loss protections. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.

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Earn a skill badge by completing the Build and Secure Networks in Google Cloud quest, where you will learn about multiple networking-related resources to build, scale, and secure your applications on Google Cloud, including how to: Enable Identity-Aware Proxy, Create VPC networks, Create virtual machine instances with nginx web servers using Compute Engine, Create firewall rules to control internal and external access to your VMs, Configure, stress, and protect a multi-region HTTP application with an HTTP load balancer and Google Cloud Armor, Configure and test an internal TCP load balancer with a regional backend service. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the skill badge quest, and final assessment challenge lab, to receive a digital badge that you can share with your network.

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Earn a skill badge by completing the Monitor Environments with Managed Service for Prometheus quest, where you learn Kubernetes Monitoring with Google Cloud Managed Service for Prometheus. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this Skill Badge, and the final assessment challenge lab, to receive a digital badge that you can share with your network.

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This course is intended to give architects, engineers, and developers the skills required to help enterprise customers architect, plan, execute, and test database migration projects. Through a combination of presentations, demos, and hands-on labs participants move databases to Google Cloud while taking advantage of various services. This course covers how to move on-premises, enterprise databases like SQL Server to Google Cloud (Compute Engine and Cloud SQL) and Oracle to Google Cloud bare metal.

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This advanced-level Quest builds on its predecessor Quest, and offers hands-on practice on the more advanced data integration features available in Cloud Data Fusion, while sharing best practices to build more robust, reusable, dynamic pipelines. Learners get to try out the data lineage feature as well to derive interesting insights into their data’s history.

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Earn a skill badge by completing the Deploy and Manage Cloud Environments with Google Cloud quest, where you will learn how to: use the gcloud CLI tool to set up and configure command features of Cloud Identity and Access Management (IAM), deploy and scale a Web App on Google Compute Engine, provision a complete Kubernetes cluster using Google Container Engine (GKE) and break an application into microservices using Kubernetes’ Deployments and Services, perform basic networking tasks on Google Cloud Platform, view BigQuery logs inside Cloud Logging and set up a sink to export them back into BigQuery, and migrate a stand-alone PostgreSQL database to Cloud SQL for PostgreSQL using a continuous Database Migration Service job and VPC peering for conectivity. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Compl…

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This introductory-level quest shows application developers how the Google Cloud ecosystem could help them build secure, scalable, and intelligent cloud native applications. You learn how to develop and scale applications without setting up infrastructure, run data analytics, gain insights from data, and develop with pre-trained ML APIs to leverage machine learning even if you are not a Machine Learning expert. You will also experience seamless integration between various Google services and APIs to create intelligent apps.

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In this quest, you will learn about Google Cloud’s IoT Core service and its integration with other services like GCS, Dataprep, Stackdriver and Firestore. The labs in this quest use simulator code to mimic IOT devices and the learning here should empower you to implement the same streaming pipeline with real world IoT devices.

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In this quest you will learn how to use several BigQuery ML features to improve retail use cases. Predict the demand for bike rentals in NYC with demand forecasting, leverage regression to estimate the time it will take for a ticket to be solved with the help of an automated agent developed using Dialogflow, and see how to use BigQuery ML for a classification task that predicts the likelihood of a website visitor making a purchase.

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Earn a skill badge by completing the Automate Data Capture at Scale with Document AI quest, where you learn how to create a document processing pipeline that will automatically process documents. You will learn how to use the Document AI form processor to extract data from the documents and save the data. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge quest, and the final assessment challenge lab, to receive a skill badge that you can share with your network.

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This intermediate-level quest is unique among Qwiklabs quests. These labs have been curated to give operators hands-on practice with Anthos—a new, open application modernization platform on Google Cloud. Anthos enables you to build and manage modern hybrid applications. Tasks include: installing service mesh, collecting telemetry, and securing your microservices with service mesh policies. This quest is composed of labs targeted to teach you everything you need to know to introduce service mesh, and Anthos, into your next hybrid cloud project.

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Google Cloud’s four step structured Cloud Migration Path Methodology provides a defined and repeatable path for users to follow when migrating and modernizing Virtual Machines. In this quest, you will get hands-on practice with Google’s current solution set for VM assessment, planning, migration, and modernization. You will start by analyzing your lab environment and building assessment reports with CloudPhysics and StratoZone, then build a landing zone within Google Cloud leveraging Terraform’s infrastructure-as-code templates, next you will manually transform a two-tier application into a cloud-native workload running on Kubernetes, and finally, transform a VM workload into Kubernetes with Migrate for Anthos and migrate a VM between cloud environments.

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If you want to take your GCP networking skills to the next level, look no further. This quest is composed of labs that cover real-life use cases and it will teach you best practices for overcoming common networking bottlenecks. From getting hands-on practice with testing and improving network performance, to integrating high-throughput VPNs and networking tiers, Network Performance and Optimization is an essential quest for GCP developers who are looking to double down on application speed and robustness.

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In this introductory-level quest, you will learn the fundamentals of developing and deploying applications on the Google Cloud Platform. You will get hands-on experience with the Google App Engine framework by launching applications written in languages like Python, Ruby, and Java (just to name a few). You will see first-hand how straightforward and powerful GCP application frameworks are, and how easily they integrate with GCP database, data-loss prevention, and security services.

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This fundamental-level quest is unique amongst the other Qwiklabs offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Associate Cloud Engineer Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.

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The Google Cloud Platform provides many different frameworks and options to fit your application’s needs. In this introductory-level quest, you will get plenty of hands-on practice deploying sample applications on Google App Engine. You will also dive into other web application frameworks like Firebase, Wordpress, and Node.js and see firsthand how they can be integrated with Google Cloud.

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TensorFlow is an open source software library for high performance numerical computation that's great for writing models that can train and run on platforms ranging from your laptop to a fleet of servers in the Cloud to an edge device. This quest takes you beyond the basics of using predefined models and teaches you how to build, train and deploy your own on Google Cloud.

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Want to build ML models in minutes instead of hours using just SQL? BigQuery ML democratizes machine learning by letting data analysts create, train, evaluate, and predict with machine learning models using existing SQL tools and skills. In this series of labs, you will experiment with different model types and learn what makes a good model. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of this quest>/a> to receive an exclusive Google Cloud digital badge.

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In this Quest, the experienced user of Google Cloud will learn how to describe and launch cloud resources with Terraform, an open source tool that codifies APIs into declarative configuration files that can be shared amongst team members, treated as code, edited, reviewed, and versioned. In these nine hands-on labs, you will work with example templates and understand how to launch a range of configurations, from simple servers, through full load-balanced applications.

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If you are a novice cloud developer looking for hands-on practice beyond Google Cloud Essentials, this quest is for you. You will get practical experience through labs that dive into Cloud Storage and other key application services like Stackdriver and Cloud Functions. By taking this quest, you will develop valuable skills that are applicable to any Google Cloud initiative. 1-minute videos walk you through key concepts for these labs.

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Networking is a principle theme of cloud computing. It’s the underlying structure of Google Cloud, and it’s what connects all your resources and services to one another. This fundamental-level quest will cover essential Google CLoud networking services and will give you hands-on practice with specialized tools for developing mature networks. From learning the ins-and-outs of VPCs, to creating enterprise-grade load balancers, Networking in the Google Cloud will give you the practical experience needed so you can start building robust networks right away. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of the Build and Secure Networks in Google Cloud Quest to receive an exclusive Google Cloud digital badge.

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In this fundamental-level quest, you will learn the ins and outs of Google Cloud's operations suite, an important service for generating insights into the health of your applications. It provides a wealth of information in application monitoring, report logging, and diagnoses. The labs in this quest will give you hands-on practice with and will teach you how to monitor virtual machines, generate logs and alerts, and create custom metrics for application data. It is recommended that the students have at least earned a Badge by completing the Google Cloud Essentials Quest. Additional lab experience with the labs in the Baseline-Infrastructure Quest will also be useful. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of the Monitor and Log with Google Cloud Operations Suite to receive an exclusive Google Cloud digital badge.

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Kubernetes is the most popular container orchestration system, and Google Kubernetes Engine was designed specifically to support managed Kubernetes deployments in Google Cloud. In this advanced-level quest, you will get hands-on practice configuring Docker images, containers, and deploying fully-fledged Kubernetes Engine applications. This quest will teach you the practical skills needed for integrating container orchestration into your own workflow. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, finish the additional Challenge Lab at the end of the Deploy to Kubernetes in Google Cloud Quest to receive an exclusive Google Cloud digital badge.

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This fundamental-level quest is unique amongst the other Qwiklabs offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Cloud Architect Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.

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This fundamental-level Quest offers hands-on practice with Cloud Data Fusion, a cloud-native, code-free, data integration platform. ETL Developers, Data Engineers and Analysts can greatly benefit from the pre-built transformations and connectors to build and deploy their pipelines without worrying about writing code. This Quest starts with a quickstart lab that familiarises learners with the Cloud Data Fusion UI. Learners then get to try running batch and realtime pipelines as well as using the built-in Wrangler plugin to perform some interesting transformations on data.

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Organizations around the world rely on Apache Kafka to integrate existing systems in real time and build a new class of event streaming applications that unlock new business opportunities. Google and Confluent are in a partnership to deliver the best event streaming service based on Apache Kafka and to build event driven applications and big data pipelines on Google Cloud Platform. In this Quest, you will first learn how to deploy and create a streaming data pipeline with Apache Kafka. You will then perform hand-on labs on the different functionalities of the Confluent Platform such as deploying and running Apache Kafka on GKE, building a Cloud Run Streaming Application with Apache Kafka on Anthos or developing a Streaming Microservices Application.

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Containerized applications have changed the game and are here to stay. With Kubernetes, you can orchestrate containers with ease, and integration with the Google Cloud Platform is seamless. In this advanced-level quest, you will be exposed to a wide range of Kubernetes use cases and will get hands-on practice architecting solutions over the course of 8 labs. From building Slackbots with NodeJS, to deploying game servers on clusters, to running the Cloud Vision API, Kubernetes Solutions will show you first-hand how agile and powerful this container orchestration system is.

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Google Cloud is committed to supporting Windows workloads in its frameworks and services. In this advanced-level quest, you will get hands-on practice running many of the popular Windows services on Google Cloud. For example, you will learn how to instantiate Microsoft SQL databases, cloud tools for Powershell on Google Cloud Platform frameworks.

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Big data, machine learning, and artificial intelligence are today’s hot computing topics, but these fields are quite specialized and introductory material is hard to come by. Fortunately, Google Cloud provides user-friendly services in these areas and Qwiklabs has you covered with this introductory-level quest, so you can take your first steps with tools like Big Query, Cloud Speech API, and AI Platform. Want extra help? 1-minute videos walk you through key concepts for each lab.

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In this quest, you will get hands-on experience with LookML in Looker. You will learn how to write LookML code to create new dimensions and measures, create derived tables and join them to Explores, filter Explores, and define caching policies in LookML.

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In this advanced-level quest, you will learn how to harness serious Google Cloud computing power to run big data and machine learning jobs. The hands-on labs will give you use cases, and you will be tasked with implementing big data and machine learning practices utilized by Google’s very own Solutions Architecture team. From running Big Query analytics on tens of thousands of basketball games, to training TensorFlow image classifiers, you will quickly see why Google Cloud is the go-to platform for running big data and machine learning jobs.

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In this introductory level Quest you will gain practical experience on the fundamentals of sports data science using BigQuery. Start your journey by creating a soccer dataset in BigQuery by importing CSV and JSON files. Harness the power of BigQuery with sophisticated SQL analytical concepts, including using BigQuery ML to train an expected goals model on the soccer event data and evaluate the impressiveness of World Cup goals.

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Earn a skill badge by completing the Migrate MySQL data to Cloud SQL using Database Migration Services quest, where you will learn how to migrate MySQL data to Cloud SQL using Database Migration Services, including how to: connect to Cloud SQL instances using the Cloud Console and with different job types and connectivity options available in Database Migration Service, and migrate MySQL user data when running Database Migration Service jobs. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge quest, and the final assessment challenge lab, to receive a skill badge that you can share with your network.

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This advanced-level quest offers hands-on practice with migrating MySQL data to Cloud SQL using Database Migration Service. You will start with an introductory lab that briefly reviews how to get started with Cloud SQL for MySQL, including how to connect to Cloud SQL instances using the Cloud Console, then continue with two labs focused on migrating MySQL databases to Cloud SQL using different job types and connectivity options available in Database Migration Service. The quest ends with migrating MySQL user data when running Database Migration Service jobs.

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Google Cloud Fundamentals: Core Infrastructure introduces important concepts and terminology for working with Google Cloud. Through videos and hands-on labs, this course presents and compares many of Google Cloud's computing and storage services, along with important resource and policy management tools.

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Big data, machine learning, and scientific data? It sounds like the perfect match. In this advanced-level quest, you will get hands-on practice with GCP services like Big Query, Dataproc, and Tensorflow by applying them to use cases that employ real-life, scientific data sets. By getting experience with tasks like earthquake data analysis and satellite image aggregation, Scientific Data Processing will expand your skill set in big data and machine learning so you can start tackling your own problems across a spectrum of scientific disciplines.

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Blockchain and related technologies, such as distributed ledger and distributed apps, are becoming new value drivers and solution priorities in many industries. In this Quest you will gain hands-on experience with distributed ledger and the exploration of blockchain datasets in Google Cloud. This Quest brings the research and solution work of Google's Allen Day into self-paced labs for you to run and learn directly. Since this Quest utilizes advanced SQL in BigQuery, a SQL-in-BigQuery refresher lab is at the start. The final lab is an advanced challenge-style lab in which there are elements where you are not provided the answer but must solve it for yourself.

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This is the first of two Quests of hands-on labs is derived from the exercises from the book Data Science on Google Cloud Platform, 2nd Edition by Valliappa Lakshmanan, published by O'Reilly Media, Inc. In this first Quest, covering up through chapter 8, you are given the opportunity to practice all aspects of ingestion, preparation, processing, querying, exploring and visualizing data sets using Google Cloud tools and services.

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Want to turn your marketing data into insights and build dashboards? Bring all of your data into one place for large-scale analysis and model building. Get repeatable, scalable, and valuable insights into your data by learning how to query it and using BigQuery. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.

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This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache Beam vision and the benefits of the Beam Portability framework. The Beam Portability framework achieves the vision that a developer can use their favorite programming language with their preferred execution backend. We then show you how Dataflow allows you to separate compute and storage while saving money, and how identity, access, and management tools interact with your Dataflow pipelines. Lastly, we look at how to implement the right security model for your use case on Dataflow.

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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.

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The purpose of this course is to help those who are qualified develop confidence to attempt the exam, and to help those not yet qualified to develop their own plan for preparation.

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Earn a skill badge by completing the Create Conversational AI Agents with Dialogflow CX quest, where you will learn how to create a conversational virtual agent, including how to: define intents and entities, use versions and environments, create conversational branching, and use IVR features. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge quest, and the final assessment challenge lab, to receive a skill badge that you can share with your network.

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In this advanced-level quest, you will learn the ins and outs of developing GCP applications in Python. The first labs will walk you through the basics of environment setup and application data storage with Cloud Datastore. Once you have a handle on the fundamentals, you will get hands-on practice deploying Python applications on Kubernetes and App Engine (the latter is the same framework that powers Snapchat!) With specialized bonus labs that teach user authentication and backend service development, this quest will give you practical experience so you can start developing robust Python applications straight away.

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In this series of labs you will learn how to use BigQuery to analyze NCAA basketball data with SQL. Build a Machine Learning Model to predict the outcomes of NCAA March Madness basketball tournament games.

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Want to learn the core SQL and visualization skills of a Data Analyst? Interested in how to write queries that scale to petabyte-size datasets? Take the BigQuery for Analyst Quest and learn how to query, ingest, optimize, visualize, and even build machine learning models in SQL inside of BigQuery.

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Want to scale your data analysis efforts without managing database hardware? Learn the best practices for querying and getting insights from your data warehouse with this interactive series of BigQuery labs. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.

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Data Catalog is a fully managed and scalable metadata management service that empowers organizations to quickly discover, understand, and manage all of their data. In this quest you will start small by learning how to search and tag data assets and metadata with Data Catalog. After learning how to build your own tag templates that map to BigQuery table data, you will learn how to build MySQL, PostgreSQL, and SQLServer to Data Catalog Connectors.

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Earn a skill badge by completing the Engineer Data in Google Cloud quest, where you will learn how to: Build data pipelines using Cloud Dataprep by Trifacta, Pub/Sub, and Dataflow; Use Cloud IoT Core to collect and manage MQTT-based devices; Use Cloud Storage, Dataflow, and BigQuery to perform ETL; Build a machine learning model using BigQuery ML; Use Cloud Composer to copy data across multiple locations. This quest is a great resource for understanding topics that will appear in the Google Cloud Certified Professional Data Engineer Certification. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the skill badge quest, and final assessment challenge lab, to receive a digital badge that you can share with your network.

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This advanced-level quest is unique amongst the other catalog offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Data Engineer Certification. From Big Query, to Dataprep, to Cloud Composer, this quest is composed of specific labs that will put your Google Cloud data engineering knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, you will need other preparation, too. The exam is quite challenging and external studying, experience, and/or background in cloud data engineering is recommended. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of the Engineer Data in the Google Cloud to receive an exclusive Google Cloud digital badge.

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Looking to build or optimize your data warehouse? Learn best practices to Extract, Transform, and Load your data into Google Cloud with BigQuery. In this series of interactive labs you will create and optimize your own data warehouse using a variety of large-scale BigQuery public datasets. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.

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Cloud SQL is a fully managed database service that stands out from its peers due to high performance, seamless integration, and impressive scalability. In this fundamental-level quest, you will receive hands-on practice with the basics of Cloud SQL and quickly progress to advanced features, which you will apply to production frameworks and application environments. From creating instances and querying data with SQL, to building Deployment Manager scripts and highly available databases that run on GKE containers, Cloud SQL will give you the knowledge and experience needed so you can start integrating this service right away.

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Earn a skill badge by completing the Create and Manage Cloud Resources quest, where you learn how to do the following: Write gcloud commands and use Cloud Shell, create and deploy virtual machines in Compute Engine, run containerized applications on Google Kubernetes Engine, and configure network and HTTP load balancers. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge quest, and the final assessment challenge lab, to receive a skill badge that you can share with your network.

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In this introductory-level Quest, you will get hands-on practice with the Google Cloud’s fundamental tools and services. Google Cloud Essentials is the recommended first Quest for the Google Cloud learner - you will come in with little or no prior cloud knowledge, and come out with practical experience that you can apply to your first Google Cloud project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features. 1-minute videos walk you through key concepts for each lab.

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