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Getting Started with Splunk Cloud GDI on Google Cloud
This is a self-paced lab that takes place in the Google Cloud console. A step-by-step guide through the process to configure multiple methods to ingest Google Cloud data into Splunk. In this hands-on lab you'll learn how to configure Google Cloud to send logging and other infrastructure data to Splunk Cloud via Dataflow, the Splunk Add-on for Google Cloud Platform, and Splunk Connect for Kubernetes (SC4K).
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Course by
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Self Paced
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2 hours
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English
Building Resilient Streaming Analytics Systems on GCP em Português Brasileiro
O processamento de dados de streaming é cada vez mais usado pelas empresas para gerar métricas sobre as operações comerciais em tempo real. Neste curso, você vai aprender a criar pipelines de dados de streaming no Google Cloud. O Pub/Sub é apresentado como a ferramenta para gerenciar dados de streaming de entrada. No curso, também abordamos a aplicação de agregações e transformações a dados de streaming usando o Dataflow, além de formas de armazenar registros processados no BigQuery ou no Cloud Bigtable para análise.
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Course by
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Self Paced
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Portuguese
Serverless Data Processing with Dataflow:Foundations Español
Este curso corresponde a la 1ª parte de una serie de 3 cursos llamada Serverless Data Processing with Dataflow. Para comenzar, en el primer curso haremos un repaso de qué es Apache Beam y cómo se relaciona con Dataflow. Luego, hablaremos sobre la visión de Apache Beam y los beneficios que ofrece su framework de portabilidad. Dicho framework hace posible que un desarrollador pueda usar su lenguaje de programación favorito con su backend de ejecución preferido. Después, le mostraremos cómo Dataflow le permite separar el procesamiento y el almacenamiento y, a la vez, ahorrar dinero.
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Course by
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Self Paced
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Spanish
Serverless Data Processing with Dataflow: Operations em Português Brasileiro
Na última parte da série de cursos do Dataflow, vamos abordar os componentes do modelo operacional do Dataflow. Veremos ferramentas e técnicas para solucionar problemas e otimizar o desempenho do pipeline. Depois analisaremos as práticas recomendadas de teste, implantação e confiabilidade para pipelines do Dataflow. Por fim, faremos uma revisão dos modelos, que facilitam o escalonamento dos pipelines do Dataflow para organizações com centenas de usuários. Essas lições garantem que a plataforma de dados seja estável e resiliente a circunstâncias imprevistas.
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Course by
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Self Paced
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Portuguese
Serverless Data Processing with Dataflow: Develop Pipelines em Português Brasileiro
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.
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Course by
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Self Paced
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Portuguese
Serverless Data Analysis with Google BigQuery and Cloud Dataflow em Português Brasileiro
Este curso rápido sob demanda tem uma semana de duração e é baseado no Google Cloud Platform Big Data and Machine Learning Fundamentals.
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Course by
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Self Paced
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Portuguese
Building Resilient Streaming Analytics Systems on GCP en Español
El procesamiento de datos de transmisión es cada vez más popular, puesto que permite a las empresas obtener métricas en tiempo real sobre las operaciones comerciales. Este curso aborda cómo crear canalizaciones de datos de transmisión en Google Cloud. Pub/Sub se describe para manejar los datos de transmisión entrantes. El curso también aborda cómo aplicar agregaciones y transformaciones a los datos de transmisión con Dataflow y cómo almacenar los registros procesados en BigQuery o Bigtable para analizarlos.
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Course by
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Self Paced
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Spanish
SingleStore on Google Cloud
This is a self-paced lab that takes place in the Google Cloud console. Learn how to deploy SingleStore DB, combine it with cloud native products like Pub/Sub, Dataflow and Cloud Storage, and interact with SingleStore once the data is ingested.
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Course by
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Self Paced
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2 hours
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English
Visualize Real Time Geospatial Data with Google Data Studio
This is a self-paced lab that takes place in the Google Cloud console. Use Google Dataflow to process real-time streaming data from a real-time real world historical data set, storing the results in Google BigQuery and t…
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Course by
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Self Paced
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English
Serverless Data Processing with Dataflow: Operations
In the last installment of the Dataflow course series, we will introduce the components of the Dataflow operational model. We will examine tools and techniques for troubleshooting and optimizing pipeline performance. We will then review testing, deployment, and reliability best practices for Dataflow pipelines. We will conclude with a review of Templates, which makes it easy to scale Dataflow pipelines to organizations with hundreds of users. These lessons will help ensure that your data platform is stable and resilient to unanticipated circumstances.
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Course by
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Self Paced
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10 hours
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English
Datastream MySQL to BigQuery
This is a self-paced lab that takes place in the Google Cloud console. Learn to migrate MySQL Databases to BigQuery using Datastream and Dataflow. Datastream is a serverless and easy-to-use Change Data Capture (CDC) an…
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Course by
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Self Paced
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English
Dataflow: Qwik Start - Python
This is a self-paced lab that takes place in the Google Cloud console. In this lab you will set up your Python development environment, get the Cloud Dataflow SDK for Python, and run an example pipeline using the Google Cloud Platform Console.
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Course by
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Self Paced
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1 hour
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English
Serverless Data Processing with Dataflow: Develop Pipelines
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.
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Course by
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Self Paced
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19 hours
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English
Data Engineer, Big Data and ML on Google Cloud em Português
Nesta especialização on-line intensiva de cinco semanas, os participantes terão uma introdução prática sobre como projetar e criar sistemas de processamento de dados no Google Cloud Platform. Por meio de uma combinação de apresentações, demonstrações e laboratórios práticos, os participantes aprenderão a projetar sistemas de processamento de dados, criar canais completos e análises de dados e desenvolver soluções de aprendizado de máquina.
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Course by
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Self Paced
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Portuguese
Processing Data with Google Cloud Dataflow
This is a self-paced lab that takes place in the Google Cloud console. In this lab you will simulate a real-time real world data set from a historical data set. This simulated data set will be processed from a set of tex…
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Course by
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Self Paced
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English
Real Time Machine Learning with Cloud Dataflow and Vertex AI
This is a self-paced lab that takes place in the Google Cloud console. Implement a real-time, streaming machine learning pipeline that uses Cloud Dataflow and Vertex AI.…
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Course by
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Self Paced
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English
Configuring MongoDB Atlas with BigQuery Dataflow Templates
This is a self-paced lab that takes place in the Google Cloud console. In this lab you will provision a MongoDB Atlas cluster, create a dataflow pipeline to load data from the cluster to BigQuery
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Course by
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Self Paced
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1 hour
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English
ETL Processing on Google Cloud Using Dataflow and BigQuery
This is a self-paced lab that takes place in the Google Cloud console. In this lab you will build several Data Pipelines that will ingest data from a publicly available dataset into BigQuery.
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Course by
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Self Paced
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1 hour
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English
Reconciling Account Data with Cloud Spanner Change Streams
This is a self-paced lab that takes place in the Google Cloud console. Learn how to perform financial account reconciliation tasks using Cloud Spanner, Dataflow, and BigQuery.
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Course by
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Self Paced
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1 hour
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English
Dataflow: Qwik Start - Templates
This is a self-paced lab that takes place in the Google Cloud console. This page shows you how to create a streaming pipeline using a Google-Provided Cloud Dataflow template.
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Course by
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Self Paced
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1 hour
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English
Machine Learning in the Enterprise - 한국어
이 과정에서는 다양한 ML 비즈니스 요구사항과 사용 사례를 다루는 ML팀의 우수사례를 중심으로 ML 워크플로에 대한 실용적이고 현실적인 접근 방식을 포괄적으로 소개합니다. 이 팀은 데이터 관리 및 거버넌스에 필요한 도구를 이해하고, Dataflow 및 Dataprep에 대한 개괄적인 지식과 BigQuery를 사용한 사전 처리 작업 등을 바탕으로 데이터 사전 처리를 위한 가장 효과적인 접근 방식을 검토해야 합니다. 팀은 두 가지 구체적인 사용 사례에 맞는 머신러닝 모델을 빌드하는 세 가지 옵션을 제공합니다. 이 과정에서는 팀이 목표 달성을 위해 AutoML, BigQuery ML 또는 커스텀 학습을 사용해야 하는 이유를 설명합니다. 커스텀 학습에 대해서도 자세히 설명합니다. 학습 코드 구조, 스토리지, 대용량 데이터 세트 로드에서 학습된 모델 내보내기에 이르기까지 커스텀 학습 요구사항을 설명합니다. Docker에 대한 지식이 거의 없어도 컨테이너 이미지를 빌드할 수 있는 커스텀 학습 머신러닝 모델을 빌드합니다. 우수사례팀에서 Vertex Vizier를 사용한 초매개변수 조정과 모델 성능을 개선하는 데 이를 어떻게 활용할 수 있는지 연구합니다.
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Course by
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Self Paced
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English
Quantitative Formal Modeling and Worst-Case Performance Analysis
Welcome to "Quantitative Formal Modeling and Worst-Case Performance Analysis," an intellectually stimulating course designed to hone your abstract thinking skills in the realm of theoretical computer science. This course invites you to dive deep into the world of token production and consumption, a foundational approach to system behaviour. Master the art of mathematically formalizing these concepts through prefix orders and counting functions. Get hands-on with Petri-nets, explore the nuances of timing, and delve into the scheduling intricacies of token systems.
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Course by
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Self Paced
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17 hours
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English
Serverless Data Processing with Dataflow: Foundations
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.
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Course by
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Self Paced
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3 hours
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English
Stream Processing with Cloud Pub/Sub and Dataflow: Qwik Start
This is a self-paced lab that takes place in the Google Cloud console. This quickstart shows you how to use Dataflow to read messages published to a Pub/Sub topic, window (or group) the messages by timestamp, and Write the messages to Cloud Storage.
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Course by
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Self Paced
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1 hour
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English
Serverless Data Processing with Dataflow
It is becoming harder and harder to maintain a technology stack that can keep up with the growing demands of a data-driven business. Every Big Data practitioner is familiar with the three V’s of Big Data: volume, velocity, and variety. What if there was a scale-proof technology that was designed to meet these demands? Enter Google Cloud Dataflow. Google Cloud Dataflow simplifies data processing by unifying batch & stream processing and providing a serverless experience that allows users to focus on analytics, not infrastructure.
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Course by
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Self Paced
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English