Trophy Arki1, Google Cloud Authorized Training Partner of the year 2019 in Latin America

From Data to Insights com GCP

Este treinamento de três dias ensina aos participantes do curso como obter insights por meio da análise e visualização de dados usando o Google Cloud Platform. O curso apresenta cenários interativos e laboratórios práticos, onde os participantes exploram, exploram, carregam, visualizam e extraem informações de diversos conjuntos de dados do Google BigQuery. O curso também abrange carregamento de dados, consultas, modelagem de esquemas, otimização de desempenho, preços de consultas e visualização de dados.

Público-Alvo

Esta aula destina-se ao seguinte público:
  • Data Analysts,
  • Business Analysts,
  • Business Intelligence professionals,
  • Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on GCP.

Pré-requisitos

Para aproveitar ao máximo este curso, os participantes precisam atender aos seguintes critérios:
  • Proficiência básica em linguagem de consulta comum, como SQL.

Duração

3 dias

Investimento

Consulte o valor atualizado e próximas datas para turmas abertas em nossa página de inscrições. Caso tenha interesse em uma turma fechada para sua empresa, entre em contato conosco.

Resumo do curso

O curso inclui apresentações, demonstrações e laboratórios práticos.
  • Highlight Analytics Challenges Faced by Data Analysts
  • Compare Big Data On-Premises vs on the Cloud
  • Learn from Real-World Use Cases of Companies Transformed through Analytics on the Cloud
  • Navigate Google Cloud Platform Project Basics
  • Walkthrough Data Analyst Tasks, Challenges, and Introduce Google Cloud Platform Data Tools
  • Demo: Analyze 10 Billion Records with Google BigQuery
  • Explore 9 Fundamental Google BigQuery Features
  • Compare GCP Tools for Analysts, Data Scientists, and Data Engineers
  • Lab: BigQuery Basics
  • Compare Common Data Exploration Techniques
  • Learn How to Code High Quality Standard SQL
  • Explore Google BigQuery Public Datasets
  • Visualization Preview: Google Data Studio
  • Lab: Explore your Ecommerce Dataset with SQL in Google BigQuery
  • Examine the 5 Principles of Dataset Integrity
  • Characterize Dataset Shape and Skew
  • Clean and Transform Data using SQL
  • Clean and Transform Data using a new UI: Introducing Cloud Dataprep
  • Lab: Creating a Data Transformation Pipeline with Cloud Dataprep
  • Overview of Data Visualization Principles
  • Exploratory vs Explanatory Analysis Approaches
  • Demo: Google Data Studio UI
  • Connect Google Data Studio to Google BigQuery
  • Lab: How to Build a BI Dashboard Using Google Data Studio and BigQuery
  • Compare Permanent vs Temporary Tables
  • Save and Export Query Results
  • Performance Preview: Query Cache
  • Lab: Ingesting New Datasets into BigQuery
  • Merge Historical Data Tables with UNION
  • Introduce Table Wildcards for Easy Merges
  • Review Data Schemas: Linking Data Across Multiple Tables
  • Walkthrough JOIN Examples and Pitfalls
  • Lab: Troubleshooting and Solving Data Join Pitfalls
  • Review SQL Case Statements
  • Introduce Analytical Window Functions
  • Safeguard Data with One-Way Field Encryption
  • Discuss Effective Sub-query and CTE design
  • Compare SQL and Javascript UDFs
  • Lab: Creating Date-Partitioned Tables in BigQuery
  • Compare Google BigQuery vs Traditional RDBMS Data Architecture
  • Normalization vs Denormalization: Performance Tradeoffs
  • Schema Review: The Good, The Bad, and The Ugly
  • Arrays and Nested Data in Google BigQuery
  • Lab: Querying Nested and Repeated Data
  • Lab: Schema Design for Performance: Arrays and Structs in BigQuery
  • Walkthrough of a BigQuery Job
  • Calculate BigQuery Pricing: Storage, Querying, and Streaming Costs
  • Optimize Queries for Cost
  • Data Security Best Practices
  • Controlling Access with Authorized Views
  • Structured vs Unstructured ML
  • Prebuilt ML models
  • Lab: Extract, Analyze, and Translate Text from Images with the Cloud ML APIs
  • Lab: Training with Pre-built ML Models using Cloud Vision API and AutoML
  • Summary and course wrap-up