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 Platform 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. Learners will get hands-on experience with data lakes and warehouses on Google Cloud Platform using QwikLabs.
ofrecido por
Google CloudAcerca de este Curso
143,935 vistas recientes
Certificado para compartir
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Fechas límite flexibles
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Nivel intermedio
Aprox. 8 horas para completar
Inglés (English)
Subtítulos: Inglés (English), Español (Spanish)
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel intermedio
Aprox. 8 horas para completar
Inglés (English)
Subtítulos: Inglés (English), Español (Spanish)
ofrecido por
Google Cloud
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
Programa - Qué aprenderás en este curso
7 minutos para completar
Introduction
This module gives an introduction of the Data Engineering specialization and the course.
7 minutos para completar
2 videos (Total 7 minutos)
2 horas para completar
Introduction to Data Engineering
This module describes the role of a data engineer and motivates the claim why data engineering should be done in the Cloud
2 horas para completar
13 videos (Total 55 minutos)
13 videos
Analyze data engineering challenges8m
Intro to BigQuery3m
Data Lakes and Data Warehouses5m
Demo: Federated Queries with BigQuery6m
Transactional Databases vs Data Warehouses4m
Partner effectively with other data teams6m
Manage data access and governance2m
Demo: Finding PII in your dataset with DLP API1m
Build production-ready pipelines2m
Review GCP customer case study3m
Recap1m
Lab Intro: Using BigQuery to do Analysis17s
1 ejercicio de práctica
Introduction to Data Engineering30m
2 horas para completar
Building a Data Lake
In this module, we describe what data lake is and how to use Google Cloud Storage as you data lake on GCP
2 horas para completar
10 videos (Total 58 minutos)
10 videos
Data Storage and ETL options on GCP4m
Building a Data Lake using Cloud Storage10m
Demo: Optimizing cost with Google Cloud Storage classes and Cloud Functions7m
Securing Cloud Storage5m
Storing All Sorts of Data Types5m
Demo: Running federated queries on Parquet and ORC files in BigQuery4m
Storing Relational Data in the Cloud1m
Cloud SQL as a relational Data Lake7m
Lab: Loading Taxi Data into Cloud SQL27s
1 ejercicio de práctica
Building a Data Lake4m
4 horas para completar
Building a data warehouse
In this module, we talk about BigQuery as a data warehousing option on GCP
4 horas para completar
17 videos (Total 93 minutos)
17 videos
Intro to BigQuery1m
Demo: Querying TB of Data in seconds7m
Getting Started9m
Loading Data11m
Lab Intro: Loading Data into BigQuery21s
Exploring Schemas24s
Demo: Exploring Schemas10m
Schema Design3m
Nested and Repeated Fields8m
Demo: Nested and Repeated Fields15m
Lab Intro: Working with JSON and Array Data in BigQuery13s
Optimizing with Partitioning and Clustering5m
Demo: Creating Partitioned Tables7m
Demo: Partitioning and Clustering6m
Preview: Transforming Batch and Streaming Data2m
Recap1m
1 ejercicio de práctica
Building a Data Warehouse4m
2 minutos para completar
Summary
This module reviews all the topics covered in the course
2 minutos para completar
1 video (Total 2 minutos)
1 video
Revisiones
Principales revisiones sobre MODERNIZING DATA LAKES AND DATA WAREHOUSES WITH GCP
por AA14 de feb. de 2020
Good introduction and overview of the field of data engineering, data lakes and modern data warehouses and a hands-on walkthrough of all the technologies related to solving these problems on GCP.
por FM16 de abr. de 2020
A better understanding of BigQuery starts here. A vital resource for consultants, data analysts, and product managers, and an important reference source for engineers and data scientists.
por BA8 de feb. de 2020
The course offers a nice description of what modern DWH means, which are the differences between classic DWH and cloud DWH. You have the chance to work with the new cloud concept on GCP.
por AG11 de may. de 2020
Very detailed explanation on Data Lake and Data Ware house and use cases. Concepts of the Data types such as STRUCT and ARRAYS are explained very well and beneficial in Data modeling.
Preguntas Frecuentes
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When will I have access to the lectures and assignments?
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
What will I get when I enroll?
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.
When will I receive my Course Certificate?
If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.
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