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Streaming Data to Bigtable

Google Cloud Training
This is a self-paced lab that takes place in the Google Cloud console. In this lab, you launch a Dataflow pipeline to load streaming data from Pub/Sub into Bigtable.
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides hands-on labs for learners to apply their knowledge
Taught by Google Cloud Training, who are recognized for their expertise in cloud computing
Teaches skills and knowledge that are highly relevant to industry practices
Builds a strong foundation for beginners in data engineering and cloud computing
Focuses on loading streaming data into Bigtable, which is a valuable skill in data management

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Streaming Data to Bigtable with these activities:
Review SQL basics
Strengthen your foundation in SQL to enhance your ability to query and analyze data in Bigtable.
Browse courses on SQL
Show steps
  • Go through online tutorials or resources
  • Practice writing SQL queries
Review Bigtable documentation
Get started with the core concepts of Bigtable by reviewing the Google documentation.
Browse courses on Bigtable
Show steps
  • Visit the Bigtable documentation page
  • Read the Bigtable Overview
  • Read about Bigtable Best Practices
Tutorial: Load data from Pub/Sub into Bigtable with Dataflow and Apache Kafka
Build confidence using Google Cloud services by following a guided tutorial on loading data into Bigtable.
Browse courses on Bigtable
Show steps
  • Visit the tutorial page
  • Follow the instructions to set up the environment
  • Run the Dataflow pipeline
Six other activities
Expand to see all activities and additional details
Show all nine activities
Join a study group to discuss the course content
Engage with fellow learners by discussing the course content, sharing insights, and asking questions.
Show steps
  • Find a study group or create your own
  • Set up a regular meeting time and place
  • Prepare topics for discussion
Practice Dataflow exercises
Reinforce Dataflow concepts by practicing exercises.
Show steps
  • Solve exercises on Dataflow
  • Review solutions and compare with others
  • Identify areas for improvement
Practice loading data into Bigtable from Apache Kafka
Gain hands-on experience with Apache Kafka by practicing loading data into your Bigtable instance.
Browse courses on Apache Kafka
Show steps
  • Create a Pub/Sub topic
  • Configure Apache Kafka to publish data to the topic
  • Create a Bigtable instance
  • Run the Dataflow pipeline
Create a data visualization
Reinforce your understanding of Bigtable by creating visualizations based on your query results.
Browse courses on Data Visualization
Show steps
  • Connect to your Bigtable instance
  • Run a query
  • Export the results to a CSV file
  • Use a data visualization tool to create visualizations
Attend a Bigtable workshop
Deepen your understanding of Bigtable functionalities and applications by attending a workshop.
Browse courses on Data Storage
Show steps
  • Research and find a relevant workshop
  • Reach out to the organizers and register
  • Attend the workshop and actively participate
Help peers with their understanding of Bigtable
Sharpen your understanding of Bigtable by assisting others with their queries and sharing your knowledge.
Show steps
  • Identify opportunities to assist peers
  • Provide clear and concise explanations
  • Encourage peers to ask questions

Career center

Learners who complete Streaming Data to Bigtable will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts use data to understand the performance of a business. They work with data engineers and data scientists to develop data pipelines and with business leaders to understand the data needs of the organization. This course may be useful for Data Analysts who want to learn how to use Google Cloud products to build data pipelines.
See salaries and explore the career path for Data Analyst
Data Engineer
Data Engineers are responsible for designing, building, and maintaining big data systems. They work with data scientists and business analysts to understand the data needs of the organization and develop solutions to meet those needs. This course may be useful for Data Engineers who want to learn how to use Google Cloud products to build data pipelines.
See salaries and explore the career path for Data Engineer
Data Scientist
Data Scientists use data to solve business problems. They work with data engineers to develop data pipelines and with business analysts to understand the data needs of the organization. This course may be useful for Data Scientists who want to learn how to use Google Cloud products to build data pipelines.
See salaries and explore the career path for Data Scientist
Database Administrator
Database Administrators are responsible for the management and maintenance of databases. They work with data engineers and data scientists to develop data pipelines and with business analysts to understand the data needs of the organization. This course may be useful for Database Administrators who want to learn how to use Google Cloud products to build data pipelines.
See salaries and explore the career path for Database Administrator
Big Data Architect
Big Data Architects design and implement big data solutions. They work with data engineers and data scientists to develop data pipelines and with business analysts to understand the data needs of the organization. This course may be useful for Big Data Architects who want to learn how to use Google Cloud products to build data pipelines.
See salaries and explore the career path for Big Data Architect
Cloud Architect
Cloud Architects design and implement cloud computing solutions. They work with data engineers and data scientists to develop data pipelines and with business analysts to understand the data needs of the organization. This course may be useful for Cloud Architects who want to learn how to use Google Cloud products to build data pipelines.
See salaries and explore the career path for Cloud Architect
Data Warehouse Engineer
Data Warehouse Engineers design and implement data warehouse solutions. They work with data engineers and data scientists to develop data pipelines and with business analysts to understand the data needs of the organization. This course may be useful for Data Warehouse Engineers who want to learn how to use Google Cloud products to build data pipelines.
See salaries and explore the career path for Data Warehouse Engineer
Business Intelligence Analyst
Business Intelligence Analysts use data to understand the performance of a business. They work with data engineers and data scientists to develop data pipelines and with business leaders to understand the data needs of the organization. This course may be useful for Business Intelligence Analysts who want to learn how to use Google Cloud products to build data pipelines.
See salaries and explore the career path for Business Intelligence Analyst
Data Quality Analyst
Data Quality Analysts ensure the quality of data in an organization. They work with data engineers and data scientists to develop data pipelines and with business analysts to understand the data needs of the organization. This course may be useful for Data Quality Analysts who want to learn how to use Google Cloud products to build data pipelines.
See salaries and explore the career path for Data Quality Analyst
ETL Developer
ETL Developers design and implement ETL (extract, transform, and load) solutions. They work with data engineers and data scientists to develop data pipelines and with business analysts to understand the data needs of the organization. This course may be useful for ETL Developers who want to learn how to use Google Cloud products to build data pipelines.
See salaries and explore the career path for ETL Developer
Data Governance Analyst
Data Governance Analysts develop and implement data governance policies and procedures. They work with data engineers and data scientists to develop data pipelines and with business analysts to understand the data needs of the organization. This course may be useful for Data Governance Analysts who want to learn how to use Google Cloud products to build data pipelines.
See salaries and explore the career path for Data Governance Analyst
Data Security Analyst
Data Security Analysts ensure the security of data in an organization. They work with data engineers and data scientists to develop data pipelines and with business analysts to understand the data needs of the organization. This course may be useful for Data Security Analysts who want to learn how to use Google Cloud products to build data pipelines.
See salaries and explore the career path for Data Security Analyst
Data Integration Engineer
Data Integration Engineers design and implement data integration solutions. They work with data engineers and data scientists to develop data pipelines and with business analysts to understand the data needs of the organization. This course may be useful for Data Integration Engineers who want to learn how to use Google Cloud products to build data pipelines.
See salaries and explore the career path for Data Integration Engineer
Machine Learning Engineer
Machine Learning Engineers develop and deploy machine learning models. They work with data engineers and data scientists to develop data pipelines and with business analysts to understand the data needs of the organization. This course may be useful for Machine Learning Engineers who want to learn how to use Google Cloud products to build data pipelines.
See salaries and explore the career path for Machine Learning Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. They work with data engineers and data scientists to develop data pipelines and with business analysts to understand the data needs of the organization. This course may be useful for Software Engineers who want to learn how to use Google Cloud products to build data pipelines.
See salaries and explore the career path for Software Engineer

Reading list

We've selected six books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Streaming Data to Bigtable.
Cover image
The Data Warehouse Toolkit
Save
Provides a comprehensive overview of dimensional modeling, a data modeling technique that is well-suited for data warehousing and business intelligence.
The Data Warehouse Toolkit
Paperback
Check
The Data Warehouse Toolkit
Kindle Edition
Check
Cover image
Ethics and Data Science
Save
Provides a practical guide to building and managing data science teams.
Ethics and Data Science
Kindle Edition
Check Price
Cover image
Deep Learning
Save
Provides a comprehensive overview of deep learning, a subfield of machine learning that uses artificial neural networks to learn complex patterns in data.
Deep Learning
Paperback
$$$
Deep Learning (Adaptive Computation and Machine...
Hardcover
$$$
Deep Learning (Adaptive Computation and Machine...
Kindle Edition
$$$
Cover image
Deep Learning with TensorFlow 2 and Keras
Save
Provides a concise overview of TensorFlow, an open-source machine learning library.
Deep Learning with TensorFlow 2 and Keras
Paperback
Check
Deep Learning with TensorFlow 2 and Keras
Kindle Edition
Check
Cover image
Hands-On Machine Learning with Scikit-Learn, Keras,...
Save
Provides a practical guide to machine learning using Python libraries such as Scikit-Learn, Keras, and TensorFlow.
Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
$$
Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
$$$
Hands-On Machine Learning with Scikit-Learn, Keras,...
Kindle Edition
$$
Cover image
Deep Learning with Python, Second Edition
Save
Provides a practical guide to deep learning using Python and the Keras library.
Deep Learning with Python, Second Edition
Paperback
$$
Deep Learning with Python, Second Edition
Kindle Edition
$$

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Time
1 hours
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
This course belongs to a collection called Google Cloud Database Engineer. It's comprised of 16 courses:
  1. Migrating to Cloud SQL from Amazon RDS for MySQL Using Database Migration Service
  2. Designing and Querying Bigtable Schemas
  3. Monitoring and Managing Bigtable Health and Performance
  4. Enterprise Database Migration
  5. Cloud Spanner - Loading Data and Performing Backups
  6. Configure Replication and Enable Point-in-Time-Recovery for Cloud SQL for PostgreSQL
  7. Streaming Data to Bigtable (viewing)
  8. Migrating On-premises MySQL Using a Continuous Database Migration Service Job
  9. Securing a Cloud SQL for PostgreSQL Instance
  10. Connect an App to a Cloud SQL for PostgreSQL Instance
  11. Migrate to Cloud SQL for PostgreSQL using Database Migration Service
  12. Deploy a Modern Web App connected to a Cloud Spanner Instance
  13. Creating and Populating a Bigtable Instance
  14. Cloud Spanner - Defining Schemas and Understanding Query Plans
  15. Cloud SQL for MySQL: Qwik Start
  16. A Tour of Google Cloud Hands-on Labs
Good to know
Provides hands-on labs for learners to apply their knowledge
Taught by Google Cloud Training, who are recognized for their expertise in cloud computing
Teaches skills and knowledge that are highly relevant to industry practices
Builds a strong foundation for beginners in data engineering and cloud computing
Focuses on loading streaming data into Bigtable, which is a valuable skill in data management
Share and help others discover this course.
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