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Janani Ravi
Google Bigtable is a sophisticated NoSQL offering on the Google Cloud Platform with extremely low latencies. By the end of this course, you'll understand why Bigtable is much more powerful offering than HBase, with linear scaling of your data.
Bigtable is Google’s proprietary storage service that offers extremely fast read and write speeds. It uses a sophisticated internal architecture which learns access patterns and moves around your data to mitigate the issue of hot-spotting.
Read more
Google Bigtable is a sophisticated NoSQL offering on the Google Cloud Platform with extremely low latencies. By the end of this course, you'll understand why Bigtable is much more powerful offering than HBase, with linear scaling of your data.
Bigtable is Google’s proprietary storage service that offers extremely fast read and write speeds. It uses a sophisticated internal architecture which learns access patterns and moves around your data to mitigate the issue of hot-spotting.
Read more
Google Bigtable is a sophisticated NoSQL offering on the Google Cloud Platform with extremely low latencies. By the end of this course, you'll understand why Bigtable is much more powerful offering than HBase, with linear scaling of your data.
Bigtable is Google’s proprietary storage service that offers extremely fast read and write speeds. It uses a sophisticated internal architecture which learns access patterns and moves around your data to mitigate the issue of hot-spotting.
In this course, Architecting Big Data Solutions Using Google Bigtable, you’ll learn both the conceptual and practical aspects of working with Bigtable. You’ll learn how to best to design your schema to enable fast reads and write speeds and discover how data in Bigtable can be accessed using the command line as well as client libraries.
First, you’ll study the internal architecture of Bigtable and how data is stored within it using the 4-dimensional data model. You’ll also discover how Bigtable clusters, nodes, and instances work and how Bigtable works with Colossus - Google’s proprietary storage system behind the scenes.
Next, you’ll access Bigtable using both the HBase shell as well as cbt, Google’s command line utility. Later, you'll create and manage tables while practice exporting and importing data using sequence files.
Finally, you’ll study how manual fail-overs can be handled when we have single cluster routing enabled.
At the end of this course, you’ll be comfortable working with Bigtable using both the command line as well as client libraries.
This course is no longer available. Find something similar by browsing:
Bigtable
NoSQL
Data Modelling
Data Storage
Data Management
HBase
Scalability
Register for this course and see more details by visiting:
OpenCourser.com/course/wus22q/architecting
What's inside
Syllabus
Course Overview
Introducing Cloud Bigtable
Interacting with Cloud Bigtable Using cbt and the HBase API
Managing Cloud Bigtable Instances, Clusters, and Nodes
Read more
Syllabus
Course Overview
Introducing Cloud Bigtable
Interacting with Cloud Bigtable Using cbt and the HBase API
Managing Cloud Bigtable Instances, Clusters, and Nodes
Read more
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Course is suitable for people who want to better understand why Bigtable is a more powerful offering than HBase
Provides hands-on practice with methods to export and import data using sequence files
Introduces Bigtable's internal architecture and four-dimensional data model
Teaches how to create and manage tables, ensuring fast reads and writes
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Reviews summary
Google bigtable: architecture and practical use
According to students, this course offers a strong conceptual and practical understanding of Google Bigtable. Learners particularly praise the in-depth coverage of Bigtable's internal architecture and how data is stored. Many found the hands-on activities, especially those involving the `cbt` command-line utility and HBase API, to be highly beneficial for practical application. The principles of effective schema design for optimal performance are frequently highlighted as a significant positive. However, some learners noted that the course assumes a baseline familiarity with Google Cloud Platform or NoSQL concepts, which might pose a challenge for absolute beginners. There's also feedback indicating a desire for more advanced topics or real-world complex scenarios beyond the foundational material.
Valuable insights into designing optimized Bigtable schemas.
"The section on schema design was incredibly valuable, directly applicable to my work."
"I learned how to best design my schema to enable fast reads and write speeds."
"Understanding best practices for data modeling in Bigtable was a key takeaway from this course."
Effective hands-on practice with Bigtable using cbt and HBase API.
"The hands-on coding and projects using `cbt` and the HBase API are the strongest part of the course for me."
"I found the practical exercises extremely useful for gaining confidence in interacting with Bigtable."
"Learning to access Bigtable via command line and client libraries was very practical and well-covered."
Provides strong conceptual understanding of Bigtable's internal workings.
"The internal architecture of Bigtable was explained so clearly; it made complex concepts easy to grasp."
"I appreciated the depth of coverage on how data is stored and managed within Bigtable."
"Understanding Bigtable's sophisticated internal architecture was a highlight for me."
Could benefit from more advanced topics and complex use cases.
"While comprehensive, I wish it covered more advanced topics like Bigtable replication or security in depth."
"Good foundational course, but could use more in-depth coverage on complex topics or optimization techniques."
"I was hoping for more real-world, large-scale project examples to solidify my understanding further."
Requires some prior knowledge of NoSQL or Google Cloud Platform.
"This course assumes a certain level of familiarity with GCP, which made it challenging for me as a beginner."
"Could be difficult for those without prior NoSQL experience; the pace is quite fast in parts."
"I think some more introductory content for absolute beginners would be beneficial to follow along easily."
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 Architecting Big Data Solutions Using Google Bigtable with these
activities:
Review basic data modeling concepts
Show steps
Strengthen your foundation in data modeling to enhance your understanding of Bigtable's schema design capabilities.
Browse courses on
Data Modeling
Show steps
-
Review the basics of data modeling, including entities, attributes, and relationships.
-
Explore different data modeling techniques, such as normalization and denormalization.
-
Apply your understanding to create a simple data model for a hypothetical scenario.
Review background reading
Show steps
Understand the fundamentals of Google Cloud Platform, NoSQL, and Bigtable to enhance comprehension of the course material.
View
Google Cloud Platform for Architects: Design...
on Amazon
Show steps
-
Read chapters 1-3 to gain an overview of Google Cloud Platform and Bigtable.
-
Summarize the key concepts of NoSQL databases.
-
Identify the key features and benefits of Bigtable.
Solve Bigtable coding challenges
Show steps
Sharpen your Bigtable coding skills and prepare for real-world scenarios.
Browse courses on
Bigtable
Show steps
-
Find Bigtable coding challenges online
-
Solve the challenges using the Bigtable API
-
Review your solutions and identify areas for improvement
16 other activities
Expand to see all activities and additional details
Show all 19 activities
Learn about Bigtable Data Storage and Performance Optimization
Show steps
Become familiar with Bigtable data storage and techniques to optimize performance for better learning outcomes in this course.
Browse courses on
Cloud Storage
Show steps
-
Watch a video tutorial on Bigtable data storage.
-
Read a blog post on Bigtable performance optimization.
Explore Google Cloud Platform Bigtable documentation
Show steps
Enhance your understanding of Bigtable by delving into the official Google Cloud Platform documentation.
Show steps
-
Navigate to the Google Cloud Platform Bigtable documentation website.
-
Review the introductory pages to gain an overview of Bigtable's capabilities.
-
Explore the documentation on creating and managing Bigtable instances and tables.
-
Refer to the documentation as you progress through the course for specific technical details.
Participate in a Bigtable Study Group
Show steps
Enhance your understanding of Bigtable through discussions and collaboration with peers.
Show steps
-
Find a study group or create your own.
-
Set regular meeting times.
-
Discuss course material, work on exercises together, and share knowledge.
Practice Data Modeling
Show steps
Develop your skills in designing and optimizing data models for Bigtable.
Show steps
-
Review the Bigtable data model and best practices.
-
Design a data model for a real-world use case.
-
Implement the data model in Bigtable.
-
Query the data using the HBase API.
Build a simple web application that uses Bigtable as its database
Show steps
Gain hands-on experience with Bigtable and learn how to use it to store and retrieve data in a real-world application.
Browse courses on
Bigtable
Show steps
-
Design the schema for your Bigtable table
-
Create a web application that uses the Bigtable table to store and retrieve data
-
Deploy your web application and test its functionality
Practice Creating Bigtable Tables and Managing Data
Show steps
Creating tables and managing data within the tables is an important skill to master in Bigtable. Regular practice will lead to increased confidence.
Show steps
-
Connect to a Bigtable instance using the command line tools.
-
Create a new table with a defined schema.
-
Write rows to the table.
-
Read data from the table.
-
Delete data from the table.
Discuss Bigtable architecture and performance
Show steps
Engage with peers to exchange insights and deepen your understanding of Bigtable's architecture and performance considerations.
Browse courses on
Performance Optimization
Show steps
-
Join or create a study group or discussion forum dedicated to Bigtable.
-
Present a topic related to Bigtable architecture or performance.
-
Actively participate in discussions, sharing your perspectives and asking clarifying questions.
-
Summarize key takeaways from the discussions and document them for future reference.
Build a Real-Time Data Pipeline with Cloud Bigtable
Show steps
Gain hands-on experience building and managing a data pipeline that uses Bigtable.
Show steps
-
Follow a tutorial on building a data pipeline with Cloud Bigtable.
-
Set up a data source and a data sink.
-
Write code to transform and load data into Bigtable.
-
Monitor the pipeline and make adjustments as needed.
Create a blog post about Bigtable and its use cases
Show steps
Solidify your understanding of Bigtable's strengths and how it can be used in real-world applications.
Browse courses on
Bigtable
Show steps
-
Research Bigtable and its features
-
Identify a specific use case for Bigtable
-
Design and implement a Bigtable table for your use case
-
Write a blog post describing your use case and how Bigtable met your requirements
Create and manage Bigtable tables
Show steps
Solidify your understanding of Bigtable data modeling and schema design by creating and managing tables.
Browse courses on
Data Modeling
Show steps
-
Create a Bigtable instance and cluster using the Google Cloud Platform Console.
-
Design a schema for your table, considering data types and column families.
-
Create the table using the Google Cloud Platform Console or SDK.
-
Insert data into the table using the command line or a client library.
-
Retrieve data from the table and analyze its structure.
Develop a Bigtable Schema Design
Show steps
Demonstrate your understanding of Bigtable's data model by designing a schema for a complex real-world use case.
Show steps
-
Identify the data requirements for the use case.
-
Design a data model that meets the requirements.
-
Create a detailed schema design document.
-
Present the design to a team of engineers.
Contribute to the HBase Community
Show steps
Deepen your understanding of Bigtable and make a valuable contribution to the open-source community.
Show steps
-
Find a project to contribute to on the HBase GitHub repository.
-
Fork the repository and make changes to the code.
-
Submit a pull request and work with the community to get your changes merged.
Attend a workshop on Bigtable best practices
Show steps
Complement your theoretical knowledge with hands-on experience by attending a workshop focused on Bigtable best practices.
Browse courses on
Hands-On Learning
Show steps
-
Research and identify workshops or conferences that cover Bigtable best practices.
-
Register for a workshop that aligns with your learning objectives.
-
Actively participate in the workshop, asking questions and taking notes.
-
Apply the techniques and strategies learned to your own Bigtable projects.
Mentor a Junior Bigtable Engineer
Show steps
Reinforce your knowledge by sharing it with others and fostering their growth in the field.
Show steps
-
Identify a junior engineer who is interested in learning about Bigtable.
-
Set up regular mentoring sessions.
-
Share your knowledge and experience.
-
Provide guidance and support.
Design a Bigtable schema for a real-world scenario
Show steps
Apply your knowledge to a practical scenario by designing a Bigtable schema for a real-world dataset.
Show steps
-
Identify a real-world dataset that could benefit from Bigtable's capabilities.
-
Analyze the data and determine the optimal column families and data types.
-
Design a schema that optimizes performance and scalability.
-
Create a detailed document outlining your design decisions.
-
Share your schema design with a mentor or peer for feedback.
Participate in a Bigtable hackathon
Show steps
Challenge yourself by participating in a Bigtable hackathon, applying your skills to solve real-world data problems.
Browse courses on
Problem-Solving
Show steps
-
Identify and register for a Bigtable hackathon that aligns with your interests.
-
Form a team or work independently on a project that leverages Bigtable.
-
Develop a solution that addresses a specific problem or demonstrates innovative use of Bigtable.
-
Present your project to a panel of judges.
-
Receive feedback and insights on your solution.
Review basic data modeling concepts
Show steps
Strengthen your foundation in data modeling to enhance your understanding of Bigtable's schema design capabilities.
Browse courses on
Data Modeling
Show steps
Show steps
Show steps
- Review the basics of data modeling, including entities, attributes, and relationships.
- Explore different data modeling techniques, such as normalization and denormalization.
- Apply your understanding to create a simple data model for a hypothetical scenario.
Review background reading
Show steps
Understand the fundamentals of Google Cloud Platform, NoSQL, and Bigtable to enhance comprehension of the course material.
View
Google Cloud Platform for Architects: Design...
on Amazon
Show steps
Show steps
Show steps
- Read chapters 1-3 to gain an overview of Google Cloud Platform and Bigtable.
- Summarize the key concepts of NoSQL databases.
- Identify the key features and benefits of Bigtable.
Solve Bigtable coding challenges
Show steps
Sharpen your Bigtable coding skills and prepare for real-world scenarios.
Browse courses on
Bigtable
Show steps
Show steps
Show steps
- Find Bigtable coding challenges online
- Solve the challenges using the Bigtable API
- Review your solutions and identify areas for improvement
16 other activities
Expand to see all activities and additional details
Show all 19 activities
Learn about Bigtable Data Storage and Performance Optimization
Show steps
Become familiar with Bigtable data storage and techniques to optimize performance for better learning outcomes in this course.
Browse courses on
Cloud Storage
Show steps
Show steps
Show steps
- Watch a video tutorial on Bigtable data storage.
- Read a blog post on Bigtable performance optimization.
Explore Google Cloud Platform Bigtable documentation
Show steps
Enhance your understanding of Bigtable by delving into the official Google Cloud Platform documentation.
Show steps
Show steps
Show steps
- Navigate to the Google Cloud Platform Bigtable documentation website.
- Review the introductory pages to gain an overview of Bigtable's capabilities.
- Explore the documentation on creating and managing Bigtable instances and tables.
- Refer to the documentation as you progress through the course for specific technical details.
Participate in a Bigtable Study Group
Show steps
Enhance your understanding of Bigtable through discussions and collaboration with peers.
Show steps
Show steps
Show steps
- Find a study group or create your own.
- Set regular meeting times.
- Discuss course material, work on exercises together, and share knowledge.
Practice Data Modeling
Show steps
Develop your skills in designing and optimizing data models for Bigtable.
Show steps
Show steps
Show steps
- Review the Bigtable data model and best practices.
- Design a data model for a real-world use case.
- Implement the data model in Bigtable.
- Query the data using the HBase API.
Build a simple web application that uses Bigtable as its database
Show steps
Gain hands-on experience with Bigtable and learn how to use it to store and retrieve data in a real-world application.
Browse courses on
Bigtable
Show steps
Show steps
Show steps
- Design the schema for your Bigtable table
- Create a web application that uses the Bigtable table to store and retrieve data
- Deploy your web application and test its functionality
Practice Creating Bigtable Tables and Managing Data
Show steps
Creating tables and managing data within the tables is an important skill to master in Bigtable. Regular practice will lead to increased confidence.
Show steps
Show steps
Show steps
- Connect to a Bigtable instance using the command line tools.
- Create a new table with a defined schema.
- Write rows to the table.
- Read data from the table.
- Delete data from the table.
Discuss Bigtable architecture and performance
Show steps
Engage with peers to exchange insights and deepen your understanding of Bigtable's architecture and performance considerations.
Browse courses on
Performance Optimization
Show steps
Show steps
Show steps
- Join or create a study group or discussion forum dedicated to Bigtable.
- Present a topic related to Bigtable architecture or performance.
- Actively participate in discussions, sharing your perspectives and asking clarifying questions.
- Summarize key takeaways from the discussions and document them for future reference.
Build a Real-Time Data Pipeline with Cloud Bigtable
Show steps
Gain hands-on experience building and managing a data pipeline that uses Bigtable.
Show steps
Show steps
Show steps
- Follow a tutorial on building a data pipeline with Cloud Bigtable.
- Set up a data source and a data sink.
- Write code to transform and load data into Bigtable.
- Monitor the pipeline and make adjustments as needed.
Create a blog post about Bigtable and its use cases
Show steps
Solidify your understanding of Bigtable's strengths and how it can be used in real-world applications.
Browse courses on
Bigtable
Show steps
Show steps
Show steps
- Research Bigtable and its features
- Identify a specific use case for Bigtable
- Design and implement a Bigtable table for your use case
- Write a blog post describing your use case and how Bigtable met your requirements
Create and manage Bigtable tables
Show steps
Solidify your understanding of Bigtable data modeling and schema design by creating and managing tables.
Browse courses on
Data Modeling
Show steps
Show steps
Show steps
- Create a Bigtable instance and cluster using the Google Cloud Platform Console.
- Design a schema for your table, considering data types and column families.
- Create the table using the Google Cloud Platform Console or SDK.
- Insert data into the table using the command line or a client library.
- Retrieve data from the table and analyze its structure.
Develop a Bigtable Schema Design
Show steps
Demonstrate your understanding of Bigtable's data model by designing a schema for a complex real-world use case.
Show steps
Show steps
Show steps
- Identify the data requirements for the use case.
- Design a data model that meets the requirements.
- Create a detailed schema design document.
- Present the design to a team of engineers.
Contribute to the HBase Community
Show steps
Deepen your understanding of Bigtable and make a valuable contribution to the open-source community.
Show steps
Show steps
Show steps
- Find a project to contribute to on the HBase GitHub repository.
- Fork the repository and make changes to the code.
- Submit a pull request and work with the community to get your changes merged.
Attend a workshop on Bigtable best practices
Show steps
Complement your theoretical knowledge with hands-on experience by attending a workshop focused on Bigtable best practices.
Browse courses on
Hands-On Learning
Show steps
Show steps
Show steps
- Research and identify workshops or conferences that cover Bigtable best practices.
- Register for a workshop that aligns with your learning objectives.
- Actively participate in the workshop, asking questions and taking notes.
- Apply the techniques and strategies learned to your own Bigtable projects.
Mentor a Junior Bigtable Engineer
Show steps
Reinforce your knowledge by sharing it with others and fostering their growth in the field.
Show steps
Show steps
Show steps
- Identify a junior engineer who is interested in learning about Bigtable.
- Set up regular mentoring sessions.
- Share your knowledge and experience.
- Provide guidance and support.
Design a Bigtable schema for a real-world scenario
Show steps
Apply your knowledge to a practical scenario by designing a Bigtable schema for a real-world dataset.
Show steps
Show steps
Show steps
- Identify a real-world dataset that could benefit from Bigtable's capabilities.
- Analyze the data and determine the optimal column families and data types.
- Design a schema that optimizes performance and scalability.
- Create a detailed document outlining your design decisions.
- Share your schema design with a mentor or peer for feedback.
Participate in a Bigtable hackathon
Show steps
Challenge yourself by participating in a Bigtable hackathon, applying your skills to solve real-world data problems.
Browse courses on
Problem-Solving
Show steps
Show steps
Show steps
- Identify and register for a Bigtable hackathon that aligns with your interests.
- Form a team or work independently on a project that leverages Bigtable.
- Develop a solution that addresses a specific problem or demonstrates innovative use of Bigtable.
- Present your project to a panel of judges.
- Receive feedback and insights on your solution.
Career center
Learners who complete Architecting Big Data Solutions Using Google Bigtable will develop knowledge and skills
that may be useful to these careers:
Big Data Architect
Big Data Architect
Big Data Architects are responsible for designing, implementing, and managing big data solutions. They work with a variety of big data technologies, including Google Bigtable. This course can help you build a strong foundation in Bigtable, which will make you a more effective Big Data Architect. You will learn how to design and implement Bigtable schemas, how to manage Bigtable clusters, and how to use Bigtable to build big data applications.
Data Engineer
Data Engineer
Data Engineers are responsible for designing, building, and maintaining data pipelines. They work with a variety of data technologies, including Google Bigtable. This course can help you build a strong foundation in Bigtable, which will make you a more effective Data Engineer. You will learn how to design and implement Bigtable schemas, how to manage Bigtable clusters, and how to use Bigtable to build data pipelines.
Data Scientist
Data Scientist
Data Scientists are responsible for analyzing data to find patterns and trends. They work with a variety of data technologies, including Google Bigtable. This course can help you build a strong foundation in Bigtable, which will make you a more effective Data Scientist. You will learn how to design and implement Bigtable schemas, how to manage Bigtable clusters, and how to use Bigtable to build data science applications.
Software Engineer
Software Engineer
Software Engineers are responsible for designing, developing, and maintaining software applications. They work with a variety of technologies, including Google Bigtable. This course can help you build a strong foundation in Bigtable, which will make you a more effective Software Engineer. You will learn how to design and implement Bigtable schemas, how to manage Bigtable clusters, and how to use Bigtable to build software applications.
Cloud Architect
Cloud Architect
Cloud Architects are responsible for designing and implementing cloud-based solutions. They work with a variety of cloud technologies, including Google Bigtable. This course can help you build a strong foundation in Bigtable, which will make you a more effective Cloud Architect. You will learn how to design and implement Bigtable schemas, how to manage Bigtable clusters, and how to use Bigtable to build cloud-based applications.
Database Administrator
Database Administrator
Database Administrators are responsible for managing and maintaining databases. They work with a variety of database technologies, including Google Bigtable. This course can help you build a strong foundation in Bigtable, which will make you a more effective Database Administrator. You will learn how to design and implement Bigtable schemas, how to manage Bigtable clusters, and how to use Bigtable to build database applications.
DevOps Engineer
DevOps Engineer
DevOps Engineers are responsible for bridging the gap between development and operations. They work with a variety of technologies, including Google Bigtable. This course can help you build a strong foundation in Bigtable, which will make you a more effective DevOps Engineer. You will learn how to design and implement Bigtable schemas, how to manage Bigtable clusters, and how to use Bigtable to build DevOps pipelines.
Data Analyst
Data Analyst
Data Analysts are responsible for analyzing data to find patterns and trends. They work with a variety of data technologies, including Google Bigtable. This course can help you build a strong foundation in Bigtable, which will make you a more effective Data Analyst. You will learn how to design and implement Bigtable schemas, how to manage Bigtable clusters, and how to use Bigtable to build data analysis applications.
Business Analyst
Business Analyst
Business Analysts are responsible for analyzing business processes and identifying opportunities for improvement. They work with a variety of technologies, including Google Bigtable. This course can help you build a strong foundation in Bigtable, which will make you a more effective Business Analyst. You will learn how to design and implement Bigtable schemas, how to manage Bigtable clusters, and how to use Bigtable to build business analysis applications.
Product Manager
Product Manager
Product Managers are responsible for managing the development and launch of new products. They work with a variety of technologies, including Google Bigtable. This course can help you build a strong foundation in Bigtable, which will make you a more effective Product Manager. You will learn how to design and implement Bigtable schemas, how to manage Bigtable clusters, and how to use Bigtable to build new products.
Project Manager
Project Manager
Project Managers are responsible for planning and executing projects. They work with a variety of technologies, including Google Bigtable. This course can help you build a strong foundation in Bigtable, which will make you a more effective Project Manager. You will learn how to design and implement Bigtable schemas, how to manage Bigtable clusters, and how to use Bigtable to build project management applications.
Technical Writer
Technical Writer
Technical Writers are responsible for writing technical documentation. They work with a variety of technologies, including Google Bigtable. This course can help you build a strong foundation in Bigtable, which will make you a more effective Technical Writer. You will learn how to design and implement Bigtable schemas, how to manage Bigtable clusters, and how to use Bigtable to build technical documentation.
Quality Assurance Analyst
Quality Assurance Analyst
Quality Assurance Analysts are responsible for testing and verifying the quality of software applications. They work with a variety of technologies, including Google Bigtable. This course can help you build a strong foundation in Bigtable, which will make you a more effective Quality Assurance Analyst. You will learn how to design and implement Bigtable schemas, how to manage Bigtable clusters, and how to use Bigtable to build quality assurance applications.
Sales Engineer
Sales Engineer
Sales Engineers are responsible for selling and supporting software applications. They work with a variety of tecnologías, including Google Bigtable. This course can help you build a strong foundation in Bigtable, which will make you a more effective Sales Engineer. You will learn how to design and implement Bigtable schemas, how to manage Bigtable clusters, and how to use Bigtable to build sales and support applications.
Customer Success Manager
Customer Success Manager
Customer Success Managers are responsible for ensuring the satisfaction of customers. They work with a variety of tecnologías, including Google Bigtable. This course can help you build a strong foundation in Bigtable, which will make you a more effective Customer Success Manager. You will learn how to design and implement Bigtable schemas, how to manage Bigtable clusters, and how to use Bigtable to build customer success applications.
For more career information including salaries, visit:
OpenCourser.com/course/wus22q/architecting
Reading list
We've selected 13 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
Architecting Big Data Solutions Using Google Bigtable.
Provides a comprehensive overview of HBase, the open-source NoSQL database that is the inspiration for Bigtable. It valuable resource for anyone looking to learn more about HBase or Bigtable.
Provides a gentle introduction to NoSQL databases, including Bigtable. It good starting point for anyone who is new to NoSQL databases.
Provides a comprehensive overview of the principles and patterns for designing data-intensive applications. It valuable resource for anyone who wants to learn more about how to design and build scalable, reliable, and efficient data-intensive applications.
Provides a comprehensive overview of big data analytics, including how to use Hadoop and Spark to process and analyze big data. It valuable resource for anyone looking to learn more about big data analytics.
Save
Provides a comprehensive overview of deep learning with big data, including how to use Bigtable to store and process big data. It valuable resource for anyone looking to learn more about deep learning with big data.
Provides a comprehensive overview of HBase, covering its architecture, features, and best practices. It valuable resource for anyone who wants to learn more about HBase and how to use it effectively.
Introduces Big Data Analytics, Cloud Bigtable, and Google Cloud Platform. It contains a wide range of case studies and examples that demonstrate how to use Cloud Bigtable to solve real-world problems.
Provides a comprehensive list of definitions for terms related to big data. It valuable resource for anyone who wants to learn more about the terminology used in the big data industry.
Provides a non-technical overview of the impact of Big Data on society. It valuable resource for anyone who wants to learn more about the potential benefits and challenges of Big Data.
Provides a comprehensive overview of data science, covering its methods and applications. It valuable resource for anyone who wants to learn more about data science and how it can be used to solve business problems.
Provides a non-technical overview of machine learning. It valuable resource for anyone who wants to learn more about machine learning and how it can be used to solve real-world problems.
Save
Provides a thought-provoking look at the future of artificial intelligence and its potential impact on society. It valuable resource for anyone who wants to learn more about the challenges and opportunities that AI presents.
Provides a mathematical introduction to Big Data analytics. It valuable resource for anyone wants to learn more about the quantitative foundations of Big Data and how to apply them to solve real-world problems.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/wus22q/architecting
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Time
122 hours
Level
Introductory
Via
Pluralsight
Instructor
Janani Ravi
Language
English
This course belongs to a
collection
called
Google: Professional Cloud Data Engineer. It's comprised of 18 courses:
- Architecting Big Data Solutions Using Google Dataproc
- Architecting Serverless Big Data Solutions Using Google Dataflow
- Architecting Data Warehousing Solutions Using Google BigQuery
- Building Machine Learning Models in SQL Using BigQuery ML
- Creating and Administering Google Cloud SQL Instances
- Architecting Big Data Solutions Using Google Bigtable (viewing)
- Designing and Implementing Solutions Using Google Machine Learning APIs
- Designing and Implementing Solutions Using Google Cloud AutoML
- Building Pipelines for Workflow Orchestration Using Google Composer
- Architecting Stream Processing Solutions Using Google Cloud Pub/Sub
- Creating and Administering Google Cloud Spanner Instances
- Architecting Schemaless Scalable NoSQL Databases Using Google Datastore
- Leveraging Fully Managed Redis Datastores Using Google Cloud Memorystore
- Leveraging Google Cloud Firestore for Realtime Database Solutions
- Architecting Scalable Web Applications with Firebase on the Google Cloud Platform
- Developing on the Google Cloud Using Datalab and Cloud Source Repositories
- Architecting Production-ready ML Models Using Google Cloud ML Engine
- Designing Scalable Data Architectures on the Google Cloud
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