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Data Management and Storage in the Cloud

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Overview

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This is the second of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll explore how data is structured and organized. You’ll gain hands-on experience with the data lakehouse architecture and cloud components like BigQuery, Google Cloud Storage, and DataProc to efficiently store, analyze, and process large datasets.

Syllabus

  • Introduction to data management and storage in the cloud
    • Introduction to Course 2
    • Course 2 overview
    • Eric: Data analytics skills translate across industries and roles
    • Helpful resources and tips
    • Lab technical tips
    • Explore your Course 2 scenario: TheLook eCommerce
    • Welcome to module 1
    • Data storage and connections
    • Gerrit: Experience with a variety of tools can help you as an analyst
    • Common ways to store data
    • [Supplemental] Common data storage systems
    • AI-based predictive data management
    • Structured, unstructured, and semi-structured data
    • Overview of data lakehouse architecture
    • Example of a data lakehouse
    • Comparison of data warehouses and data lakehouses
    • Test your knowledge: Data storage options
    • Aspects of table schema
    • Overview of BigQuery's schema editing abilities
    • Components of BigQuery table schema
    • Complex data types in BigQuery
    • Introduction to nested data structure
    • Guide to BigQuery
    • Explore flat and nested data types in BigQuery
    • Test your knowledge: Data types and organization in BigQuery
    • Overview of data processing methods
    • Batch versus streaming data processing
    • Identify different batch and streaming data sources
    • Test your knowledge: Batch and streaming data sources
    • Wrap-up
    • Glossary terms from module 1
    • Module 1 challenge
  • Key components of data organization
    • Welcome to module 2
    • Denormalized data
    • Normalized and denormalized data
    • Test your knowledge: Ways to organize data
    • Data governance for effective data management
    • MK: Risk management in a cloud-first world
    • Components and objectives of data governance
    • Introduction to master data management
    • Test your knowledge: Data governance
    • Introduction to data catalogs
    • Data catalog components
    • Technical and business metadata
    • Test your knowledge: Foundations of accessible data
    • Overview of data lakehouse architecture
    • Components of data lakehouse architecture
    • Data lakehouse implementation best practices
    • Explore a lakehouse
    • Test your knowledge: Data lakehouse architecture
    • Wrap-up
    • Glossary terms from module 2
    • Module 2 challenge
  • Steps to find data
    • Welcome to module 3
    • Ryan: Curiosity can help you understand and connect data
    • How to find data using BigQuery
    • Data lineage and traceability
    • Dataplex's data lineage feature
    • How to use the Dataplex data lineage feature
    • Test your knowledge: Strategies for understanding data sources
    • Introduction to Analytics Hub
    • Analytics Hub enables data sharing
    • How to use Analytics Hub
    • Test your knowledge: Tools for sharing data
    • Data discovery, curation, and unification
    • Overview of Dataplex
    • Benefits of using Dataplex
    • How to search for data with BigQuery
    • Navigate Dataplex
    • Test your knowledge: Dataplex and BigQuery for accessing data
    • Wrap-up
    • Glossary terms from module 3
    • Module 3 challenge
  • Techniques to access data
    • Welcome to module 4
    • Methods for defining BigQuery table schemas
    • Auto-detection of schemas in BigQuery
    • Basic SQL commands for querying data
    • [Supplemental] SQL query terms
    • Compare data analytics with BigQuery and Dataproc
    • Test your knowledge: Data schemas and queries in BigQuery
    • Steps and models for accessing data with machine learning
    • Cloud-based machine learning can train predictive models
    • Introduction to machine learning with Vertex AI and BigQuery
    • Overview of Google Colab
    • Managed notebooks
    • Test your knowledge: Integration of Google Cloud tools
    • Essentials of database partitioning
    • Benefits of data partitioning
    • Methods for partitioning tables
    • Data partitioning reduces cloud costs
    • Create a partitioned table
    • Test your knowledge: Overview of data partitioning
    • Strategies for querying partitioned tables
    • Tips for interacting with partitioned tables
    • Manage a partitioned table in BigQuery
    • Test your knowledge: Techniques for managing partitioned tables
    • Key processes and benefits of Dataproc
    • How to create a Dataproc cluster
    • How to manage Dataproc clusters
    • Test your knowledge: Dataproc for automation and improved data processing
    • Wrap-up
    • Vince and George: Interview role play
    • Interview tip: Provide examples
    • Glossary terms from module 4
    • Module 4 challenge
    • Course wrap-up
    • Course 2 resources and citations
    • Glossary terms from Course 2
  • Your Next Steps
    • Course Badge

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