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Data Management and Storage in the Cloud

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Overview

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Hi again! This is the second course of the Google Cloud Data Analytics Certificate. Get cozy with the key components of data governance, normalized and star schemas, data catalogs, and data lakehouse architecture.

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
    • Knowledge Catalog's data lineage feature
    • How to use the Knowledge Catalog data lineage feature
    • Test your knowledge: Strategies for understanding data sources
    • Introduction to BigQuery sharing
    • BigQuery sharing enables data sharing
    • How to use BigQuery sharing
    • Test your knowledge: Tools for sharing data
    • Data discovery, curation, and unification
    • Overview of Knowledge Catalog
    • Benefits of using Knowledge Catalog
    • Using Knowledge Catalog
    • How to search for data with BigQuery
    • Navigate Knowledge Catalog
    • 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 Managed Service for Apache Spark
    • 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 Gemini Enterprise Agent Platform 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 Managed Service for Apache Spark
    • How to create a Managed Service for Apache Spark cluster
    • How to manage Managed Service for Apache Spark 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 wrap-up
    • Course 2 resources and citations
    • Glossary terms from Course 2
  • Your Next Steps
    • Completion

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