Section 4 (Incremenatal Data Processing), 28. Multi Hop Architecture
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Questions and Answers

The multi hop architecture consists of four layers: bronze, silver, gold, and platinum.

False

The bronze table contains raw data ingested from various sources like json files and operational databases.

True

Incremental ETL means that data is extracted, transformed, and loaded all at once.

False

The silver table provides the most refined view of the data compared to the gold table.

<p>False</p> Signup and view all the answers

Multi hop architecture allows for configuring each stage as either a batch or streaming job.

<p>True</p> Signup and view all the answers

What is the primary purpose of a silver table in a multi hop architecture?

<p>To offer a more refined view of data, including cleaning and filtering.</p> Signup and view all the answers

What advantage does multi hop architecture provide in terms of data processing?

<p>It facilitates both streaming and batch workloads in the same pipeline.</p> Signup and view all the answers

Which statement best describes the bronze table in a multi hop architecture?

<p>It consists of raw data sourced from operational databases and Kafka Streams.</p> Signup and view all the answers

What can the gold table in a multi hop architecture be primarily used for?

<p>Providing business-level aggregations for reporting and dashboarding.</p> Signup and view all the answers

In the context of multi hop architecture, what does the term incremental ETL refer to?

<p>The method of extracting, transforming, and loading data sequentially and in smaller increments.</p> Signup and view all the answers

Match the layers of the multi hop architecture with their descriptions:

<p>Bronze = Contains raw data ingested from various sources Silver = Provides cleaned and filtered data Gold = Offers business-level aggregations for reporting Multi hop architecture = Data design pattern for incrementally improving data structure</p> Signup and view all the answers

Match the terms with their definitions in the context of multi hop architecture:

<p>Incremental ETL = Extracts, transforms, and loads data in stages Streaming workload = Processes data in real-time Batch workload = Processes data at scheduled intervals Medallion architecture = Another name for multi hop architecture</p> Signup and view all the answers

Match the data processing benefits with their explanations:

<p>Simple data model = Easy to understand and implement Incremental processing = Allows for combining streaming and batch workloads Data recreation = Enables re-processing raw data anytime Layered approach = Improves data structure and quality incrementally</p> Signup and view all the answers

Match the types of tables with their functions:

<p>Bronze table = Raw data storage Silver table = Data cleaning and enrichment Gold table = Data for reporting and machine learning Incremental pipeline = Streamlined data flow through layers</p> Signup and view all the answers

Match the source types with their examples of use in the bronze table:

<p>JSON files = Format for raw data input Operational databases = Source for structured data Kafka Stream = Used for real-time data ingestion CSV files = Another common format for raw data</p> Signup and view all the answers

Study Notes

Multi Hop Architecture in Lakehouse

  • Multi hop architecture, also called Medallion architecture, organizes data in a multilayered structure.
  • The structure aims to improve data quality and organization as it transitions through each layer of the architecture.

Layers of Multi Hop Architecture

  • Bronze Layer:

    • Contains raw data ingested from various sources (e.g., JSON files, operational databases, Kafka Stream).

  • Silver Layer:

    • Provides a more refined view of the data.
    • Allows for data cleaning, filtering, and field joining from various bronze tables for enriching records.

  • Gold Layer:

    • Offers business-level aggregations for analytics.
    • Typically used for reporting, dashboarding, and machine learning applications.

Benefits of Multi Hop Architecture

  • Features a straightforward data model that is easy to comprehend and implement.
  • Supports incremental ETL (Extract, Transform, Load) processes, allowing for gradual data processing.
  • Capable of integrating both streaming and batch workloads within a single pipeline.
  • Each stage can be configured to operate as either a batch or streaming job.
  • Enables recreation of tables from raw data at any point in time, enhancing flexibility in data management.

Multi Hop Architecture in Lakehouse

  • Multi hop architecture, also called Medallion architecture, organizes data in a multilayered structure.
  • The structure aims to improve data quality and organization as it transitions through each layer of the architecture.

Layers of Multi Hop Architecture

  • Bronze Layer:

    • Contains raw data ingested from various sources (e.g., JSON files, operational databases, Kafka Stream).

  • Silver Layer:

    • Provides a more refined view of the data.
    • Allows for data cleaning, filtering, and field joining from various bronze tables for enriching records.

  • Gold Layer:

    • Offers business-level aggregations for analytics.
    • Typically used for reporting, dashboarding, and machine learning applications.

Benefits of Multi Hop Architecture

  • Features a straightforward data model that is easy to comprehend and implement.
  • Supports incremental ETL (Extract, Transform, Load) processes, allowing for gradual data processing.
  • Capable of integrating both streaming and batch workloads within a single pipeline.
  • Each stage can be configured to operate as either a batch or streaming job.
  • Enables recreation of tables from raw data at any point in time, enhancing flexibility in data management.

Multi Hop Architecture in Lakehouse

  • Multi hop architecture, also called Medallion architecture, organizes data in a multilayered structure.
  • The structure aims to improve data quality and organization as it transitions through each layer of the architecture.

Layers of Multi Hop Architecture

  • Bronze Layer:

    • Contains raw data ingested from various sources (e.g., JSON files, operational databases, Kafka Stream).

  • Silver Layer:

    • Provides a more refined view of the data.
    • Allows for data cleaning, filtering, and field joining from various bronze tables for enriching records.

  • Gold Layer:

    • Offers business-level aggregations for analytics.
    • Typically used for reporting, dashboarding, and machine learning applications.

Benefits of Multi Hop Architecture

  • Features a straightforward data model that is easy to comprehend and implement.
  • Supports incremental ETL (Extract, Transform, Load) processes, allowing for gradual data processing.
  • Capable of integrating both streaming and batch workloads within a single pipeline.
  • Each stage can be configured to operate as either a batch or streaming job.
  • Enables recreation of tables from raw data at any point in time, enhancing flexibility in data management.

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Description

Explore the concept of multi hop architecture within Lakehouse frameworks in this video. You'll learn about the incremental multi hop pipeline and the significance of the bronze, silver, and gold table layers. This Medallion architecture is essential for enhancing data structure and quality incrementally.

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