3. Compare and contrast silver and gold tables, which workloads will use a bronze table as a source, which workloads will use a gold table as a source

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Questions and Answers

What is the primary purpose of silver tables in a data lakehouse?

To store raw, unprocessed data for historical reference.

To contain validated, cleansed, and conformed data as an intermediate layer. (correct)

To provide business-ready data optimized for reporting.

To support complex queries and real-time decision-making.

Which of the following is NOT a typical use case for gold tables?

Building and training machine learning models.

Supporting complex queries for strategic insights.

Business Intelligence reporting and dashboard generation.

Data deduplication and basic transformations. (correct)

Who primarily utilizes silver tables for their work?

Data engineers and data analysts. (correct)

Application developers for operational processes.

Business analysts and decision-makers.

Data scientists focusing on machine learning.

What characterizes the data quality in gold tables compared to silver tables?

Data quality in gold tables is the highest, ready for consumption. Signup and view all the answers

In a data lakehouse, what is a common workload for bronze tables?

Storing the raw, unprocessed history of datasets. Signup and view all the answers

Match the purpose of each type of table in a data lakehouse with its description:

Silver Tables = Intermediate layer for enriched and standardized data Gold Tables = Contains highly refined, business-ready data Bronze Tables = Stores raw, unprocessed history of datasets Signup and view all the answers

Match each user type with their primary interaction with the tables:

Data Engineers = Need clean datasets for processing Business Analysts = Require high-quality data for insights Data Scientists = Utilize data for building ML models Data Analysts = Process data for validation and deduplication Signup and view all the answers

Match the quality of data with its corresponding table type:

Bronze Tables = Historical data storage Silver Tables = Validated and cleansed data Gold Tables = High-quality, ready for BI tools Signup and view all the answers

Match the use case with the appropriate table type

Gold Tables = Real-time decision-making applications Silver Tables = Data validation and deduplication Bronze Tables = Initial data processing Signup and view all the answers

Match the following terms associated with data processing tasks:

Data Cleansing = Occurs in Silver Tables Aggregation = Characteristic of Gold Tables Raw Data Ingestion = Source of Bronze Tables Basic Transformations = Initial processing before Silver Tables Signup and view all the answers

Match the descriptions of workloads with their respective table sources:

Business Intelligence = Uses Gold Tables for reports Advanced Analytics = Involves Gold Tables for ML Data Reprocessing = Utilizes Bronze Tables' history Data Quality Assurance = Implemented in Silver Tables Signup and view all the answers

Match the primary characteristics with the corresponding table type:

Silver Tables = Standardized and enriched Gold Tables = Highest quality data for BI Bronze Tables = Unprocessed and raw Signup and view all the answers

Match each table type with its specific users:

Silver Tables = Data engineers and analysts Gold Tables = Data scientists and ML engineers Bronze Tables = Data architects for initial processing Signup and view all the answers

Match the advanced features to the appropriate table type:

Gold Tables = Aggregated business-ready data Silver Tables = Intermediate processing layer Bronze Tables = Ingests raw data Signup and view all the answers

Match the feature of each table type with its significance:

Silver Tables = Provides enterprise view Gold Tables = Facilitates real-time analytics Bronze Tables = Preserves original data source Signup and view all the answers

Silver tables contain raw and unprocessed data that is ready for immediate use.

False Signup and view all the answers

Gold tables are primarily used by data engineers for basic transformations.

False Signup and view all the answers

Bronze tables can be used to store historical data which can be reprocessed if necessary.

True Signup and view all the answers

Data in gold tables is of higher quality than the data in silver tables and is ready for consumption by BI tools.

True Signup and view all the answers

Data analysts primarily utilize gold tables for their data processing needs.

False Signup and view all the answers

Study Notes

Silver Tables

Purpose: Silver tables hold validated, cleansed and conformed data: this means the data has been checked for correctness, cleaned up, and made consistent across different sources.
Data Quality: Silver tables have better data quality than bronze tables but are not as refined as gold tables.
Use Cases:
- Data validation: ensuring the accuracy and completeness of data.
- Deduplication: removing duplicate records.
- Basic transformations: applying simple transformations to data, like changing data formats or adding calculated fields.
- Provide an enterprise view: presenting critical business entities and related transactions in a unified way.
Users: Primarily data engineers and data analysts who need a clean and consistent dataset for further processing and analysis.

Gold Tables

Purpose: Gold tables contain highly refined, aggregated and business-ready data: this means the data is ready for use by business analysts and data scientists.
Data Quality: Gold tables have the highest quality data, suitable for consumption by BI tools and machine learning models.
Use Cases:
- Advanced analytics: sophisticated data analysis techniques, often involving statistical modeling, to uncover insights.
- Machine learning: training and deploying machine learning models to make predictions or decisions.
- Production applications: deploying applications that require high-quality data for real-time decision-making.
Users: Business analysts, data scientists, and decision-makers who rely on accurate data to make decisions.

Workloads Using Bronze Tables

Data Ingestion: Raw data from various sources are ingested into bronze tables, including batch and streaming data.
Historical Data Storage: Bronze tables hold the unprocessed history of datasets: useful for reprocessing if needed.
Initial Data Processing: Basic transformations and metadata additions are performed before moving data to silver tables.

Workloads Using Gold Tables

Business Intelligence (BI): BI tools utilize gold tables for generating reports and dashboards.
Advanced Analytics: Data scientists leverage gold tables to build and train machine learning models.
Production Applications: Applications needing high-quality, aggregated data for real-time decision-making and operational processes rely on gold tables.

Silver Tables

Contain validated, cleansed, and conformed data
Serve as an intermediate layer between bronze and gold tables
Data is more reliable than bronze tables but less refined than gold tables
Used for data validation, deduplication, and basic transformations
Provide an enterprise view of key business entities and transactions
Used by data engineers and data analysts

Gold Tables

Contain highly refined, aggregated, and business-ready data
Optimized for analytics and reporting
Data is of the highest quality, ready for consumption by BI tools and machine learning models
Used for advanced analytics, machine learning, and production applications
Support complex queries and reporting
Used by business analysts, data scientists, and decision-makers

Workloads Using Bronze Tables

Raw data from various sources is ingested into bronze tables
This includes batch and streaming data
Bronze tables store the raw, unprocessed history of datasets
Initial data processing like basic transformations and metadata additions are performed before moving data to silver tables

Workloads Using Gold Tables

BI tools use gold tables for generating reports and dashboards
Data scientists use gold tables for building and training machine learning models
Applications that require high-quality, aggregated data for real-time decision-making and operational processes use gold tables

Silver Tables

Purpose: Hold validated, cleansed, and conformed data serving as an intermediate layer for enrichment and standardization.
Data Quality: More reliable than bronze tables but less refined than gold tables.
Use Cases: Data validation, deduplication, basic transformations, providing an enterprise view of business entities and transactions.
Users: Data engineers and analysts for further processing and analysis.

Gold Tables

Purpose: Contain highly refined, aggregated, business-ready data optimized for analytics and reporting.
Data Quality: Highest quality, ready for consumption by BI tools and machine learning models.
Use Cases: Advanced analytics, machine learning, production applications, supporting complex queries and reporting.
Users: Business analysts, data scientists, decision-makers for strategic insights and decision-making.

Workloads Using Bronze Tables as a Source

Data Ingestion: Raw data from various sources is ingested into bronze tables, including batch and streaming data.
Historical Data Storage: Bronze tables store the raw, unprocessed history of datasets, allowing for reprocessing if needed.
Initial Data Processing: Basic transformations and metadata additions are performed before moving data to silver tables.

Workloads Using Gold Tables as a Source

Business Intelligence (BI): BI tools use gold tables for generating reports and dashboards.
Advanced Analytics: Data scientists use gold tables for building and training machine learning models.
Production Applications: Applications that require high-quality, aggregated data for real-time decision-making and operational processes.

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Description

This quiz explores the concepts of silver and gold tables in data engineering. It discusses their purposes, quality levels, and use cases, such as data validation and transformation. Ideal for data engineers and analysts, it helps in understanding how to manage and utilize refined datasets effectively.