What is Medallion Architecture and Why Does It Matter
Medallion architecture is an important system for managing data today. This system helps you organize data well. It makes sure you can get useful insights. By knowing its layers—Bronze, Silver, and Gold—you can solve common problems in data processing. For example, it improves data quality and consistency, as shown in the table below:
With these benefits, medallion architecture is key to your data plan.
Key Takeaways
Medallion architecture sorts data into three layers: Bronze, Silver, and Gold. This setup helps improve data quality and makes it easier to analyze.
The Bronze Layer gathers raw data from different sources. It acts as a flexible storage area for future use.
The Silver Layer cleans and organizes data. It uses methods like fixing missing data and getting rid of duplicates. This makes sure we have high-quality data for analysis.
The Gold Layer gives ready-to-use data for making decisions. It helps with advanced analytics and machine learning.
Using medallion architecture boosts teamwork among data teams. Each layer has a special job, which helps with teamwork and efficiency.
Medallion Architecture Overview
Overview of medallion architecture
Medallion architecture is a clear way to manage data. It sorts data into three layers: Bronze, Silver, and Gold. This setup helps you keep data quality high. Each layer has a special job in the data process.
Bronze Layer: This layer collects raw data from different places. Think of it as the inbox for the data lake, where all original data goes. You can check and redo this data later if you want.
Silver Layer: In this layer, you change the raw data into organized datasets. This layer cleans and improves the data, making it ready for analysis. By fixing problems, you make the data better overall.
Gold Layer: This layer gives you ready-to-use datasets for making decisions. It combines data and uses business rules, preparing features for machine learning models.
The importance of medallion architecture in today’s data plans is very high. It gives a clear view of company data. You can change it to fit the needs of different people. This flexibility helps you react quickly to changes in business. Also, it builds a strong base for data rules and following laws.
Medallion architecture also makes managing metadata easier. You can track where data comes from and check your DataOps steps. This order helps cut costs and boost efficiency. Unlike old data storage methods, medallion architecture grows well with more data. It takes in new data sources without big changes, helping both batch and real-time data processing. This ability makes you quicker to respond to market changes.
Bronze Layer
Raw Data Characteristics
The Bronze Layer is the base of medallion architecture. It keeps raw, unprocessed data from many sources. This data can be in different forms, like:
Raw, unprocessed data from many sources
Unstructured or semi-structured data such as logs, JSON files, or CSV data
Data from streaming services like Apache Kafka, external APIs, or batch processes
You can think of the Bronze Layer as a big storage space. It captures all incoming data in its original form. This layer can hold different types of data, making it flexible for future use.
Data Ingestion Process
Getting data into the Bronze Layer has several steps. You usually pull data from different sources, such as:
Transactional databases
IoT devices
Logs
External APIs
During this process, you should follow best practices to keep data safe. Here are some important practices to think about:
Foreign Key Validation: Make sure every foreign key matches a valid primary key.
Checksum or Hashing: Use hashing functions to check data safety during transfer.
Duplicate Records Check: Find and remove duplicate entries.
Schema Validation: Ensure the ingested data fits a set schema.
By following these practices, you can keep the quality of the data in the Bronze Layer. This careful method prepares the data for the next layers, where it will be cleaned and changed for analysis.
Silver Layer
Data Cleaning Techniques
In the Silver Layer, you change raw data into clean datasets. This process uses several good data cleaning methods. Here’s a list of some important techniques:
These methods help you keep data quality high and get datasets ready for analysis.
Validation and Quality Control
Validation is very important in the Silver Layer. You want to make sure your data is correct and trustworthy. Here are some common ways to validate data:
You can use tools like dbt tests, Great Expectations, and Delta Live Tables (DLT) to apply these validation methods well. These tools help you check data and set rules, making sure your datasets are reliable.
By using these data cleaning methods and validation techniques, you improve the quality of your data in the Silver Layer. This leads to better insights and smarter decisions in your organization.
Gold Layer
Analytics and Insights
The Gold Layer is the top part of medallion architecture. Here, you find high-quality data that is ready for analysis. This layer focuses on important performance indicators (KPIs) and shared definitions of key items. It acts as a single source of truth. This means the metrics used in dashboards and applications stay the same across your organization.
In this layer, you can do different types of analytics, such as:
Predictive analytics to guess future trends.
Performance monitoring to check business goals.
Executive dashboards that show a complete view of your operations.
These analytics help you make smart decisions based on trustworthy data.
Business Intelligence Applications
The Gold Layer allows for advanced analytics and machine learning uses. You get access to special datasets made for specific business needs. This access helps create predictive models and machine learning applications. Here are some key features of the Gold Layer:
It has well-organized and combined data for specific business cases.
It includes advanced changes for analytics, machine learning, and business reports.
You can use this layer for real-time reporting and dashboards. The table below shows the benefits of using the Gold Layer for business intelligence:
By using the Gold Layer well, you can improve your organization's decision-making skills and achieve better business results.
Benefits of Medallion Architecture
Advantages of using medallion architecture
Medallion architecture has many important benefits. It helps you manage data and analyze it better. First, it greatly improves data quality. By testing data carefully at each layer—Bronze, Silver, and Gold—you can find and fix problems early. This careful checking reduces mistakes in the insights that customers see. Because of this, you build trust in your organization. Trust is very important for making good decisions.
Also, medallion architecture makes analytics faster. For example, a UK investment firm cut data processing time from days to minutes. They handled 5 terabytes of data from over 50 million records. This change improved their ability to analyze data. Similarly, a U.S. insurance company sped up partner onboarding by 3.5 times. They also reduced manual data work by 70%. These examples show how medallion architecture can make your analytics work better.
Collaboration among data roles also gets better with this architecture. The three-layer design allows different departments to process data flexibly. Each layer has a special job: raw data in Bronze, cleaned data in Silver, and ready-to-analyze data in Gold. This flexibility helps meet changing analytics needs and encourages teamwork among data engineers, analysts, and scientists.
Here’s a summary of how medallion architecture helps collaboration:
By using these benefits, you can improve your data strategy and boost your organization’s performance.
In short, medallion architecture is very important for improving how you manage and analyze data. This organized method changes messy data into something useful. Here are some main points to remember:
Data Governance and Security: Good governance keeps data safe and correct.
Automation and Orchestration: Automation helps cut down mistakes and lessens manual work.
Scalability Considerations: Build your architecture to grow with flexible parts.
By using medallion architecture, you can make your data processes smoother and help with better decision-making. Think about using this model to get the most out of your data strategy. 🌟
FAQ
What is the main purpose of medallion architecture?
Medallion architecture sorts data into three layers: Bronze, Silver, and Gold. This setup helps improve data quality, makes analytics better, and supports smarter decision-making.
How does the Bronze Layer differ from the Gold Layer?
The Bronze Layer keeps raw data, while the Gold Layer has processed, high-quality data ready for analysis. Each layer has a special job in managing data.
Why is data validation important in the Silver Layer?
Data validation makes sure your datasets are correct and trustworthy. It helps you find mistakes early, leading to better insights and informed choices.
Can medallion architecture handle real-time data?
Yes, medallion architecture can work with both batch and real-time data. Its flexible design lets you add new data sources without big changes.
Who benefits from using medallion architecture?
Data engineers, analysts, and business people all gain from it. This architecture encourages teamwork and improves data access for different roles in your organization.