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The Race For Data Quality in a Medallion Architecture

DataKitchen

Bronze layers can also be the raw database tables. Next, data is processed in the Silver layer , which undergoes “just enough” cleaning and transformation to provide a unified, enterprise-wide view of core business entities. For instance, suppose a new dataset from an IoT device is meant to be ingested daily into the Bronze layer.

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The Top Snowflake Integrations Every Data Team Should Know

Monte Carlo

The main benefits of a well-integrated Snowflake environment include automation of repetitive tasks, scalability that grows with your data volumes, data + AI observability that catches issues before they impact users, compliance features that satisfy regulators, and data democratization that puts insights in everyone’s hands.

BI
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Microsoft Fabric - All-in-one AI-Powered Analytics Solution

ProjectPro

With Microsoft Fabric, you can integrate data from various sources, including point-of-sale systems, inventory databases, customer relationship management (CRM) tools, and external sources like weather forecasts and social media trends. OneLake Storage provides a unified solution for storing all data, priced at $0.023 per GB per month.

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How to Learn AWS for Data Engineering?

ProjectPro

What is AWS for Data Engineering? AWS Data Engineering Tools Architecting Data Engineering Pipelines using AWS Data Ingestion - Batch and Streaming Data How to Transform Data to Optimize for Analytics? The word "engineering" is crucial to understand what data engineering means.

AWS
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30+ Data Engineering Projects for Beginners in 2025

ProjectPro

And, out of these professions, we will focus on the data engineering job role in this blog and list out a comprehensive list of projects to help you prepare for the same. Cloud computing skills, especially in Microsoft Azure, SQL , Python , and expertise in big data technologies like Apache Spark and Hadoop, are highly sought after.

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7 Best Data Warehousing Tools for Efficient Data Storage Needs

ProjectPro

These tools are crucial in modern business intelligence and data-driven decision-making processes. They provide a centralized repository for data, known as a data warehouse, where information from disparate sources like databases, spreadsheets, and external systems can be integrated.

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Top 21 Big Data Tools That Empower Data Wizards

ProjectPro

Data scientists can then leverage different Big Data tools to analyze the information. Data scientists and engineers typically use the ETL (Extract, Transform, and Load) tools for data ingestion and pipeline creation. It quickly integrates and transforms cloud-based data.