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How Apache Iceberg Is Changing the Face of Data Lakes

Snowflake

Data storage has been evolving, from databases to data warehouses and expansive data lakes, with each architecture responding to different business and data needs. Traditional databases excelled at structured data and transactional workloads but struggled with performance at scale as data volumes grew.

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Why Open Table Format Architecture is Essential for Modern Data Systems

phData: Data Engineering

The world we live in today presents larger datasets, more complex data, and diverse needs, all of which call for efficient, scalable data systems. Open Table Format (OTF) architecture now provides a solution for efficient data storage, management, and processing while ensuring compatibility across different platforms.

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Level Up Your Data Platform With Active Metadata

Data Engineering Podcast

Summary Metadata is the lifeblood of your data platform, providing information about what is happening in your systems. A variety of platforms have been developed to capture and analyze that information to great effect, but they are inherently limited in their utility due to their nature as storage systems.

Metadata 130
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Announcing New Innovations for Data Warehouse, Data Lake, and Data Lakehouse in the Data Cloud 

Snowflake

Over the years, the technology landscape for data management has given rise to various architecture patterns, each thoughtfully designed to cater to specific use cases and requirements. These patterns include both centralized storage patterns like data warehouse , data lake and data lakehouse , and distributed patterns such as data mesh.

Data Lake 114
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Eliminate Friction In Your Data Platform Through Unified Metadata Using OpenMetadata

Data Engineering Podcast

Summary A significant source of friction and wasted effort in building and integrating data management systems is the fragmentation of metadata across various tools. Start trusting your data with Monte Carlo today! Supercharge your business teams with customer data using Hightouch for Reverse ETL today.

Metadata 100
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AI and Data Predictions 2025: Strategies to Realize the Promise of AI

Snowflake

Beyond working with well-structured data in a data warehouse, modern AI systems can use deep learning and natural language processing to work effectively with unstructured and semi-structured data in data lakes and lakehouses.

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Being Data Driven At Stripe With Trino And Iceberg

Data Engineering Podcast

In this episode Kevin Liu shares some of the interesting features that they have built by combining those technologies, as well as the challenges that they face in supporting the myriad workloads that are thrown at this layer of their data platform. What are the other systems that feed into and rely on the Trino/Iceberg service?

Data Lake 147