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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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Stitching Together Enterprise Analytics With Microsoft Fabric

Data Engineering Podcast

Summary Data lakehouse architectures have been gaining significant adoption. To accelerate adoption in the enterprise Microsoft has created the Fabric platform, based on their OneLake architecture. Data lakes in various forms have been gaining significant popularity as a unified interface to an organization's analytics.

Data Lake 162
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Charting A Path For Streaming Data To Fill Your Data Lake With Hudi

Data Engineering Podcast

Summary Data lake architectures have largely been biased toward batch processing workflows due to the volume of data that they are designed for. With more real-time requirements and the increasing use of streaming data there has been a struggle to merge fast, incremental updates with large, historical analysis.

Data Lake 130
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Exploring Processing Patterns For Streaming Data Integration In Your Data Lake

Data Engineering Podcast

Summary One of the perennial challenges posed by data lakes is how to keep them up to date as new data is collected. In this episode Ori Rafael shares his experiences from Upsolver and building scalable stream processing for integrating and analyzing data, and what the tradeoffs are when coming from a batch oriented mindset.

Data Lake 100
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Data Lake Explained: A Comprehensive Guide to Its Architecture and Use Cases

AltexSoft

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. What is a data lake?

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How Marriott Modernized Their Data Architecture with Snowflake

Snowflake

More than 50% of data leaders recently surveyed by BCG said the complexity of their data architecture is a significant pain point in their enterprise. As a result,” says BCG, “many companies find themselves at a tipping point, at risk of drowning in a deluge of data, overburdened with complexity and costs.”

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Top Data Lake Vendors (Quick Reference Guide)

Monte Carlo

Data lakes are useful, flexible data storage repositories that enable many types of data to be stored in its rawest state. Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption.