Remove data enterprise-data-lake
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A Comprehensive Guide on Delta Lake

Analytics Vidhya

Introduction Enterprises here and now catalyze vast quantities of data, which can be a high-end source of business intelligence and insight when used appropriately. Delta Lake allows businesses to access and break new data down in real time.

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Delta Lake in Action – Quick Hands-on Tutorial for Beginners

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction In the modern data world, Lakehouse has become one of the most discussed topics for building a data platform. The post Delta Lake in Action – Quick Hands-on Tutorial for Beginners appeared first on Analytics Vidhya.

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Building a Lakehouse – Try Delta Lake!

Analytics Vidhya

Introduction Enterprises have been building data platforms for the last few decades, and data architectures have been evolving. The post Building a Lakehouse – Try Delta Lake! Let’s first look at how things have changed and how […]. Let’s first look at how things have changed and how […].

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Look Out: Computer Vision in AI is Coming Into Sight

David Menninger's Analyst Perspectives

Unstructured data has been a significant factor in data lakes and analytics for some time. Twelve years ago, nearly a third of enterprises were working with large amounts of unstructured data. As I’ve pointed out previously , unstructured data is really a misnomer.

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12 Considerations When Evaluating Data Lake Engine Vendors for Analytics and BI

Businesses today compete on their ability to turn big data into essential business insights. To do so, modern enterprises leverage cloud data lakes as the platform used to store data for analytical purposes, combined with various compute engines for processing that data.

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Rapidminer Platform Supports Entire Data Science Lifecycle

David Menninger's Analyst Perspectives

Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. It can support AI/ML processes with data preparation, model validation, results visualization and model optimization.

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Use AWS Glue ETL to perform merge, partition evolution, and schema evolution on Apache Iceberg

AWS Big Data

As enterprises collect increasing amounts of data from various sources, the structure and organization of that data often need to change over time to meet evolving analytical needs. Schema evolution enables adding, deleting, renaming, or modifying columns without needing to rewrite existing data.

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Top Considerations for Building an Open Cloud Data Lake

Data fuels the modern enterprise — today more than ever, businesses compete on their ability to turn big data into essential business insights. Increasingly, enterprises are leveraging cloud data lakes as the platform used to store data for analytics, combined with various compute engines for processing that data.