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Schema Evolution in Data Lakes

KDnuggets

Whereas a data warehouse will need rigid data modeling and definitions, a data lake can store different types and shapes of data. In a data lake, the schema of the data can be inferred when it’s read, providing the aforementioned flexibility.

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Data warehouse architecture

Dataconomy

Want to create a robust data warehouse architecture for your business? The sheer volume of data that companies are now gathering is incredible, and understanding how best to store and use this information to extract top performance can be incredibly overwhelming.

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Exploring the Power of Data Warehouse Functionality

Pickl AI

Summary: A data warehouse is a central information hub that stores and organizes vast amounts of data from different sources within an organization. Unlike operational databases focused on daily tasks, data warehouses are designed for analysis, enabling historical trend exploration and informed decision-making.

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Data Version Control for Data Lakes: Handling the Changes in Large Scale

ODSC - Open Data Science

In this article, we will delve into the concept of data lakes, explore their differences from data warehouses and relational databases, and discuss the significance of data version control in the context of large-scale data management. Before we address the questions, ‘ What is data version control ?’

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Deciphering The Seldom Discussed Differences Between Data Mining and Data Science

Smart Data Collective

This new approach has proven to be much more effective, so it is a skill set that people must master to become data scientists. Definition: Data Mining vs Data Science. Data mining is an automated data search based on the analysis of huge amounts of information. Data Mining Techniques and Data Visualization.

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Introduction to Power BI Datamarts

ODSC - Open Data Science

This article is an excerpt from the book Expert Data Modeling with Power BI, Third Edition by Soheil Bakhshi, a completely updated and revised edition of the bestselling guide to Power BI and data modeling. in an enterprise data warehouse. in an enterprise data warehouse. What is a Datamart?

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Building an efficient MLOps platform with OSS tools on Amazon ECS with AWS Fargate

AWS Machine Learning Blog

Additionally, Feast promotes feature reuse, so the time spent on data preparation is reduced greatly. It promotes a disciplined approach to data modeling, making it easier to ensure data quality and consistency across the ML pipelines. The following figure shows schema definition and model which reference it.

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