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Visual Data modeling using erwin Data Modeler on the Databricks Lakehouse Platform

databricks

This is a collaborative post between Databricks and Quest Software. We thank Vani Mishra, Director of Product Management at Quest Software for her.

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Big Data Modeling Improves Business Intelligence

The Data Administration Newsletter

Through big data modeling, data-driven organizations can better understand and manage the complexities of big data, improve business intelligence (BI), and enable organizations to benefit from actionable insight.

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Data Modeling in Machine Learning Pipelines: Best Practices Using SQL and NoSQL Databases

Dataversity

Data, undoubtedly, is one of the most significant components making up a machine learning (ML) workflow, and due to this, data management is one of the most important factors in sustaining ML pipelines.

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CI/CD for Data Pipelines: A Game-Changer with AnalyticsCreator

Data Science Blog

It offers full BI-Stack Automation, from source to data warehouse through to frontend. It supports a holistic data model, allowing for rapid prototyping of various models. It also supports a wide range of data warehouses, analytical databases, data lakes, frontends, and pipelines/ETL. Mixed approach of DV 2.0

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Book of the Month: Data Models for Banking, Finance, and Insurance

Dataversity

This time, well be going over Data Models for Banking, Finance, and Insurance by Claire L. This book arms the reader with a set of best practices and data models to help implement solutions in the banking, finance, and insurance industries. Welcome to the first Book of the Month for 2025.This

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Tales of Data Modelers

Dataversity

Reading Larry Burns’ “Data Model Storytelling” (TechnicsPub.com, 2021) was a really good experience for a guy like me (i.e., someone who thinks that data models are narratives). The post Tales of Data Modelers appeared first on DATAVERSITY. The post Tales of Data Modelers appeared first on DATAVERSITY.

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Traditional vs Vector databases: Your guide to make the right choice

Data Science Dojo

This blog delves into a detailed comparison between the two data management techniques. In today’s digital world, businesses must make data-driven decisions to manage huge sets of information. Hence, databases are important for strategic data handling and enhanced operational efficiency.

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