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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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SQL vs. NoSQL: Decoding the database dilemma to perfect solutions

Data Science Dojo

Welcome to the world of databases, where the choice between SQL (Structured Query Language) and NoSQL (Not Only SQL) databases can be a significant decision. In this blog, we’ll explore the defining traits, benefits, use cases, and key factors to consider when choosing between SQL and NoSQL databases.

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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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Dynamic text-to-SQL for enterprise workloads with Amazon Bedrock Agents

AWS Machine Learning Blog

Text-to-SQL empowers people to explore data and draw insights using natural language, without requiring specialized database knowledge. Amazon Web Services (AWS) has helped many customers connect this text-to-SQL capability with their own data, which means more employees can generate insights.

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Build your gen AI–based text-to-SQL application using RAG, powered by Amazon Bedrock (Claude 3 Sonnet and Amazon Titan for embedding)

AWS Machine Learning Blog

SQL is one of the key languages widely used across businesses, and it requires an understanding of databases and table metadata. This can be overwhelming for nontechnical users who lack proficiency in SQL. This application allows users to ask questions in natural language and then generates a SQL query for the users request.

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Remote Data Science Jobs: 5 High-Demand Roles for Career Growth

Data Science Dojo

Specialized Industry Knowledge The University of California, Berkeley notes that remote data scientists often work with clients across diverse industries. Whether it’s finance, healthcare, or tech, each sector has unique data requirements. Modeling Questions Be ready to explain how you’ve applied modeling or visualization skills.

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Navigate your way to success – Top 10 data science careers to pursue in 2023

Data Science Dojo

In the current landscape, data science has emerged as the lifeblood of organizations seeking to gain a competitive edge. As the volume and complexity of data continue to surge, the demand for skilled professionals who can derive meaningful insights from this wealth of information has skyrocketed.