Remove Azure Remove Data Modeling Remove EDA
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The Data Dilemma: Exploring the Key Differences Between Data Science and Data Engineering

Pickl AI

Their primary responsibilities include: Data Collection and Preparation Data Scientists start by gathering relevant data from various sources, including databases, APIs, and online platforms. They clean and preprocess the data to remove inconsistencies and ensure its quality. ETL Tools: Apache NiFi, Talend, etc.

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Generative AI in Software Development

Mlearning.ai

Generative AI can be used to automate the data modeling process by generating entity-relationship diagrams or other types of data models and assist in UI design process by generating wireframes or high-fidelity mockups. diagram Using ChatGPT to build system diagrams — Part II Generate C4 diagrams using mermaid.js

AI 52
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Data Scientists in the Age of AI Agents and AutoML

Towards AI

Its less about just building models and more about how those models fit into scalable, business-critical systems usually in the cloud. The role of a data scientist is changing so fast that often schools cant keep up. Universities still mostly focus on things like EDA, data cleaning, and building/fine-tune models.