Remove Data Pipeline Remove EDA Remove SQL
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11 Open Source Data Exploration Tools You Need to Know in 2023

ODSC - Open Data Science

These tools will help make your initial data exploration process easy. ydata-profiling GitHub | Website The primary goal of ydata-profiling is to provide a one-line Exploratory Data Analysis (EDA) experience in a consistent and fast solution. You can watch it on demand here.

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The Data Dilemma: Exploring the Key Differences Between Data Science and Data Engineering

Pickl AI

Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

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Harness the power of AI and ML using Splunk and Amazon SageMaker Canvas

AWS Machine Learning Blog

AWS data engineering pipeline The adaptable approach detailed in this post starts with an automated data engineering pipeline to make data stored in Splunk available to a wide range of personas, including business intelligence (BI) analysts, data scientists, and ML practitioners, through a SQL interface.

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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. GPT-4 Data Pipelines: Transform JSON to SQL Schema Instantly Blockstream’s public Bitcoin API.

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Data Scientists in the Age of AI Agents and AutoML

Towards AI

Uncomfortable reality: In the era of large language models (LLMs) and AutoML, traditional skills like Python scripting, SQL, and building predictive models are no longer enough for data scientist to remain competitive in the market. The role of a data scientist is changing so fast that often schools cant keep up. It depends.