Data Science Blog

MAY 20, 2024

Continuous Integration and Continuous Delivery (CI/CD) for Data Pipelines: It is a Game-Changer with AnalyticsCreator! The need for efficient and reliable data pipelines is paramount in data science and data engineering. It offers full BI-Stack Automation, from source to data warehouse through to frontend.

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AWS Machine Learning Blog

NOVEMBER 9, 2023

Building out a machine learning operations (MLOps) platform in the rapidly evolving landscape of artificial intelligence (AI) and machine learning (ML) for organizations is essential for seamlessly bridging the gap between data science experimentation and deployment while meeting the requirements around model performance, security, and compliance.

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Flipboard

AUGUST 17, 2023

Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and ML to deliver the best price-performance at any scale. If you want to do the process in a low-code/no-code way, you can follow option C.

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Alation

JULY 7, 2022

To answer these questions we need to look at how data roles within the job market have evolved, and how academic programs have changed to meet new workforce demands. In the 2010s, the growing scope of the data landscape gave rise to a new profession: the data scientist. The data scientist. We’ve made incredible progress.

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AWS Machine Learning Blog

AUGUST 4, 2023

Use the Salesforce Einstein Studio API for predictions Salesforce Einstein Studio is a new and centralized experience in Salesforce Data Cloud that data science and engineering teams can use to easily access their traditional models and LLMs used in generative AI. Choose Add permissions and select Create an inline policy.

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