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Transforming Your Data Pipeline with dbt(data build tool)

Analytics Vidhya

In today’s data-driven world, extracting, transforming, and loading (ETL) data is crucial for gaining valuable insights. While many ETL tools exist, dbt (data build tool) is emerging as a game-changer.

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Supercharging Your Data Pipeline with Apache Airflow (Part 2)

Heartbeat

Image Source —  Pixel Production Inc In the previous article, you were introduced to the intricacies of data pipelines, including the two major types of existing data pipelines. You might be curious how a simple tool like Apache Airflow can be powerful for managing complex data pipelines.

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How Kakao Games automates lifetime value prediction from game data using Amazon SageMaker and AWS Glue

AWS Machine Learning Blog

To solve this problem, we had to design a strong data pipeline to create the ML features from the raw data and MLOps. Multiple data sources ODIN is an MMORPG where the game players interact with each other, and there are various events such as level-up, item purchase, and gold (game money) hunting.

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The 2021 Executive Guide To Data Science and AI

Applied Data Science

Machine learning The 6 key trends you need to know in 2021 ? Automation Automating data pipelines and models ➡️ 6. First, let’s explore the key attributes of each role: The Data Scientist Data scientists have a wealth of practical expertise building AI systems for a range of applications.

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How Cloud Data Platforms improve Shopfloor Management

Data Science Blog

If the data sources are additionally expanded to include the machines of production and logistics, much more in-depth analyses for error detection and prevention as well as for optimizing the factory in its dynamic environment become possible.

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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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A Guide to Choose the Best Data Science Bootcamp

Data Science Dojo

Machine Learning : Supervised and unsupervised learning algorithms, including regression, classification, clustering, and deep learning. Tools and frameworks like Scikit-Learn, TensorFlow, and Keras are often covered.