Remove Amazon Web Services Remove Data Preparation Remove Google Cloud Remove Structured Data
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15+ Best Data Engineering Tools to Explore in 2023

Knowledge Hut

Here, we'll take a look at the top data engineer tools in 2023 that are essential for data professionals to succeed in their roles. These tools include both open-source and commercial options, as well as offerings from major cloud providers like AWS, Azure, and Google Cloud. What are Data Engineering Tools?

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Snowflake Architecture and It's Fundamental Concepts

ProjectPro

Traditional data preparation platforms, including Apache Spark, are unnecessarily complex and inefficient, resulting in fragile and costly data pipelines. Multi-Cloud Support- Snowflake is a fully managed data warehouse deployed across various clouds while maintaining the same intuitive user interface.

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20 Solved End-to-End Big Data Projects with Source Code

ProjectPro

There are open data platforms in several regions (like data.gov in the U.S.). These open data sets are a fantastic resource if you're working on a personal project for fun. Data Preparation and Cleaning The data preparation step, which may consume up to 80% of the time allocated to any big data or data engineering project, comes next.

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20+ Data Engineering Projects for Beginners with Source Code

ProjectPro

Source Code: Event Data Analysis using AWS ELK Stack 5) Data Ingestion This project involves data ingestion and processing pipeline with real-time streaming and batch loads on the Google cloud platform (GCP). Create a service account on GCP and download Google Cloud SDK(Software developer kit).

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50 Artificial Intelligence Interview Questions and Answers [2023]

ProjectPro

This would include the automation of a standard machine learning workflow which would include the steps of Gathering the data Preparing the Data Training Evaluation Testing Deployment and Prediction This includes the automation of tasks such as Hyperparameter Optimization, Model Selection, and Feature Selection.