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Top 12 Data Engineering Project Ideas [With Source Code]

Knowledge Hut

If you want to break into the field of data engineering but don't yet have any expertise in the field, compiling a portfolio of data engineering projects may help. Data pipeline best practices should be shown in these initiatives. In addition to this, they make sure that the data is always readily accessible to consumers.

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Big Data Analytics: How It Works, Tools, and Real-Life Applications

AltexSoft

It’s worth noting though that data collection commonly happens in real-time or near real-time to ensure immediate processing. Data cleansing. Before getting thoroughly analyzed, data ? and as such confirming the usefulness and relevance of data for analytics. whether small or big ?

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Data Lake Explained: A Comprehensive Guide to Its Architecture and Use Cases

AltexSoft

Unstructured data sources. This category includes a diverse range of data types that do not have a predefined structure. Examples of unstructured data can range from sensor data in the industrial Internet of Things (IoT) applications, videos and audio streams, images, and social media content like tweets or Facebook posts.

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15+ Must Have Data Engineer Skills in 2023

Knowledge Hut

With a plethora of new technology tools on the market, data engineers should update their skill set with continuous learning and data engineer certification programs. What do Data Engineers Do? Technical Data Engineer Skills 1.Python Knowing how to work with key-value pairs and object formats is still necessary.

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Real-World Use Cases of Big Data That Drive Business Success

Knowledge Hut

Sentiment Analysis and Natural Language Processing (NLP): AI and ML algorithms can process and analyze unstructured data, like text and speech, to better understand consumer sentiments. AWS (Amazon Web Services) offers a range of services and tools for managing and analyzing big data.

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20+ Data Engineering Projects for Beginners with Source Code

ProjectPro

They are also often expected to prepare their dataset by web scraping with the help of various APIs. Thus, as a learner, your goal should be to work on projects that help you explore structured and unstructured data in different formats. Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data.

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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.