Data-Driven Organizations and Pipelines

The five Vs of data are volume, velocity, variety, veracity, and value. They are important because they help organizations understand how to manage and utilize data effectively for decision-making.

ETL stands for Extract, Transform, Load, which processes data before loading it into the storage. ELT, or Extract, Load, Transform, loads raw data first and then transforms it in the target storage, allowing faster access to data.

A data engineer designs, constructs, and maintains the infrastructure and systems needed to collect, store, and analyze data. They ensure that data flows smoothly through the data pipeline.

<p>Batch processing ingests large volumes of data at once in scheduled intervals, while stream processing ingests data continuously in real-time as it is generated. This affects how quickly insights can be derived.</p> Signup and view all the answers

<p>Data cleaning is significant because it improves the accuracy and quality of data by removing errors, duplicates, and inconsistencies. This ensures that analysis and insights derived from the data are reliable.</p> Signup and view all the answers

<p>Cloud security impacts data ingestion and storage by ensuring that data is protected from unauthorized access and breaches, which is crucial for maintaining data integrity and compliance. Security measures must be integrated throughout the data pipeline.</p> Signup and view all the answers

<p>One method of feature engineering is creating interaction features, which involve combining two or more existing features to extract their combined effects on the target variable. This can improve the model's predictive performance.</p> Signup and view all the answers

<p>Purpose-built databases are specialized databases designed for specific types of data and use cases, optimizing performance and scalability. They support modern data architecture by providing efficient storage and retrieval tailored to particular analytical needs.</p> Signup and view all the answers