Which services can be employed to analyze unstructured data in Google Cloud?

Study for the Google Cloud Professional Data Engineer Exam with engaging Qandamp;A. Each question features hints and detailed explanations to enhance your understanding. Prepare confidently and ensure your success!

Google Cloud Natural Language and Google Vision are specifically designed to analyze unstructured data, making them the correct choice in this context. Google Cloud Natural Language specializes in processing and understanding human language, allowing you to derive insights from text data, such as sentiment analysis, entity recognition, and syntactic analysis. This capability is crucial for applications that need to analyze text-based data, which often lacks a structured format.

On the other hand, Google Vision is focused on image analysis. It uses machine learning models to interpret and extract information from images, enabling features such as label detection, optical character recognition (OCR), and image classification. Together, these services facilitate the analysis of various forms of unstructured data, including text and images, allowing users to harness valuable insights from content that doesn’t conform to traditional database structures.

In contrast, the other options either focus on computing resources or database management without the specific capabilities to analyze unstructured data. Services like Google Cloud Functions and Google App Engine provide platforms for running applications, while Google Kubernetes Engine and Google Compute Engine are more focused on orchestrating containerized applications and providing virtual machines respectively. Similarly, Google Cloud Storage is primarily for storing data, and Google Spanner is designed for relational database management, rather than directly analyzing unstructured

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