Exam AZ-900 topic 1 question 13 discussion

Machine Learning Studio (classic) is a drag-and-drop tool you can use to build, test, and deploy predictive analytics solutions. Azure Cosmos DB is a fully managed NoSQL database for modern app development. AI Fits with ML not with Cosmos DB so ANs B

Answer is NO. Azure Cosmos DB is a fully managed NoSQL database for modern app development. Single-digit millisecond response times, and automatic and instant scalability, guarantee speed at any scale.

Azure Cosmos DB is a fully managed NoSQL database

o CosmoDB é um banco de dados

Cosmos DB = Data storage (NoSQL). its only used for storing training ai data but it cant build test or deploy models AI/ML = Azure Machine Learning, Databricks, Cognitive Services.

Cosmos DB is a database service, not an AI solution, the given solution does not meet the goal.

Azure Cosmos DB is a NoSQL database service designed for high performance, scalability, and global distribution. It's a fully managed service, meaning Azure handles all the infrastructure, scaling, and maintenance for you. Schema-less: This makes it ideal for applications where the data structure might change frequently or isn't strictly defined (e.g., JSON-based storage).

For AI, Azure ML and Azure Cosmos DB is a database.

Azure Cosmos DB is a fully managed NoSQL database for modern app development.

it is not specifically geared towards building, testing, and deploying predictive analytics. For AI and predictive analytics, you should consider using **Azure Machine Learning**.

B. No The solution does not meet the goal. Azure Cosmos DB is a globally distributed, multi-model database service that can be used to store and retrieve data for various use cases. However, it is not specifically designed for building, testing, and deploying predictive analytics solutions. To build, test, and deploy predictive analytics solutions in Azure, you should make use of Azure Machine Learning, which is a cloud-based service that provides a platform for building and deploying machine learning models. Azure Machine Learning supports a wide range of AI and machine learning scenarios, including predictive analytics. It provides a variety of tools and frameworks, including Jupyter notebooks, Python, R, and SQL, to help data scientists build, test, and deploy machine learning models. Therefore, the recommended solution should be to use Azure Machine Learning instead of Azure Cosmos DB to meet the goal of building, testing, and deploying predictive analytics for the AI solution.

The answer is B. No Azure Cosmos DB is a globally distributed, multi-model database service, and while it is a powerful solution for managing and querying data, it is not specifically designed for building, testing, and deploying predictive analytics models. For building, testing, and deploying predictive analytics models, you would typically use machine learning services and platforms provided by Azure, such as Azure Machine Learning. Azure Machine Learning provides tools and services specifically designed for creating, training, testing, and deploying machine learning models, including predictive analytics models. So, the solution of using Azure Cosmos DB does not meet the goal of building, testing, and deploying predictive analytics for the AI solution.

Agree cosmos DB is not the correct choice

Azure Cosmos is not an AI service

https://learn.microsoft.com/es-es/azure/cosmos-db/introduction

No, the solution does not meet the goal. Azure Cosmos DB is not the appropriate service for building, testing, and deploying predictive analytics for an AI solution. You should consider Azure Machine Learning or Azure Databricks for these purposes

Only if Azure Cosmos DB is used with Azure Synapse Link the goal of building, testing, and deploying predictive analytics for AI solution will be met.