Azure Services for Big Data Analytics
Question
You are working in a cloud company and you have been assigned the responsibility of building an enterprise data lake on Azure and accomplish big data analytics.
Which of the following Azure Service would you use in this scenario?
Answers
Explanations
Click on the arrows to vote for the correct answer
A. B. C. D. E.Correct Answer: B
Azure blobs allow storing and accessing the unstructured data at a massive scale in block blobs.
Azure blobs are recommended to use: When you want your applications to support streaming and random-access scenarios.
When you want to access application data from anywhere.
When you want to develop an enterprise data lake on Azure and carry out big data analytics.
Option A is incorrect.
Azure Files offer fully managed cloud file shares that can be accessed from anywhere using the industry-standard Server Message Block (SMB) protocol.
Azure files are not the right choice for the given scenario.
Option B is correct.
Azure Blobs is the best choice to be used in the given scenario.
Option C is incorrect.
Azure Disks help in persistently storing and accessing the data from an attached virtual hard disk.
In the given scenario, using Azure Disks is not the right choice.
Option D is incorrect.
Azure Queues is the best choice for decoupling the application components and using asynchronous messaging to communicate among them.
Option E is incorrect.
Azure tables should be used to store flexible data.
In the given scenario, using Azure Tables is not the right choice.
To know more about core Azure Storage services, please visit the below-given link:
In this scenario, the most appropriate Azure service for building an enterprise data lake and accomplishing big data analytics is Azure Blobs.
Azure Blobs (short for binary large objects) is a massively scalable object storage service that can store unstructured data such as text, binary data, images, and videos. It is ideal for storing large volumes of unstructured data, such as log files, media files, and data generated by Internet of Things (IoT) devices.
Azure Blobs supports a variety of data access methods including REST APIs, SDKs, and command-line tools. This allows for seamless integration with various big data analytics tools such as Apache Hadoop, Spark, and Storm.
Azure Files, on the other hand, is a fully managed file share service that is built on the Server Message Block (SMB) protocol. It is designed for hosting files and folders that can be accessed from anywhere using the SMB protocol.
Azure Disks are block-level storage volumes that can be attached to virtual machines. They are optimized for high performance, low latency, and durability. They are not suitable for storing large volumes of unstructured data.
Azure Queues and Azure Tables are both NoSQL storage services. Azure Queues provide a reliable messaging solution for queuing and processing asynchronous requests, whereas Azure Tables provide a key-value store for storing structured data. However, neither of these services is well-suited for storing large volumes of unstructured data such as those found in a data lake.
In summary, Azure Blobs is the most appropriate Azure service for building an enterprise data lake and accomplishing big data analytics due to its scalability, support for various data access methods, and seamless integration with big data analytics tools.
