Building an Enterprise Data Lake on Azure
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:
For building an enterprise data lake on Azure and accomplishing big data analytics, the most suitable Azure service would be Azure Blobs (B). Azure Blob storage is a scalable and cost-effective storage solution for unstructured data. It is optimized for storing massive amounts of unstructured data, such as text and binary data.
Azure Blob storage is designed to handle large-scale, unstructured data sets, including text and binary data. The data is stored as blobs, which are objects that can range in size from a few bytes to several terabytes.
Azure Blob storage is ideal for data lakes because it can store a wide variety of data types, including unstructured, semi-structured, and structured data. It also provides the flexibility to manage data in any way that is suitable for the business, including managing data through batch processing or real-time processing.
Azure Blob storage is also highly available, durable, and secure. It provides redundancy options for data protection, including geographic replication and zone redundancy. It also offers encryption and access controls to protect data at rest and in transit.
Azure Files (A) is a fully managed cloud file share solution that is optimized for managed access from Azure virtual machines and on-premises environments. It is not suitable for storing large-scale unstructured data sets like a data lake.
Azure Disks (C) provides durable and high-performance block-level storage for Azure virtual machines. It is not suitable for storing large-scale unstructured data sets like a data lake.
Azure Queues (D) provide a messaging service for asynchronous communication between different components of an application. It is not designed for storing large-scale unstructured data sets like a data lake.
Azure Tables (E) is a NoSQL key-value store that can store semi-structured data. It is not optimized for storing large-scale unstructured data sets like a data lake.
