Azure Data Lake Interview Questions
What is an Azure Data Lake ?
What are the core features of the Azure blob storage service?
Assume that you are working for XYZ organization as azure developer and your organization is moving to cloud from on premise location. As a part of this activity you may need to store data which is not to be accessed from outside the virtual machine to which the disk is attached.. Which Azure storage solution would you prefer for this situation and why?
Assume that you are working for ABC organization as azure architect and your organization is building enterprise solutions having multiple applications. As a part of this solution multiple components want to communicate with each other using the asynchronous messages. Which Azure storage solution would you prefer for this situation and why?
Assume that you are working as a data engineer for Azurelib.com. Your application is storing the data with the cloud as your blob storage. Application is generating some reports which need to be accessible to third-party applications. However, you want this to be accessible only for the next 7 days. After that, it should automatically not be allowed access to these reports. How could you solve this problem?
Which protocol is used by the Azure file for accessing the share files?
What are the main components of Azure Data Lake Analytics?
Can you explain what blob objects are in the context of Azure Data Lake?
What is your understanding of a job in the context of Azure Data Lake? How does it differ from other platforms like Spark or Yarn?
What is the process used by Azure Data Lake Analytics to transform data?
What is an object store in context with Data Lake?
What is the default retention period for an object in Azure Data Lake Store? How can it be changed?
What types of files can be stored in Azure Data Lake Store?
What is the max size of a file that can be uploaded to Azure Data Lake Object Storage?
What are some use cases for Azure Data Lake?
What is the maximum size allowed for a batch in Azure Data Lake Analytics?
What are the differences between Azure Data Lake and other cloud-based big data solutions like AWS S3, Google Cloud Storage, or IBM Bluemix?
What are the differences between Azure Data Lake and other cloud-based big data solutions like AWS S3, Google Cloud Storage, or IBM Bluemix?
What is the advantage of using Azure Data Lake over Amazon Web Services S3?
What do you understand about Big Data? What challenges does it solve?
What is Hadoop? How does it work?
What are the three V’s of Big Data?
What are containers? What’s the difference between Docker and Kubernetes?
Frequently Asked Questions
Azure Data Lake is a cloud-based storage and analytics service that allows businesses to store, process, and analyze massive amounts of data. It can store structured, semi-structured, and unstructured data types, including images, videos, and logs.
Jobs in Azure Data Lake can include data scientists, data analysts, data engineers, and data architects, among others. Each role involves working with data to some degree, but the specific responsibilities and required skills may differ.
Some key skills required for working with Azure Data Lake include expertise in data storage, processing, and analysis, as well as proficiency in data manipulation tools such as SQL and Python. Familiarity with Azure cloud computing and big data technologies is also beneficial.
Experience requirements vary depending on the specific job and level of seniority. Entry-level roles may require a bachelor’s degree in a related field and some experience with data analysis, while more senior positions may require several years of experience in data engineering or architecture.
Salaries for Azure Data Lake-related jobs can vary widely based on factors such as job title, location, and experience level.
However, some estimates suggest that data engineers can expect to earn an average of $100,000 to $150,000 per year.
Data security is a critical aspect of Azure Data Lake, as it involves storing and processing sensitive business information. The platform provides various security features such as access controls, encryption, and compliance with various regulatory standards.
. Azure Data Lake offers many unique features and advantages compared to other big data platforms, including its integration with other Azure services, flexibility in data processing, and support for a wide range of data types.
Yes, Azure Data Lake can be used for real-time data processing through integration with other Azure services such as Azure Stream Analytics.
Many companies across various industries, including healthcare, finance, and retail, are using Azure Data Lake for data storage, processing, and analysis.
. Azure Trainings offers a range of training and certification options for individuals interested in working with Azure Data Lake, including online courses, certifications, and documentation.