Azure Data Lake Analytics

Features of Azure Data Lake Analytics

Dynamic scaling

Data Lake Analytics dynamically provisions resources and allows you to do analytics on data ranging from terabytes to petabytes. You only pay for the processing power that is used. You don't have to modify code when growing or reducing the quantity of data stored or computing resources employed.

Develop faster, debug, and optimize smarter using familiar tools

Data Lake Analytics has strong integration with Visual Studio. You may use familiar tools to execute, debug, and tune your code. U-SQL job visualizations show how your code performs at scale, allowing you to readily find performance bottlenecks and minimize costs.

U-SQL: simple, familiar, powerful, and extensible

U-SQL is a query language that combines the familiar, easy, declarative nature of SQL with the expressive capability of C#. The U-SQL language uses the distributed runtime that runs Microsoft's internal exabyte-scale data lake. SQL and.NET developers may now handle and analyze data using their existing skills.

Integrates seamlessly with your IT investments

Data Lake Analytics utilizes your existing IT investments for identification, management, and security. This technique simplifies data governance while also making it simple to extend your existing data applications. Data Lake Analytics comes with built-in monitoring and auditing and is connected with Active Directory for user management and permissions.

Affordable and cost-effective

Data Lake Analytics is a low-cost approach for handling large amounts of data. When data is processed, you are charged on a per-job basis. There is no need for hardware, licensing, or service-specific support agreements. The system automatically scales up or down as the project begins and ends, ensuring that you never pay for more than what you require.

Works with all your Azure data

Data Lake Analytics uses Azure Data Lake Storage Gen1 for maximum speed, throughput, parallelization, Azure Storage blobs, Azure SQL Database, and Azure Synapse Analytics.

In-region data residency

Customer data is not moved or stored outside of the region in which Data Lake Analytics is implemented.

Security Controls by Azure policy

Regulatory Compliance in Azure Policy offers Microsoft-created and managed initiative definitions, known as built-ins, for compliance domains and security controls associated with various compliance standards. You may assign the built-ins for a security control to ensure that your Azure resources comply with the specified standard. The compliance domains and security controls for Azure Data Lake Analytics are listed below.

1. Azure Security Benchmark
2. Azure Security Benchmark v1
3. CIS Microsoft Azure Foundations Benchmark 1.3.0 
4. FedRAMP High
5. FedRAMP Moderate
6. HIPAA HITRUST 9.2
7. New Zealand ISM Restricted
8. NIST SP 800-53 Rev. 5
9. RMIT Malaysia

Azure security baseline for Data Lake Analytics

This security baseline applies Azure Security Benchmark version 1.0 guidelines to Data Lake Analytics. The Azure Security Benchmark guides how to protect your cloud solutions on Azure. The data is grouped around the security measures outlined by the Azure Security Benchmark and the accompanying Data Lake Analytics guidelines.

Network Security

• Within virtual networks, keep Azure resources safe.
• Intercept communications from known-malicious IP addresses.

Logging and Monitoring

• Set up central security log management.
• Make audit logging for Azure resources available.
• Configure the security log storage retention period.
• Logs should be monitored and reviewed.
• Enable notifications for unusual activity.

Identity and Access Control

• Keep track of all administrator accounts.
• Change default passwords as needed.
• Dedicated administration accounts should be used.
• Use single sign-on with Azure Active Directory (SSO)
• For all Azure Active Directory-based access, use multi-factor authentication.
• For all administrative activities, use specialized computers (Privileged Access Workstations).
• Log and notify on unusual administrator account activity.
• Only manage Azure resources from authorized places.
• Make use of Azure Active Directory.
• Review and reconcile user access regularly.
• Keep track of attempts to access deactivated credentials.
• Account sign-in behavior variation should be reported.

Data Protection

• Keep a record of sensitive information.
• Isolate systems that store or process sensitive data.
• Track and prevent the unlawful transmission of critical information.
• Encrypt all sensitive information in transit. 
• Identify sensitive data using an active discovery technique.
• Control resource access using Azure RBAC.
• Encrypt sensitive data at rest.
• Changes to essential Azure resources are logged and alerted on.

Vulnerability Management

• Use automated vulnerability scanning software.
• To prioritize the remedy of detected vulnerabilities, use a risk-rating approach.

Inventory and Asset Management

• Make use of an automated asset-finding system.
• Keep track of asset metadata.
• Delete illegal Azure resources. Keep an eye out for unauthorized Azure resources.
• Use only Azure services that have been authorized.
• Limit the ability of users to interact with Azure Resource Manager.

Secure Configuration

• Create safe setups for all Azure resources.
• Keep Azure resource configurations safe.
• Azure resource configuration should be securely stored.
• Automate the configuration monitoring of Azure resources.
• Avoid unintentional credential exposure.

Malware Defense

• Pre-scan files to be uploaded to Azure non-computing resources

Data Recovery

• Maintain frequent automatic backups.
• Perform entire system backups as well as any customer backups.
• Validate all backups, including those handled by customers.
• Ensure backup and customer-managed critical security.

Incident Response

• Make an incident response manual.
• Create a method for incident grading and prioritizing.
• Security response processes should be tested.
• Configure security incident alert alerts and provide contact information for security incidents.
• Add security alerts to your incident response system.
• Responding to security notifications should be automated.

Penetration Tests and Red Team Exercises

• Conduct frequent penetration testing on your Azure resources and verify that all key security discoveries are addressed.

Frequently Asked Questions

What is the use of Azure Data Lake?

Azure Data Lake contains all of the tools needed to enable developers, data scientists, and analysts to efficiently store data of any size, shape, or speed and perform all sorts of processing and analytics across platforms and languages.

How do I use Azure Data Lake Analytics?

Creating an Azure Data Lake Analytics (ADLA) Account. Log in to the Azure portal using your credentials. In Azure Services, click on Data Lake Analytics. In the New Data Lake Analytics account, enter the information. Click on Review+Create.

What is Azure Data Lake Analytics?

Azure Data Lake Analytics is a real-time analytics job service that makes massive data easier to understand. Over petabytes of data, quickly design and run massively parallel data transformation and processing programs in U-SQL, R, Python, and.NET.

Conclusion

In this article, we have extensively discussed Azure Data Lake Analytics. With the help of the above discussion, we may conclude that Azure Data Lake Analytics is a job service for on-demand analytics that simplifies big data.

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