How On-Demand Analytics Service Works with Azure Data Lake Effectively?
Azure Data Lake is becoming an analytics service that aims at analyzing big data in a simpler avatar. This will allow organizations to focus on running, managing, and writing jobs instead of monitoring a distributed infrastructure. Users use query to extract useful insights and change their data, instead of deploying, configuring or tuning hardware. These on-demand services can be used for handling a small or large scale business by an estimate of power requirement. Users will have to shell out for service while running, by creating a cost-effective investment. Also, the analytics service is designed to serve as Azure Active Directory which enables the user to manage roles and access, integrating with on-premises organization’s system in an actual manner.
Further, it comes with U-SQL language, which integrates the goodness of SQL gracefully with user codes expressive power. U-SQL’s scalable distribution query allows making sense of data across multiple SQL servers, besides in the store.
Besides, you can use SQL Server to Azure Migration tool, which helps to move SQL Server database to Azure. It allows the user to migrate corrupted data into the healthy state from a local server to Azure SQL Database. With this utility, you can perform selective migration of SQL server database objects.
Key Capabilities of Azure Data Lake Analytics
Here are following actions that will help to know the functionality of azure data lake. Please have a look:
- Dynamic Scaling
One can examine Data Lake analytics is specifically designed to improve performance while working in the cloud. It provides all the resources dynamically and capable to perform analytics operations on terabytes of data. It can move resources automatically, so users, only paying for the resources which are being used. User can work more effectively towards the goal of an organization by focusing the attention on logic and leaving process and storage part to Data Lake.
- Develop Speed & Optimize
Data Lake Analytics is perfectly aligned with the Visual Studio, offered known tools for running, debugging, or tuning the code. U-SQL’s Visualization supports the user in how their code works at a higher scale and helps to identify the performance-related issues that can be used for optimizing costs.
- U-SQL – Simple & Powerful
Data Lake Analytics that comes with U-SQL language, being simple and considered as the essence of familiarity. Additionally, it is designed to work with huge data that makes it efficient on the Data Lake.
- IT Investments for Perfect Integrations
Data Lake Analytics uses the user existing investments to manage, identify, and secure data warehousing tasks. It eases the data governance that makes it easier for users to extend existing data applications in a short time. Data Lake Analytics uses built-in monitoring features and elements of auditing that works as per user permission and manages through its integrated Active Directory.
- Cost-Efficient and Affordable
Data Lake Analytics is cost-effective and fair service for working on big data scenarios. The user pay depends on the service operation time, and infrastructure intelligence service that automatically cuts power just as soon the task is completed. This ensures that user charges only for power being used in performing his/her tasks. Users do not have to spend on all sorts of license, hardware or agreement to consume services.
- Access Azure SQL Database
Data Lake Analytics that work best with Azure Data, promising a high level of output and performance when offering parallelization for big data workloads. It can also be used with both Azure SQL Database and Azure Blob Storage.
In this blog, we have discussed all the advantages of Microsoft Azure Data Lake Analytics. Also, we have suggested an alternate method (100% Secure and Reliable) to let users understand how On-Demand analytics service works with Azure Data Lake. SQL to Azure Database Migrator is the best approach that helps to perform migration from SQL Server to Azure SQL database in an efficient way.