Azure Data Lake Analytics

Azure Data Lake Analytics services are beneficial when working with a lot of data. It can process enormous amounts of data extremely quickly. Service is secure and easy to set up, build, scale, and run on Azure. Regarding big data analytics and reporting, parallel processing has a significant impact. It consolidated our analytics from multiple systems and increased our analysis productivity. This tool has excellent support for reporting tools like Power BI and is very quick when performing analytics.

For us we have an enterprise of SQL users at all skill levels, and this product is very SQL friendly and extremely fast in creation of data aggregates and analysis. If you are an Azure storage user, considering using Lake Analytics over top of your blob or any other storage just adds complementary services and functions native to your existing architecture.

U-SQL is the language used by Azure Data Lake Analytics for query and processing. The SQL and C# computer languages are combined to create the U-SQL language. The U-SQL language is easily learned by SQL Server database specialists.

Azure Data Lake Analytics is a perfect fit for those who are needing to have a data lake where you have some tools to process and visualize the data. I would say it's a smart choice for companies going to the cloud due to the fact of the quick learning and easy implementation.

Azure Data Lake Analytics is best suited for -
1) Storing raw data ( original data format)
2) You can store Unstructured, semi-structured and structured in it
3) Data lake follows schema on the reading method in which data is transformed as per requirement basis

Not the best scenario when -

1) Data volume isn't great
2) Latency, and querying speed isn't the most important criteria

It is great for analyzing large workloads and large amounts of data, but I think that there needs to be a certain amount of data even present, to begin with, to make the additional costing worthwhile.