How to Save Money and Control Costs with Azure Data Lake Analytics
Where there is great power there is great responsibility
Azure Data Lake Analytics with its serverless approach and scale-up U-SQL query execution puts a lot of power in developers hands. As enterprises start exploring what is possible with Azure Data Lake and their datasets start growing, it becomes ever more important for their developers and administrators to a develop a sense of what they are spending on big data and how they can most efficiently use their budget for big data.
We’ve spoken to a lot of you out there, collected the top questions and experiences, and used created a document that is a MUST-READ for every ADLA developer and adminstrator!
Please look through this doc and let us know what you think! Are you looking for any other samples, features, or improvements? Let us know and vote for them on our UserVoice.