From the course: Machine Learning with SageMaker by Pearson

Unlock this course with a free trial

Join today to access over 25,200 courses taught by industry experts.

Data storage optimization and transfer in AWS

Data storage optimization and transfer in AWS - Amazon SageMaker Tutorial

From the course: Machine Learning with SageMaker by Pearson

Start my 1-month free trial Buy for my team

Data storage optimization and transfer in AWS

“

If you're dealing with machine learning and trying to predict some sort of feature, you're most likely dealing with a large data set. So we do need to touch on our ability to get data into AWS and how we could maybe potentially save some money along the way. So we have speed of ingestion of data into AWS, as well as the cost of ingestion of data into AWS. So why do we care? Efficient storage and transfer can reduce costs and improve performance. So getting that data into S3, for example, if we're using, for example, transfer acceleration, could be faster. As well, if we're doing different storage classes within S3, we could save some money. It is extremely important. When you're dealing with extremely large data sets, How can we get the data into AWS faster? And how can we maybe save a little bit of money along the way? Speeds up trading as well as inference, scales with demand, ensures data integrity and security during transfers. So if we are using AWS, most likely we're doing it in…

Contents