Lift-and-shift is potentially a very efficient method to move your applications to the cloud. You need to be aware, though, of the implications of the pay-as-you-go pricing model that comes with a cloud deployment. Check out our 3 tips to ensure lift-and-shift delivers the most cost-effective solution.
This blogpost will look into the evolution that AI has made in order to become what it is today. Next to that we will look forward, how AI can likely impact our future. Lastly, we will try to formulate a plan of attack that companies need to consider to be best prepared for the drastic changes that AI will have on our way of working.
AWS Glue, the serverless ETL service of AWS, supports two types of jobs: Spark and Python shell. In this article, we'll focus on Python shell jobs and explain how you can make optimal use of your S3 Data Lake using Athena within Python shell jobs.
Before you can generate insights from your data, you need to move those data from an operational to an analytical environment - a process commonly referred to as data ingestion. An event-driven architecture provides an elegant way to achieve a process marked by timeliness, performance, and cost-effectiveness.
Data science & Engineering
Half day
350
Mechelen
