With the rise of modern data platforms and cloud-based solutions, BI has become just one part of a much larger data ecosystem. This evolution has presented data teams with a host of new challenges, primarily in terms of the skills and expertise to create and manage data products that meet the needs of data consumers.
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.
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.
A traditional data warehouse setup is no longer up to the many data challenges ahead. If you want to get ready for the future, regardless of the amount of data you are dealing with, you should check out Azure Synapse. This data analytics environment combines all components of a modern data platform.
