Introduction
As the data grows with the business need, building an enterprise-scale analytics solution requires careful thinking. It forces organizations to think strategically on the resource setup, utilization, governance, and plumbing that must exist before actual workloads gets onboarded to Azure.
This learning path walks you through systematic architecture design on how one should approach the challenge
Data Management and Analytics
As organizations are striving to be competitive and remain viable in today's dynamic situations, they're looking for a data-first approach. They're looking for every opportunity to use data-driven insights to focus on the right directions for the business while cutting down the time to market. They're looking to easily access, consolidate, and unify data of many types in a structured way. This pattern allows them to not only generate value assets, but also to monetize at a lower cost of ownership. The cloud platform provides that agility and opportunity. Regardless of an organization's size, it could rely on cloud economics to deliver new innovations and improve business outcomes.
The true value of a cloud-based analytics solution comes from using modern technologies and architecture styles that constantly evolve.
The Data Management and Analytics scenario provides a prescriptive data platform design coupled with Azure best practices and design principles. These principles serve as a compass for subsequent design decisions across critical technical domains.