The volume of data collected by any given company is too much for the human mind to absorb, let alone organise and evaluate. Consequently, an increasing number of firms emphasise machine analysis of their consumer data to obtain valuable intelligence that may transform the way they think and act. An AWS cloud computing courses would give you a clear explanation for these.
In the end, if the data isn't based on a solid foundation - a single source of truth — it's useless.
A cloud data warehouse (CDW) can help in this situation. A CDW serves as a single source of truth for a user's data, enabling different departments to study and act on the same info.
Here's why a CDW is necessary for every customer analysis project:
Providing accurate data
A CDW is a single point of truth where data structure may be accessed. This prohibits product and development marketing departments from mining relevant information from numerous data repositories. CDWs are data warehouses that connect analytics and business intelligence tools to the data they contain. The hub ensures that an organisation's data is secure and provides a more relevant perspective.
Increasing the speed of detailed analysis
Non-technical individuals may quickly analyse data using Customer Analytics solutions that are not bound by SQL limitations. Far beyond "what" that typical business intelligence (BI) technologies give, product teams may extract the "why" and "how." The corporation can make faster and better strategic decisions because of quick access to research.
Creating a data stack for the future
As the amount of data flowing into brands rises, having a CDW to scale along with that data quickly will become increasingly important to their main contributions. With technologies like Amazon Web, Google Cloud, and others, creating a bespoke CDW has become simpler.
