Articles
Data doesn’t like to move, but in the cloud, it’s moved multiple times, across several technologies, using multiple services and languages.
Artificial intelligence has the potential to impact the data architecture and engineering professions like no tech trend ever before.
Decision-makers, business analysts and architects must help transform the data culture and thinking within organisations.
There is a need to change how the data industry operates, which should be incapsulated in a professional body and associated methodology.
Some potentially radical concepts are needed to prompt a different way of thinking to address some of the key challenges in the data industry.
Companies need to know there is more on offer than what they are used to from the standard cloud platform vendors.
The data lakehouse is a hybrid architecture that implements the best concepts of both a data warehouse and data lake methodology.
While a company can change its data warehouse approach, it must avoid falling into the trap of replacing this capability and methodology with just technology.
Companies should periodically re-evaluate their data warehouse approach and methodology, while avoiding the rabbit-hole of technology evaluation and selection.
Serve, enable, question, listen, engage and empower should be the new management mantra of data architecture that leads to a continual, virtuous cycle.
There is a long way to go to regain trust in architecture. For this to be possible, we need business to change how it perceives data architecture.
There are several principles to live by when it comes to data warehouse automation and its implementation in real life.