PodChats for FutureCIO: Futureproofing your database strategy

A database is a collection of structured information, or data, typically stored electronically in a computer system. 

A data architecture is a framework of models, policies, rules and standards that an organization uses to manage data and its flow through the organization. Given how and where data today is created, consumed and managed, you have to wonder whether the approaches to data, data architectures and databases are still effective in today's hybrid, multi-cloud approach to doing business. 

In this PodChats for FutureCIO, we are joined by Karthik Ranganathan, co-founder and CTO, YugabyteDB to get his view on the state of data, data architectures and databases, and more importantly, how do we futureproof our database strategies in today's complex, run-from-anywhere digital society.

1.       Define data architecture and how does it relate to an organisation's database strategy? 

a.       Where is the impact to database strategy most significantly?

2.       Given that in Asia, we will likely have a hybrid approach to how organisations choose to run their business applications – on-premises public and private cloud (with a mix of SaaS, on-premises off-the-shelf software, and in-house developed software). 

a.       And allowing for regulations on data sovereignty, how should CIOs and CTOs architect their database strategy? 

b.       What is your recommendation for a metadata management strategy where you have heterogeneous databases?

3.       How to choose the right database, and is there such a thing as one database for all use cases?

4.       For organisations that choose to be cloud-only, given that they will likely be using multiple SaaS applications – not to mention data protection strategies – what should be the approach to deciding which data architecture and database strategy to consider?

5.       The rise of democratised data is predicted to force enterprises to reinvent their data architecture frameworks. What (How) should CIOs and data architects consider as regards to their enterprise data architecture to futureproof against evolving business needs?

6.       How do you solve/provision for the lack of skills in the market today?