I am working up two further features for Computer Weekly.
AI, ML and the cloud
The first is looking at artificial intelligence, machine learning and RPA (robotic process automation), with a focus on what the cloud providers can offer enterprises to help them build AI and ML applications.
We want to examine:
- practices that work, and those that might not
- limitations (such as data ingress and egress costs, data protection regulations)?
- performance drawbacks in the cloud vs capacity advantages
- whether hybrid approaches to AI and ML, combining on-premises technology and the cloud, are effective and mature
- how do CIOs determine which workloads are effective in the cloud, and which are better on premises?
The deadline for leads for this article is Tuesday 16th August, with a view to completing any interviews by Friday 19th.
To contribute, please contact me by email. Many thanks.
Designing a data architecture
For this piece, we want to set out how an organisation should design a data architecture: what works, what doesn’t, what the benefits are, and what resources (tools, people and skills) that are needed.
This cuts into data management, but it’s less focused on tools, and more on the business processes. It might suit consultants and analysts most of all, but we are also keen to speak to a data analyst working in a business it possible.
At this stage the deadline is flexible, and I am open to discussions with experts about the direction the article could take (see here for some previous TechTarget coverage https://www.techtarget.com/searchdatamanagement/definition/What-is-data-architecture-A-data-management-blueprint).
To contribute, please email, in the first instance, with your views and background. I’d like to have contacts for interviews lined up by 26 August.