I am working on two storage-related features for Computer Weekly, with April deadlines.
When is cloud data storage the answer?
Has there been a cooling off in enterprise enthusiasm for cloud storage?
In this piece we will look at some reasons firms should move their data storage to cloud infrastructure.
The piece will follow up on this from earlier in the year: Cloud is not always the answer: Five reasons why
We aim to cover
- When does on site storage fall short and how cloud can be better?
- Performance / availability / operations:
- IT management:
- Costs
- Agility and responsiveness
- Data protection and compliance
The deadline for leads is 1700, Thursday 28 March.
How does AI affect data storage
The second looks at the impact of AI workloads on storage. This includes how data are used in training models, how AI analytics are used, where data are sourced and where they are stored. The piece will also cover compliance, which is a growing concern for anyone using AI.
The piece will not be limited to LLMs or generative AI, but all the different forms of AI being used by enterprises.
On the technology side, we’ll cover IO, the types of storage being used, where the data processing bottlenecks sit, how to feed GPUs and where to store the outputs from AI systems. But that’s not the whole picture.
I’m looking for analysts and consultants with direct experience of AI projects.
Deadline for leads: Wednesday 10th April, 1700hrs.
To contribute to either piece, please contact me by email in the first instance.