From ingest to insight: How IBM addresses every stage of the AI data pipeline
Despite the IT world evolving at a rapid pace, the issues the businesses are facing when it comes to technology decision making have not really changed. It’s still about cost saving, ease of management, simplified IT, the fear of data loss, and, performance.
But the industry IS using new words for the same thing. And that’s, agility, modern, secure, ROI in months, open, and performant. So really, it’s the same exam question, but a different answer.
One technology area that is jumping straight from the pages of a sci fi comic to business fact is AI or Artificial intelligence.
To meet today’s challenges and prepare for this future, businesses need AI solutions that integrate with your IT infrastructure and data strategy.
According to Gartner, “the success of machine learning and AI initiatives, relies on orchestrating effective data pipelines that provision a high quality of data, in the right formats, in a timely manner, during the different stages of the AI pipeline.
Only IBM addresses every stage of the AI data pipeline from ingest to insight.
IBM focus on three key areas for AI and modernising the infrastructure, to get the ready for AI:
- The concept of AI and big data requiring high performance, flexible, and unstructured data capabilities which comes in the form of fast, scalable file systems or object storage platforms.
- A set of products that are focused on hybrid multi cloud. As you bring resource from the public cloud to your ai stack you need a fluid and modern on premis storage infrastructure which enables you to seamlessly move data to IBM cloud or AWS, or similar.
- The need to ensure the protection of that data throughout the lifecycle. Particularly, in the case of AI, as you need to protect the results data as it is written.
To find out how you can streamline your data pipeline, with an end to end storage solution optimized for AI, Message me directly or comment below