Data is growing rapidly, and companies around the world are rushing to position themselves to take full advantage of the information and benefits that today’s AI and ML toolset can add to their organization.
However, there are several challenges associated with managing a traditional enterprise data warehouse, so migrating it to a modern cloud environment is key.
With this in mind, Thomas FowlerCTO at CloudSmiths, and Louis van Schalkwykof Technical Operations at Digicloud Africa, will be speaking on “The Benefits of Building a Modern Unified Data and Analytics Platform” at the ITWeb Cloud & Data Center Summit 2022, which will be held at The Capital on Park on November 1.
According to Van Schalkwyk, extracting value from data requires a multifaceted approach that requires multiple tools, services and skills to get the right result. “Data is everywhere, often fragmented, incomplete and outdated. Not all data is available from one place. All these factors make it difficult to get accurate information from your data.”
When it comes to building a modern unified platform, he says customers need to make sure they have robust data pipelines that can handle failures, scale automatically and take full advantage of the managed services offered by cloud providers.
Then, Van Schalkwyk says, they need to make sure they’re choosing the right data warehouse solution that will meet their future aspirations, such as machine learning. “It’s important to know that the enterprise data warehouse they choose can scale with them and provide the tools they need for the next five to ten years.”
There are also a few pitfalls to avoid, he explains. “Avoid being locked into systems with complex and proprietary licensing models. Lots of services that are easy to start with but become very expensive when you need to scale them. Also use systems that can talk to and integrate with other systems, and avoid services that require manual management of clusters and servers as much as possible.”
Delegates attending their talk will hear how other SA companies have moved analytics workloads to Google Cloud, using Vertex AI as a single platform to manage data workloads, from loading and transforming to serving ML models hosted on Google Cloud.