The 10 best tech companies to work for, and the skills they need LinkedIn's annual Top Companies list analyzes job demand and employee retention, and several tech giants top the list of places professionals want to work most. In the age of machine learning and AI in the cloud, everyone wants to do more with their data. With over 70% of enterprises using three or more clouds, it is important to understand the implications of where your data is stored and how it is managed. Leveraging a common database engine -- across clouds -- allows you to focus your efforts on your applications and not on idiosyncrasies of individual cloud databases. Join us for a live webinar, The Data Layer: IBMs Db2 in a Multi-Cloud World, where IBM software architect Bowen Turetzky will discuss: What multi-cloud means for your data; multi-cloud by design vs multi-cloud by accident; and what a multi-cloud data layer looks like The four key advantages of choosing IBMs Db2 managed services for a multi-cloud data layer solution How to leverage a common data layer across cloud providers with common tools Register for this exclusive webinar today! |
Additional TechRepublic resources | Leading enterprises understand the value of optimizing their high performance computing (HPC) resources, but they struggle with bringing meaningful change to their processes, assets, and infrastructure. For organizations looking to scale their... |
| Featured multimedia |
The 40 geekiest desk toys for IT people you can get on Amazon (and beyond) NanoPi NEO4 photos: Up close with the Raspberry Pi rival Photos: The 10 worst US cities for startups Today's recommended downloads | (IBM) (Quest Software) (Quest Software) (Quest Software) (Quest Software) |
| Featured survey |
Is your company using serverless computing services? We want to know. Take this 5-minute survey and get a free copy of the final research report. A special feature from ZDNet and TechRepublic | The AI and ML deployments are well underway, but for CXOs the biggest issue will be managing these initiatives, and figuring out where the data science team fits in and what algorithms to buy versus build. Connect with TechRepublic |
|