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Looking ahead at new and emerging certifications provides insight into the areas deemed valuable in the IT industry. If you are an early adopter or in a position where you need to show that you have the bleeding-edge expertise of a technology, this list of recent and upcoming certifications is for you.
Google Cloud certifications had a breakout year according to the Global Knowledge 2019 IT Skills and Salary Report. GCP Cloud Architect is the top-paying IT certification in North America and Europe, the Middle East and Africa (EMEA), while Google Cloud salaries are 34% higher than the average for North America. As more IT departments adopt multi-cloud strategies, Google Cloud skills are increasing in popularity.
In 2019, Microsoft has thoughtfully adapted their curriculum to boost Azure skills adoption. And to further speed up Azure consumption, Global Knowledge has stepped in to support Microsoft’s evolution and their new strategy. We’re fighting change with change. And here’s how we did it.
Cloud computing has risen from relative obscurity to the No. 1 tech area of interest in the world, according to the 2017 Global Knowledge IT Skills and Salary Report.
Cloud adoption continues to soar. In fact, worldwide Infrastructure-as-a-Service (IaaS) public cloud services grew by 29.5 percent in 2017, according to Gartner. If it’s not in a company’s current plans to utilize cloud technology, it most certainly will be (or should be) in the next couple of years.
This Certification Prep Guide provides an overview of the current MCSE: Cloud Platform and Infrastructure certification and offers helpful tips that you can use when preparing for your MCSE certification exam.
This Certification Prep Guide provides an overview of the current CompTIA Cloud+ certification and offers helpful tips that you can use when preparing for your CompTIA Cloud+ certification exam.
As far as modern architectures go, there are few more complicated than an IoT pipeline. You’ve got to consider an ingestion layer (typically streaming) that may undergo manic load. You’ve got to think of data tagging, storage (probably across multiple engines), archival and access—both internal and external. And all of it has to scale like crazy, be as cost effective as possible, and use automation wherever it can. Oh, and your boss needs the IoT pipeline built by tomorrow. Short timelines? Tight budget? Unrealistic expectations? Unfortunately, these asks are realities for many cloud professionals. AWS knows this and is here to help.
Behind various Google services lies the powerful Cloud AI, a neural net-based, machine learning technology that Google has perfected for use with services like image search and voice recognition. Here are five ways you could use Cloud AI to improve your business.
A longtime leader in data analytics, Google continues to earn their position by continually improving their data analytics offerings. Now, with Google Cloud Platform (GCP), you can capture, process, store, and analyze your data in one place, allowing you to change your focus from infrastructure to analytics that informs business decisions. However, you can also use GCP Big Data tools in combination with other cloud-native and open-source solutions to meet your needs. Below is an overview of GCP Big Data Tools and how you might utilize them to improve analytics.