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This Certification Prep Guide provides an overview of the current Google Certified Professional Cloud Architect certification and offers helpful tips that you can use when preparing for your GCP certification exam.
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 AWS Certified Solutions Architect – Associate certification and offers helpful tips that you can use when preparing for your AWS Architect 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.
It’s been about 10 years since public cloud offerings like AWS opened up the world of big data analytics. This post examines the top five most useful architectures used for big data stacks to learn the sweet spots of each.
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.
In the digital age, people and intellectual property have supplanted physical assets as the most important criteria for determining the value of an organization. It is the employees who develop the next big product or improve the practices, processes, services and internal culture that add significant value to an organization.
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.
Google takes security to a whole new level thanks to their years of experience as one of the most popular targets on the internet for would-be hackers and denial of service bots. This led Google to build a sophisticated security infrastructure the likes of which few companies or organizations can claim. Google approaches security holistically and involves everything from the physical data centers, to the data pipelines between them, down to the training of each employee that is responsible for managing the infrastructure.