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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.
Moving capabilities to a cloud provider such as Microsoft Azure is pretty straightforward. However, given the depth and breadth of service offerings provided by Azure, it’s easy to miss the product’s less obvious capabilities. If you're implementing a Microsoft Azure cloud platform, you'll want to consider these five services to save time, money, and your sanity.
Making strides as a top contending cloud provider is Google Cloud Platform (GCP). In the growing cloud market, it’s important for organizations to understand the core products and services, how GCP can be utilized and see it in action.
If you’re looking for serious change, why not focus on your IT professional career? How much can you really learn from a five-point “Hack” list that speaks to everyone, yet no one? Not much. Too many articles rattle off a quick hit list. After reading this goal-setting guide you’ll be able to develop a game plan to bring successful change in your professional life.
Getting a clear understanding of what Amazon Web Services (AWS) is and how it can help your business can be a daunting task. The depth and breadth of AWS is significant, comprising over 100 services in dozens of data centers located in 16 Regions throughout the globe (with five more in the works). They offer computing, storage, networking, deployment, management, and a host of "supporting" services like queues, serverless functions, and e-mail. There's a great chance that AWS has more than a few products to help you work faster, smarter, and more cost effectively. So, where should you start?