LATEST ARTICLES
Are you doing a lot of proof of concepts, or you're trying to figure out different ways to optimize your infrastructure and decrease costs?
Hi, I'm Peter Nichol, Data Science CIO. Allow me to share some insights. Today, we're going to talk about hyper converged infrastructure, also known as HCI, what it can do, and the potential benefits.
Is there a business case for in-storage data processing? Of course, there is, and I'm going to explain why. Hi, I'm Peter Nichol, Data Science CIO. Computational storage is one of those terms that's taken off in recent years that few truly understand. The intent of computational storage
Computational storage is all about hardware-accelerated processing and programmable computational storage. The general concept is to more data and computers closer together. The idea is that when our data is far away from our compute, it not only takes longer to process, but it's more expensive. This scenario is common in multi-cloud environments where moving and erasing data out is a requirement, but that requirement comes at a very high cost. So the closer we can move that data to our compute power, the cheaper it will be, and ultimately, the faster we will be able to execute calculations.
Are you curious about business disruption? What are the key drivers of change today, and how are businesses repositioning for a better tomorrow, maximizing growth internally.
Hi, I'm Peter Nichol, Data Science CIO. Today we're going to talk about business models and business model disruption. There are five main principles I wanted to cover that helped define how organizations today are driving disruption inside and outside their organizations.
Are you trying to deliver more functionality into production at a faster cadence? Are users asking your team to prioritize time to market over quality? Do you have release cycles longer than 3-4 days? Do you constantly review and prioritize issues that continue to resurface? You might be in a great position to benefit from DevOps.
Hi, I'm Peter Nichol, Data Science CIO. DevOps integrates the development and operations activity of the software development process to shorten development cycles and increase deployment frequency. DevOps centers around a hand full of critical principles. If you're ever unclear how DevOps might apply, always bring yourself back to the fundamental principles. This helps to drive the intent behind the outcomes achieved by adopting and implementing DevOps.
Have you ever been told to improve but weren’t sure what to work on? Have you asked your team to do better and improve their performance—and then, a week later, the group wants to have a discussion about precisely...
How are you leveraging automation in your organization today? Which parts of the company are optimizing artificial intelligence to enable a better customer experience?
Hi, I'm Peter Nichol, Data Science CIO.
Today, we’ll talk about natural language processing (NLP) and how...
Which activities do you do today that you should probably delegate? Similarly, which activities do your department own that probably should be delegated? Hi, I'm Peter Nichol, Data Science CIO. Today we're going to talk about managed service providers or MSPs.
Why make the shift to MSPs?
The concept behind a managed service provider is to shift ownership of daily activities to allow your team to focus on more important strategic priorities.
How are your teams forecasting work? How do you anticipate a budget when you're not sure what you're going to spend in a fiscal period. Hi, I'm Peter Nichol, Data Science CIO. Today we're going to talk about capacity-based funding. It's a concept that many have heard of, but few leaders execute effectively.
When you do root cause analysis, you always discover functionalities missed in testing, or something was put into production only to find it could have been identified earlier in the process. Hi, I'm Peter Nichol, Data Science CIO. What does shift left mean? Today we're going to talk about the concept of "shifting left and shifting right." Then last, we'll cover the "shifting in reverse" theory. All right, I made up the "shifting in reverse" theory. First, however, shifting left and shifting right are concepts that we will explore today.
Do you lead a technology team? Have you been asked to produce more features in less time? Is your team expected to deliver more functionality to business users at lower cost levels? Hi, I'm Peter Nichol, Data Science CIO. Today, I'm going to share some insights on how to do precisely that. The concept is called CI/CD, or continuous integration and either continuous delivery or continuous deployment. So there are three steps of this model: continuous integration, continuous delivery, and continuous deployment.