At Northwest Data Consulting we provide consulting services focused on data analytics, engineering, AI, and machine learning in the Pacific Northwest and beyond.

Make the most of your data

Let’s be realistic: getting the most out of your data can be difficult. These days, even many small companies are dealing with volumes that would have been considered ‘big data’ just a few years ago. And it’s not just the volume of data which is proliferating, but the number of sources as well. You might have data for your application, HR, finance, customers, sales, project management, and more. The average small company (fewer than 500 employees) has 172 applications in their tech stack, spends $7.9m/year on tech, and adds 4.4 new applications per month. And if you’re a tech company, the data picture is even more complicated, because you’re probably using even more tools. Every time you add an application, the picture gets more complex because each one of those apps might require interfacing or integration with several others, so complexity grows non-linearly with the number of applications in your stack.

There are a number of reasons why research shows that most companies are not using data the right way. We’ve reached an inflection point where the enormous and rapidly growing number of tools available for working with your data can easily be a liability for companies that cannot properly navigate the data space. Every day we read stories of businesses that are achieving big wins with their cloud deployment, automation, AI, and so on. But for every one of these companies that have found a formula for transforming their business, many more are struggling to find the right formula for success, and that struggle is costly.

Sometimes you do need new and/or better tools (though newer isn’t always better). I’m continually astonished at the number of companies that conduct their analytics as if they were still operating in 2010 or 2000 (I’m not joking), blissfully (or more like agonizingly) unaware of those better tools which could dramatically improve their analytics operations. There are more companies who are aware that they need better tools, but struggle with the decision of which tools, in which combination, will work best for them. Even when they have identified their ideal stack, yet more companies have difficulty organizing their team efforts to make best use of those tools. The most important solutions are not always technical, or at least not primarily so. Sometimes those solutions are cultural and organizational. You can have the best individual team members, and the best tech stack, but if that team isn’t organized properly, you will still fall short in getting that critical insight that is so important to the success of your business.

Are you overwhelmed with data? Let us help you find the right technical and organization formula to make your data operations fire on all cylinders. Schedule a consultation with me on Square to get started with your data-driven transformation. Initial consultations are free.

Github Pages Custom Domain DNS Configuration

Guy Cutting published on 2023-07-23 included in Web

I’m thrilled to find an ideal set up for this site, which uses GitHub Pages for hosting and GitHub Actions for automated build and deployment. There was one last piece to the puzzle of finally launching the site, and that was configuring the custom DNS with GitHub Pages. When Pages hosts your site, it does so by default at a URL like https://gdcutting.github.io/nwdataconsulting/. There’s nothing wrong with that URL as-is, but for branding a business, we obviously want a top-level domain that reflects the business name (like https://www.

OpenAI Model Performance Degrading In Recent Weeks

Guy Cutting published on 2023-07-23

ChatGPT Model Performance In Question OpenAI has been making all sorts of headlines in recent months after its breakthrough performance with the Chat-GPT3 model. One of those records was the fastest application debut (in terms of user downloads) in history, reaching 100m users in January, just two months after launching. But serious questions are already emerging about the long-term trajectory of the company and its flagship chat models. User data from May and June showed a ten percent drop in user base from month to month.

Automated Hugo Deployment using GitHub Pages

Guy Cutting published on 2023-07-19 included in Web

Overview After experimenting with various ways to approach the site build, I finally find what I think is the best, most streamlined method: deploying on GitHub pages, using the automatic GitHub Actions to perform the Hugo build on the server side whenever changes are pushed to the build branch. This means that all I have to do to update the live site is to execute a handful of git commands (add files, commit, push), and everything else (the Hugo build and deploying the new rendered HTML and other files) happens automatically, making the process about as easy as possible.

Overwhelmed by data?

Guy Cutting published on 2023-04-14 included in Data Studies

I recently came across a couple of articles that raise a common issue that organizations must address in dealing with their data: being overwhelmed. Here’s the first piece: How To Move Forward When You’re Feeling Overwhelmed By Data Another piece focuses on marketing data, but is relevant to the larger data discussion: 67% Of CMOs Say They Are Overwhelmed With Data Being overwhelmed is one of the biggest problems that organizations encounter when dealing with data.

What does it mean to be 'data-driven'?

Guy Cutting published on 2023-04-12 included in Data Studies

Introduction One of the many great resources for me on my professional journey has been the book Creating A Data-Driven Organization, by Carl Anderson. I would recommend it for anyone who’s involved in working with data, from managers and executives, to analysts, scientists, engineers and others. Prerequisites The first line of Anderson’s book is that “Data-drivenness is about building tools, abilities, and, most crucially, a culture that acts on data.” In explaining further what it means to be data-driven, Anderson defines a few prerequisites:

What's the relationship between data analytics, data science, and data engineering?

Guy Cutting published on 2023-04-11 included in The Data Organization

This diagram is helpful for visualizing the relationship between data engineering, data science, and the business stakeholders. Thanks to David Holm on Twitter. A subject that is sometimes the source of ambiguity and confusion is the relationship between data analytics, data science, and data engineering. Increasingly common usage of such terms such as data analytics engineering, business intelligence engineering, and others can make it even more unclear where the boundaries between these categories and roles actually lie.