This blog explores AgileData’s use of Google Cloud, specifically its BigQuery service, for cost-effective data handling. As a bootstrapped startup, AgileData incorporates data storage and compute costs into its SaaS subscription, protecting customers from unexpected bills. We constantly seek ways to minimise costs, utilising new Google tools for cost-saving recommendations. We argue that the efficiency and value of Google Cloud make it a preferable choice over other cloud analytic database options.
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5E’s
As Data Consultants your customers are buying and outcome based on one of these patterns – effort, expertise, experience or efficiency.
We outline what each of these are, how they are different to each other and how to charge for delivering them.
Agile DataOps
TD:LR Agile DataOps is where we combine the processes and technologies from DataOps with a new agile way of working, to reduce the time taken and increase the value of the data we provide to our customers What's in a...
The “Killer” Feature
One feature to rule them all As product managers we are always looking for the next “killer feature” for our product. You know the one, that feature that will become the magical thing that will have customers flooding...
3 types of product features
Our UX/UI journey is accelerating We are currently full steam into the development of the initial User Interface for AgileData.io. The team have done some awesome work on the UX designs for a bunch of the core screens,...
Reducing Manual Effort, Everywhere, Every-time
Some tasks seem really small and only take minutes, but multiply that effort by completing that task a hundred times and you have found a task that should be automated. Collect your data In AgileData we automate the...
Why assumptions are just that
When we first sketched out our plans for AgileData we were pretty clear what AgileData would do and what it wouldn’t do. Those assumptions didn’t last long. Combine with magic We knew we wanted to focus on what we call...
Micro Actions, ensuring a little bit of Magic Happens Here everytime
We are currently doing some work on creating rule patterns that enable us to automagically find duplicate Concept values and create a master view of them. For example creating a master view of Customers, or a master...
Buy, Build or Lease
One of the (many) things we needed to decide when we started to build out the AgileData Minimal Magical Product (MMP), was which capabilities we would build vs which capabilities we would lease or buy. As part of our...
What problem(s) does AgileData solve?
This should be an easy one for me to answer right? Understand the customers problem first We get told in startup land that you need to understand the customers problem in-depth, before you start building your product....
Why we chose Google Cloud as the infrastructure platform for AgileData
Pick a few things that really matter, not thousands of “requirements” We when first started developing the core of the AgileData backend for the MVP, we knew we would need a cloud database to store...
Why we founded AgileData
My co-founder Nigel and I have been working in the data and analytics domain for over 30 years (well I have, he is slightly younger). We have both held multiple roles through these years, Nigel primarily in the...