Serverless Static Blog powered by Hugo, Github, Cloud Build and Firebase

One of the announcements I liked the most from Google Cloud Next 18 was Google Cloud Build (former Google Container Builder). I’ve been missing easy and lightweight CI/CD for GCP, especially with focus on serverless. I thought I would give it a try before setting it up for CI/CD in the open source data/analytics/ML solution I’m working on - DataHem. Hence, I figured I use it to power this blog. »

DataHem: open source, serverless, real-time and end-2-end ML pipeline on Google Cloud Platform

I’m excited to say that the project I’ve been working on the last year is now released as OpenSource (MIT license). DataHem is a serverless real-time end-2-end ML pipeline built entirely on GoogleCloud Platform services - AppEngine, PubSub, Dataflow, BigQuery, Cloud ML Engine, Deployment Manager, Cloud Build and Cloud Composer. When building ML/Data products, your most valuable asset is your data. Hence, the purpose of DataHem is to give you: - Full control and ownership of your data and data platform - Unsampled data - Data in real time - The ability to replay/reprocess your data unlimited times - Data synergies, i. »

Clarifying Analytics Requests = 5 x Why + So What

Most analysts want to avoid a situation where they spend a lot of time working on ad-hoc, vague and misguided analytics/data requests instead of focusing on hypothesis testing. But hey, you will not be able to avoid those requests entirely, so what can you do in order to clarify the requests you can’t hold at bay? I use two simple methods to clarify analytics requests: 5 x why? 5 Whys is an iterative interrogative technique used to explore the cause-and-effect relationships underlying a particular problem and I’ve found that it also works really well to clarify analytics requests. »

Bigquery Training Resources for Digital Analysts

In this post I’ve tried to collect different training resources that I’ve found useful for myself, some for free and some for a fee. The focus is using BigQuery for digital analytics. If you are one of the lucky digital analysts who work for an organisation with the 360 version of Google Analytics or Firebase Blaze, but not started using BigQuery? Then, don’t wait for it, enable the BigQuery Export (read this post if you are acting in EU) and learn how to use BigQuery. »