Case study
Analytics 40% Cheaper and Hours Faster for an EdTech Platform
How SquareShift rebuilt a fast-growing EdTech platform's analytics stack on Google Cloud, cutting data delay from hours to under five minutes and running costs by 40%.
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Client
A fast-growing EdTech platform that generates learner data faster than its systems could turn into insight.
Industry
Education
Services
Stack
Google Cloud · Kafka · Spark
How SquareShift delivered it.
The challenge
The client's old cloud system only processed data in batches, so business data was already hours old by the time anyone could query it. Machine learning had no real home on the old system, and running costs had climbed above target.
What we delivered
SquareShift rebuilt the analytics system on Google Cloud, using Kafka and Spark so data flows in and gets processed continuously. It all now feeds one governed store that serves both analytics and machine learning.
See the Google Cloud migration services behind projects like this.
The outcome
Data now reaches teams within five minutes instead of hours. Running costs fell by 40%, and machine learning is now in production instead of having no home on the old system.
A migration that only moves infrastructure leaves the real problem in place — this one worked because it replaced batch processing with a continuous pipeline, not just a new address for the same jobs.
Data & Analytics Practice Lead, SquareShift
Related reading: migrating a 70TB analytics workload to BigQuery and how to migrate a database to GCP.
