ETT and Databricks
Technology we implement
ETT uses Databricks to build the data and analytics foundations that ground AI systems — pipelines, governance and real-time intelligence that turn raw enterprise data into something models can safely rely on.
Databricks is a technology ETT designs with, deploys and supports. No formal partnership is claimed, and Databricks is not an ETT customer.
About Databricks
Databricks is the data intelligence platform built on the lakehouse architecture, unifying data engineering, warehousing, analytics and machine learning on a single governed foundation.
It is one of the most widely adopted platforms for preparing enterprise data for AI — the grounding layer that determines whether models answer from reliable, well-governed information.
How Databricks fits into how we work
Ask why an AI project failed and the answer is usually data, not the model. AI grounded in messy, ungoverned or inaccessible data produces answers no one can trust. Databricks is central to how ETT avoids that, because it gives us a single governed foundation to get a client's data into shape before any model is allowed near it.
This is where ETT's emphasis on grounding becomes concrete. We use Databricks to build the pipelines, governance and analytics layer that decide whether an AI system answers from reliable information or from guesswork. Getting that foundation right is rarely glamorous, but it is the difference between an AI initiative that earns trust and one that quietly gets switched off, and it is a part of the work we refuse to skip.
Our work around Databricks
We build the pipelines, quality baselines and ownership rules that make approved data usable for a specific decision or workflow.
Fix the foundation first
We use Databricks to bring scattered enterprise data onto one governed platform, so AI is built on information the business can actually stand behind rather than on whatever was easiest to reach.
Govern as you go
Lineage, access control and quality are built into the data layer, so AI grounded in that data inherits the governance regulated organisations require rather than bolting it on later.
Turn data into live intelligence
Beyond grounding models, we use the same foundation to give clients the dashboards and real-time analytics that drive better day-to-day decisions, so the investment pays back even before AI does.
Which process would you improve first?
Tell us where your teams are losing time, where service is under pressure or where an AI initiative has stalled. We’ll help you explore the opportunity and define a practical next step.