Databricks – Datalinks

About Databricks

Databricks describes itself as a unified platform for data, analytics and AI.

The Databricks platform

Lakehouse & Delta Lake

Open storage with ACID transactions, data-quality rules and time travel for querying earlier versions of data.

Lakeflow

Data ingestion and orchestration for reliable pipelines that feed analytics and AI.

Unity Catalog

One catalog for data, AI models and agents, with permissions, lineage and auditing.

Databricks SQL

A serverless data warehouse for SQL analytics and business intelligence.

What we deliver on Databricks

Platform set-up

Workspaces, Unity Catalog, security and cost controls set up properly from day one.

Data engineering

Lakeflow pipelines that bring in CRM, finance, operations and IoT data and keep it current.

Data modelling

Clean, documented models that analysts and BI tools can trust, including graph and geospatial data.

Machine learning

Predictive models for churn, demand, risk and classification, deployed and monitored.

How a Databricks project runs

Assess

We review your data sources, current platform and use cases.
Build the foundation

We set up the workspace, governance and first pipelines using a bronze, silver and gold (medallion) design.
Deliver the use case

A dashboard, model or agent running on production data, so value shows up early.
Scale

We add sources and use cases, then hand over with documentation and training for your team.

Who it suits

Data spread across many systems

Moving off a legacy data warehouse

Asset-heavy and IoT operations

Building AI on your own data

Government and regulated sectors

Analytics teams outgrowing spreadsheets

Common questions

Do we need Databricks if we already use Power BI?

Power BI is excellent for reporting, but it isn’t built to engineer large volumes of data from many systems.

Which cloud does Databricks run on?

Databricks runs on AWS, Microsoft Azure and Google Cloud.

Databricks partner for data and AI