Talk to Cloud Tales
Tell us what you are dealing with and what has already been tried. We will tell you how we would approach it.
info@cloudtales.co.ukData engineering consultancy
Cloud Tales Ltd builds, assesses and governs data platforms on Azure and Databricks. We work with organisations whose data has outgrown the platform holding it, and with the teams who depend on that platform every working day.
Most engagements start as one of these. Tell us what you are dealing with and we will tell you which one it is.
We build data platforms on Azure and Databricks: ingestion, orchestration, storage and the modelling layers above them. That covers batch and streaming sources alike, from Data Factory pipelines and Data Lake storage through to the warehouse and semantic models your reporting sits on. Everything ships through CI/CD, so releases and production deployments happen the same way every time.
Some estates have been accumulating for decades, and both the schema and the questions have drifted along the way. We catalogue what is actually there, establish what it can support, and show you where the worthwhile insight sits. You get that answer before the migration budget is committed, not after.
First platform attempts stall for reasons that are rarely purely technical. We establish why, identify what is worth keeping, and cost a realistic route forward. Access control, lineage and personal data handling are designed in from the start, including the parts that carry real obligations: where personal data sits, who can reach it, and how you evidence that.
The platform your business already trades on has to stay up. We design disaster recovery and then test it rather than filing it, build alerting that reaches the engineer who can act on it, and take on the remediation when the overnight load stops finishing before the working day starts.
AI programmes stall on data groundwork far more often than on models. We get an existing estate to the point where AI and ML are realistic: governed tables, dependable pipelines, documented lineage, and access control that lets people use the data without exposing it. Where a lakehouse is already in place, that extends to natural-language querying, tuned against your datasets so the answers can be trusted.
Small enough that you always know who is doing the work, structured enough that you always know what you are getting.
Engagements are deliverable-based. What finished looks like is agreed in writing before work starts, and you can measure progress against it at any point.
There is no account layer between you and the work. The people who scope your engagement are the people who deliver it, which is why the estimates hold once we are into the data.
Questions get answered in hours rather than days, with the reasoning behind the answer, so your team can act on it the same day.
Engagements run under confidentiality, and often through an agency, so these describe the work rather than the organisation. No client is named, and none will be.
A consumer retail business was running its reporting on an on-premises SQL Server estate that had accumulated years of workarounds and was straining to keep up with demand. Moving to the cloud was a chance to scale on demand and to clear out the code base at the same time. We delivered the first phase: ingestion and transformation on Data Factory and Databricks, with tables landed into Unity Catalog for the client's own governance. We also built Databricks Genie rooms and tuned them against those datasets, so stakeholders could ask questions of the data in plain language.
A reporting platform built on Data Factory and Azure SQL, delivered jointly with the client's own engineers and a second consultancy. Our scope was the Data Factory architecture, the CI/CD release process and deployments into production. The new platform ran in parallel with the one it replaced and was reconciled against it before cutover, so the figures were known to match before anything was switched off.
The platforms and tools Cloud Tales works in day to day.
Cloud Tales Ltd is a data engineering consultancy registered in England and Wales. We work on Azure and Databricks with organisations that depend on their data platform to trade, report or comply.
Work is delivered by Brandon White, alongside your engineers and stakeholders rather than through an account team. That is deliberate. The person who understands your estate is the person you can call about it, and the person who answers for it.
Tell us what you are dealing with and what has already been tried. We will tell you how we would approach it.
Email reaches us directly. There is no form and no third-party enquiry service in between.