Big Data Processing
Spark, SQL, and Delta Lake processing for datasets that are too large for a single database.
Once the lake holds more than a team can query from a laptop, you need a processing platform with a known cluster size, a job schedule, and a table format. We set that up on Databricks, Synapse, or Fabric Lakehouse, depending on where your engineers already work.
The deliverable is not a notebook that ran once. It is a job, a table layout, and a way to rerun a partition when the source data is corrected.
How We Work
- 1
Discovery & assessment
- 2
Architecture design
- 3
Build & migrate
- 4
Test & go-live
- 5
Support & optimise
Talk to us about Big Data Processing
Tell us what you run today and what the first release needs to do. We will reply within one working day.
Common questions
Spark, SQL, and Delta Lake processing for datasets that are too large for a single database. Once the lake holds more than a team can query from a laptop, you need a processing platform with a known cluster size, a job schedule, and a table format. We set that up on Databricks, Synapse, or Fabric Lakehouse, depending on where your engineers already work.
We deliver Azure Databricks, Azure Synapse Analytics, Microsoft Fabric Lakehouse. The engagement uses the options that fit your requirements and the team you already have.
We start with discovery and a written design, then build in a development environment, test against your data, and go live with a runbook. Support after go-live is agreed in the same plan.
The deliverable is not a notebook that ran once. It is a job, a table layout, and a way to rerun a partition when the source data is corrected.
Access to the Azure subscription, a named owner on your side, and a sample of the data or the jobs you want moved. We can work from a fixed scope or as a dedicated team.
