A Snowflake platform your whole business can rely on
For organisations building (or fixing) a Snowflake data platform who want reliable pipelines, controlled cost, and one source of truth.
Snowflake makes it easy to load data and easy to overspend. Without a clear model and governance, you get duplicated tables, runaway compute costs, and the same old argument about which number is correct.
We design Snowflake as a proper platform: a governed model, efficient ELT, sensible warehouses sized to the workload, and the metrics defined once so analytics and AI agree.
Understand first, then build
- 1
Understand
We map your sources, workloads and consumers, and define what 'one source of truth' means for your metrics.
- 2
Model & govern
We design a layered model (raw / staging / marts) with role-based access and governance, so data is trustworthy and secure.
- 3
Build ELT
We build efficient, tested pipelines (often with dbt-style transformations) and size warehouses to control cost.
- 4
Optimise & enable AI
We tune performance and spend, and where useful enable Snowflake Cortex for AI and natural-language querying on governed data.
Concrete deliverables
- Snowflake warehouse and data model design
- ELT pipelines and transformation layer
- Role-based access control and governance
- Cost and performance optimisation
- Snowflake Cortex AI enablement
- Integration with Tableau, Power BI and custom apps
Tools we typically use
- Snowflake
- Snowflake Cortex
- SQL
- Python
- Tableau
- Power BI
Not sure which tool fits? That’s our job. We recommend based on your stack and team, not our preferences.
Talk it through with usRelated work
Large government department
We piloted Databricks Genie Space with a large government department and built the semantic layer needed for reliable conversational analytics.
Fewer ad-hoc analysis requests; analysts freed for higher-value work
Read the case studyDepartment of Transport and Main Roads (Queensland)
We developed an automated monitoring tool on Snowflake and Tableau to identify South East Queensland road corridors needing intervention and prioritise investment.
Defensible, automated corridor prioritisation
Read the case study
Komatsu Australia
We transitioned Komatsu Australia from a cumbersome manual process to automated financial reporting in Power BI, integrating data from SAP and Palantir Foundry.
50+ staff hours saved every month
Read the case studyThe questions buyers ask us
- How do you control Snowflake costs?
- Cost is mostly about compute. We size virtual warehouses to the workload, set auto-suspend and resource monitors, cluster and structure large tables sensibly, and remove wasteful reprocessing in the pipelines. Most clients we take over are overspending on idle or oversized warehouses, and the fix pays for itself quickly.
- Can Snowflake feed both our dashboards and AI?
- Yes. That is the point of a single governed platform. We model the metrics once in Snowflake, connect Tableau and Power BI to the governed layer, and where useful enable Snowflake Cortex so AI and natural-language queries run on the same trusted definitions.
- Do you migrate to Snowflake from legacy systems?
- Yes. We migrate from on-premises SQL Server, legacy warehouses and spreadsheet-based processes to Snowflake, moving the data model and pipelines across and reconciling the results so you can retire the old system with confidence.
- Do you offer Snowflake consulting in Brisbane?
- Yes. Motta Consulting is a Brisbane-based Snowflake consultant working with clients across Australia. We design the warehouse and data model, build efficient ELT pipelines, control compute cost, and enable Snowflake Cortex on a single governed source of truth. Book a free consultation for a scope specific to your platform.
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For organisations building (or fixing) a Snowflake data platform who want reliable pipelines, controlled cost, and one source of truth.