AI & DATA / DATA PLATFORM
Data platforms and analytics
Scattered data.
A usable asset.
Design collection, integration and visualization with Snowflake or Google Cloud, moving from individual reporting tasks to shared data capabilities.
- FOR
- Companies using data across departments
- PHASE
- Data utilization
- ESTIMATE
- Proposed individually after confirming scope
PARTNERSHIP
Snowflake partner
TECHNOLOGY
BigQuery
Cloud Run
Cloud SQL
Google Cloud
BigQueryCloud RunCloud SQLFROM WORKFLOW TO DELIVERABLES
How we work ↗- 01Review the current data landscape
- 02Design the foundation and metrics
- 03Implement integration and visualization
- 04Confirm refresh and operating procedures
01 SCOPE & DELIVERABLES
What this engagement delivers.
Use the following as a starting point to agree on deliverables for your workflow and requirements.
Ingestion and transformation processes
Access, refresh and quality-management design
Analytics interfaces and usage guidance
If available,
bring these to the conversation.
- Data source inventory
- Required metrics and reporting needs
- Existing cloud environment and permissions
Incomplete documentation is fine. Start by describing your current situation.
02 PROJECT FLOW
A visible path to delivery.
- 01
Review the current data landscape
- 02
Design the foundation and metrics
- 03
Implement integration and visualization
- 04
Confirm refresh and operating procedures
Decision point
Validate stable updates and consistent figures before extending to more data or AI use cases.
DESIGN / VALIDATE / OPERATE
Build a foundation for consistent metrics.
Align systems of record, keys, cutoffs and refresh frequency for sales, inventory and customer data. Validate ingestion and reconciliation for one analytical use before expanding.
What this stage establishes
Design reprocessing for failed loads and source corrections. Make workload usage and permissions reviewable, and include recurring cloud costs in operational planning.
Evaluate representative and exceptional cases separately from the data used during development.
Make it possible to trace answers and metrics to source records and their update state.
Define handling for incorrect answers, unauthorized retrieval and failed operations, with a manual fallback.
03 ENGAGEMENT
Define the scope before starting.
Cost, timing and terms are proposed after confirming scope and the team required.
A CLEAR FIRST STEP
The scope you need.
An informed decision to start.
Tell us about your objectives and current situation.
We will propose a clear scope, deliverables and approach.
- 01
Contact
Start with your current situation and challenges, even before requirements are defined.
- 02
Review scope, deliverables and estimates
Review work, cost, timing and exclusions. Additional work is discussed before it begins.
- 03
Start with the agreed phase
Confirm the terms before starting. Subsequent phases depend on results and business needs.
04 QUESTIONS
Start with your questions.
Q.Can we commission only a PoC?＋
Yes. We agree on the validation scope, evaluation method and deliverables. The production decision can follow the results.
Q.Can we start if our data is not organized?＋
We first review data locations and formats. If preparation is needed, we propose that scope separately from AI development.
Q.Do we need both Snowflake and Google Cloud?＋
No. We assess the existing environment, volumes, access needs and operating structure to choose an appropriate architecture.