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BigQuery & Data Analytics

Google Cloud Data

Turn enterprise data into a governed data-to-AI foundation.

BigQuery can unify analytics, machine learning, and AI on governed enterprise data—but value depends on source design, data products, semantics, quality, security, and adoption.

Altivate builds the ingestion, modeling, governance, analytics, and operating layers around BigQuery for SAP and non-SAP estates.

The outcome: trusted data products that serve dashboards, forecasting, machine learning, and grounded Gemini experiences without duplicating every workload.

Enterprise sources
SAP Applications Databases Files & events
BigQuery data foundation
Ingestion Data products Quality & lineage Security
Business consumption
Looker BigQuery ML Gemini APIs & activation
Trusted metrics Faster analysis AI-ready data Governed access
Operational sources become governed data products before analytics, ML, and AI consume them.
Capabilities

Build the full data product, not only the warehouse

Source integration

Design batch, change-data-capture, streaming, and API ingestion from enterprise applications, databases, SAP, files, and event sources.

BigQuery architecture

Structure projects, datasets, tables, partitions, reservations, and workload controls around data domains, access patterns, performance, and cost.

Governance, quality & security

Define ownership, data contracts, classification, policy, lineage, quality checks, retention, and controlled access before self-service scales.

Looker & semantic analytics

Create governed measures and reusable business logic so teams explore consistent data instead of rebuilding competing dashboard definitions.

BigQuery ML & AI

Bring forecasting, classification, anomaly detection, and selected Gemini capabilities closer to governed data with evaluation and cost controls.

SAP data with Cortex Framework

Use Google Cloud’s open-source Cortex Framework accelerators where appropriate to land and model SAP data products—without presenting Cortex as a licensed product.

Platform

The Google Cloud data stack

  • BigQuery
  • BigQuery ML
  • BigQuery AI
  • Looker
  • Dataflow
  • Dataproc
  • Pub/Sub
  • Datastream
  • Cloud Storage
  • Dataplex Universal Catalog
  • Cortex Framework
Entry point

Start with one decision, not a lake of undefined data

Choose a high-value decision or workflow, identify the minimum trusted sources and metrics it needs, and deliver one governed data product through to adoption. Then scale the pattern.

Google Cloud practice

Explore the full Google Cloud capability set

Bring us a reporting bottleneck, fragmented data estate, forecasting need, or AI use case that lacks trusted data.

Plan a BigQuery data foundation →

Google Cloud, BigQuery, Google Kubernetes Engine, Cloud Run, AlloyDB, Spanner, Apigee, Gemini, and related marks are trademarks of Google LLC. SAP product names are trademarks of SAP SE.

Sources, proof and authorship

Sources for BigQuery and enterprise analytics

Use these sources to inspect the underlying guidance, published customer evidence and named analysis. Adjacent proof is labelled explicitly.

Interested?

Get in touch

Schedule a free consultation, our experts are ready to help you reduce cost and risk while innovating with agility.