Data Infrastructure That Drives U.S. Board Decisions
Snowflake, BigQuery, dbt and modern BI stacks engineered to consolidate your data, automate reporting, and surface the metrics your CEO actually trusts.
U.S. companies are drowning in dashboards and starving for trusted data. Every SaaS platform has its own analytics, every team has built its own spreadsheet truth, and the numbers disagree depending on who you ask. Board meetings turn into data-reconciliation arguments instead of strategic discussions. Meanwhile your competitor's CEO can answer any question with a single dashboard, in real time.
Buraq builds U.S. modern data stacks that consolidate fragmented sources into a trusted warehouse, model the data with dbt, surface it through BI tools your team already uses, and govern it so the same metric returns the same number regardless of who asks. Output is a data function that supports growth instead of slowing it down.
What teams in United States are up against
Multiple departments reporting different numbers for the same KPI.
Manual Excel exports consuming hours of analyst time every week.
Data engineering bottleneck — every new dashboard requires an engineer.
Customer-facing analytics half-built and increasingly diverging from internal reporting.
Cost of cloud data warehouse climbing because nobody owns query optimization.
Where we deliver across United States
Built for United States regulatory requirements
HIPAA-aligned analytics architectures for healthcare data — de-identification, segregation, audit logs.
SOC 2-aligned access controls, audit logging and change management for the warehouse.
GDPR/CCPA data subject request workflows extended into analytics tooling.
Financial reporting controls for SOX-relevant data flows in pre-IPO and public companies.
Outcomes for United States teams
One source of truth
Warehouse consolidation, semantic layer, and governed metrics so the same KPI returns the same number across every team and tool.
Self-service that doesn't break trust
dbt models, governed semantic layer (Cube, dbt Semantic Layer, Looker LookML) so business users explore data without inventing new definitions of every metric.
Warehouse cost under control
Query optimization, materialization strategy, clustering and tiered storage so your Snowflake or BigQuery bill stops growing faster than your data.
Real-time when it matters
Streaming pipelines for customer-facing analytics and operational dashboards that need sub-minute freshness, batch for everything else.
Built for the U.S. modern data stack reality
The U.S. modern data stack has consolidated around a recognizable pattern: Snowflake or BigQuery as the warehouse, Fivetran or Airbyte for ingestion, dbt for transformation, a semantic layer for governed metrics, and Looker, Hex, Sigma, Mode or Tableau for delivery. We work fluently across this stack and pick the right components for your scale and team.
Where pre-built connectors don't exist, we build custom ingestion. Where dbt models need optimization, we refactor for cost and performance. Where dashboards proliferate without governance, we consolidate around a semantic layer. Output is a data platform that supports analyst self-service without descending into chaos.
Aligned to U.S. board and finance reporting cycles
U.S. companies report to boards quarterly, to investors monthly, and to executives weekly. Each cycle has its own data needs, audience, and tolerance for ambiguity. We design data infrastructure that supports all three without manual reconciliation.
For pre-IPO and public companies, we layer in financial reporting controls — change management on key metric definitions, audit trails on data transformations, and segregation of duties on production data flows — so the analytics function survives external audit scrutiny.
Technologies we deploy in United States
United States questions, answered
Have a question not listed here? Contact our United States team and we'll get back to you.
Should we use Snowflake, BigQuery, or Databricks?
How long does a typical warehouse consolidation take?
Can you handle real-time analytics?
Do we need a full-time data engineer?
Other services for United States
Data Analytics & Business Intelligence in other markets
Stop arguing about which dashboard has the right number
Book a 45-minute data strategy call. We'll review your current stack and reporting workflows and return a written modernization plan within one week.