Modern Data Stack
Snowflake, BigQuery, Databricks, dbt, Fivetran and Airbyte — production-grade.
AI & Data
Business Intelligence Services
A data platform people actually trust — reliable pipelines, governed metrics, and self-serve analytics that answer questions without a queue for the data team.
Built for your business
From Raw Data to Trusted Insights
From Snowflake and BigQuery to Looker, Power BI, and Tableau — we engineer the modern data stack and the dashboards leaders actually use.
ELT Pipelines
Reliable, observable, version-controlled pipelines built with dbt and orchestrators.
Self-Serve Analytics
Semantic layers and governed metrics so business users get answers without SQL.
Embedded Analytics
Dashboards and metrics embedded into your SaaS product or internal apps.
Data Quality & Governance
Tests, alerts, lineage, catalogs and access controls.
Predictive Analytics
Forecasts, churn, scoring and anomaly detection on a trusted data layer.
What we deliver
Business Intelligence Services We Offer
Start with the capabilities you need today. We define the scope, integrations, and acceptance criteria together before delivery begins.
BI Strategy & Roadmap
Data vision, target architecture, tooling decisions, and adoption plan.
Cloud Data Warehousing
Snowflake, BigQuery, Redshift, Databricks lakehouse implementation and tuning.
Data Pipelines & ETL/ELT
Pipelines with Fivetran, Airbyte, Stitch, and custom Python — orchestrated by Airflow/Prefect.
dbt Development
Modular dbt models, tests, docs, and CI/CD for analytics engineering at scale.
Semantic Layer & Metrics
LookML, Cube, dbt Semantic Layer — governed metrics consumed across tools.
Dashboards & Reporting
Looker, Power BI, Tableau, Metabase, Sigma — designed for executives and operators.
Embedded Analytics
Embed dashboards and customer-facing analytics into your SaaS product.
Data Quality & Observability
Monte Carlo, dbt tests, anomaly detection, freshness checks, and SLA alerting.
Data Governance & Catalogs
Atlan, DataHub, Collibra — lineage, glossaries, and access controls.
Reverse ETL
Activate warehouse data into Salesforce, HubSpot, Marketo via Hightouch or Census.
Predictive & Advanced Analytics
Forecasts, churn, LTV, and segmentation models built on your data warehouse.
Data Team Augmentation
Embedded analytics engineers, BI developers, and data architects for your team.
From brief to delivery
A clear path from the first conversation.
A practical process with agreed milestones, regular reviews, and a handover your team can use.
- 01 /
Audit & Strategy
Audit data sources, gaps, and stakeholder needs; design target architecture.
- 02 /
Build
Stand up warehouse, ELT, semantic layer, and core dashboards.
- 03 /
Activate
Roll out self-serve analytics, training, and adoption playbooks.
- 04 /
Operate & Improve
Monitor pipeline health, evolve data models, and add predictive capabilities.
Tools of the trade
The right technology for the work.
We choose tools around your existing systems, requirements, and long-term maintenance needs. The final stack follows the project.
- Snowflake
- Google BigQuery
- Databricks
- PostgreSQL
- Fivetran
- Airbyte
- Stitch
- dbt
- Apache Airflow
- Tableau
- Looker
- Power BI
- Metabase
- Cube
- Hightouch
- Monte Carlo
Before we begin
Your questions, answered.
What to know about business intelligence services, from project scope to ongoing support.
01What is business intelligence?
Business Intelligence is the practice of turning raw business data into trusted dashboards, metrics, and insights that drive better decisions across the organization.
02Which BI tools do you work with?
Looker, Power BI, Tableau, Metabase, Sigma, and Mode — chosen based on your data team, budget, and existing stack.
03Which data warehouses do you support?
Snowflake, BigQuery, Redshift, Databricks lakehouse, and Postgres-based warehouses — including migration between them.
04Do you build the pipelines too?
Yes. We design and build pipelines with Fivetran, Airbyte, Stitch, custom Python, and orchestrators like Airflow, Prefect, or Dagster.
05Can you embed analytics into our product?
Yes. We embed dashboards and build customer-facing analytics into SaaS products using Looker, Sigma, Cube, or custom builds.
06How do you handle data quality?
dbt tests, Monte Carlo or similar observability platforms, freshness alerts, anomaly detection, and clear data SLAs.
07How long does a BI implementation take?
A foundational warehouse + core dashboards typically launches in 8–14 weeks. Larger enterprise BI programs run 4–9 months in phases.
Keep exploring
The next pieces of your project.
Connected services, delivered by the same team.
A conversation is a good start
Let's talk about business intelligence services.
Tell us what you want to build or improve. We will help clarify the scope, the approach, and the next step.