📊 How We Help Companies Turn Raw Data Into Insights Using BigQuery
Complete guide to data analytics and insights using Google BigQuery
Table of Contents
📊 How We Help Companies Turn Raw Data Into Insights Using BigQuery
Data is everywhere -- but insight is rare.
Most companies sit on piles of:
- CRM exports
- Website logs
- Marketing data from Meta, Google Ads, LinkedIn
- App analytics from Firebase, Mixpanel
- Finance and billing records
And yet... decision-makers still ask:
> "Can you give me a dashboard that just shows what's working?"
At Dezoko, we help teams go from scattered spreadsheets to centralized dashboards, powered by Google BigQuery.
Here's how we do it -- and how BigQuery helps us turn raw data into clarity, fast.
🚀 What Is BigQuery?
BigQuery is Google Cloud's fully managed, serverless data warehouse.
- ✅No servers to manage
- ✅Scales to billions of rows
- ✅Real-time + batch ingestion
- ✅Blazing fast SQL queries
- ✅Cheap storage + smart pricing
- ✅Built-in support for ML + BI tools
It's perfect for:
- Analytics
- Reporting
- Marketing performance
- User behavior
- Business KPIs
🧠 Why We Recommend BigQuery
Feature | Why It Matters |
|---|---|
Serverless | No need to manage or scale infra manually |
Real-time & Batch | Works with Firebase, Pub/Sub, CSV, APIs, etc. |
Low Cost | Only pay for what you scan -- and storage is dirt cheap |
Easy SQL | Your team already knows SQL. No steep learning curve. |
Google-native | Seamless with Firebase, GA4, Sheets, Looker Studio |
🏗️ How We Help Clients Use BigQuery
🔹 1. Centralize Disconnected Data
Before:
Marketing data in Meta, GA4, and Google Ads
User behavior in Firebase
Sales data in Stripe
Manual reports in Excel
After:
- ✅Daily sync pipelines to BigQuery
- ✅Cleaned and joined into unified tables
- ✅Ready for dashboard or CSV export
🔹 2. Build Custom Marketing Dashboards
We integrate:
- Meta Ads API
- Google Ads API
- Google Analytics 4
- Firebase Analytics
- Stripe / Razorpay
- LinkedIn Ads
- And more...
👉 All into one schema in BigQuery
👉 Auto-refreshed daily
👉 Visualized in Looker Studio or Retool
🔹 3. Analyze Product Usage at Scale
We've helped product teams:
- Analyze funnel drop-off by user type
- Track feature usage across roles
- Spot churn patterns
- Build custom retention cohorts
🧠 All using raw logs stored in BigQuery from Firebase or Supabase.
🔄 Sample Stack We Use for BigQuery Projects
Layer | Tool |
|---|---|
Ingestion | Cloud Functions / Pub/Sub / Airbyte / Fivetran |
Storage | BigQuery native tables (partitioned + clustered) |
ETL | dbt / Dataform / SQL workflows |
Dashboards | Looker Studio / Retool / Superset |
Automation | Cloud Scheduler + BigQuery scripts |
ML | BigQuery ML or export to Vertex AI |
💬 What Clients Say
> "They replaced 5 different tools and gave us one dashboard with everything -- and we finally trust our data."
> -- Marketing Head, D2C SaaS
> "We can now track product usage down to the second -- it changed how we build features."
> -- VP of Product, AI Platform
🔐 Security & Compliance
We help you ensure:
- ✅Row-level access controls (per team or region)
- ✅GDPR/CCPA compliance (data classification + masking)
- ✅Fine-grained IAM (read-only, editor, audit logs)
📞 Want to Turn Your Data into Insights?
We offer:
- ✅Full BigQuery setup + schema design
- ✅Marketing + analytics data pipelines
- ✅Custom dashboards + reports
- ✅Real-time alerts + BI integrations