Google BigQuery consultants

We can help you automate your business with Google BigQuery and hundreds of other systems to improve efficiency and productivity. Get in touch if you’d like to discuss implementing Google BigQuery.

Integration And Tools Consultants

Google Bigquery

About Google BigQuery

Google BigQuery is a serverless, highly scalable data warehouse built on Google Cloud. It enables SQL-based analysis of massive datasets — from gigabytes to petabytes — without managing infrastructure. BigQuery handles the compute resources automatically, so queries across billions of rows return results in seconds rather than hours.

Data analysts, business intelligence teams, marketing analysts, and finance departments use BigQuery to centralise data from multiple sources and run complex analytical queries. Common use cases include combining Google Analytics data with CRM records, building revenue dashboards, analysing customer behaviour across touchpoints, running cohort analyses, and generating reports that would be too slow or impossible in a spreadsheet.

At Osher, we connect BigQuery to your operational workflows so analytical insights translate into action. We build pipelines that load data from your CRM, advertising platforms, payment systems, and operational tools into BigQuery for unified analysis. Then we connect BigQuery outputs back to your business systems — query results can feed automated reports, trigger alerts when KPIs shift, update dashboards in real time, or push insights into your CRM for sales team action. Our AI consulting team also builds machine learning models that run directly on BigQuery data using BigQuery ML, enabling predictive analytics like churn scoring and demand forecasting without moving data out of your warehouse.

Google BigQuery FAQs

Frequently Asked Questions

What types of data can we store and analyse in BigQuery?

How much does BigQuery cost for a typical business?

Can BigQuery replace our existing reporting spreadsheets?

How do we get data from our CRM and other tools into BigQuery?

Can BigQuery query results trigger automated business actions?

Do we need a data engineer to manage BigQuery?

How it works

We work hand-in-hand with you to implement Google BigQuery

Step 1

Identify Your Data Sources and Questions

We work with your team to determine which business systems should feed into BigQuery and what analytical questions you need answered — revenue trends, customer segmentation, marketing attribution, or operational metrics.

Step 2

Design Your Data Warehouse Schema

We create a BigQuery dataset structure with tables optimised for your most common queries. This includes deciding on partitioning, clustering, and data types that keep query costs low and performance high.

Step 3

Build Automated Data Pipelines

We set up extraction workflows that pull data from your CRM, advertising platforms, Google Analytics, payment systems, and other sources into BigQuery on a regular schedule — hourly, daily, or in real time.

Step 4

Create Core Analytical Queries and Views

We write the SQL queries and materialised views that answer your key business questions — revenue dashboards, customer lifetime value calculations, marketing attribution models, or operational KPI tracking.

Step 5

Connect Outputs to Business Systems

We wire BigQuery query results to your reporting tools (Looker, Data Studio, Google Sheets), automation workflows (alerts, notifications), and operational systems (CRM updates, email triggers).

Step 6

Optimise Costs and Train Your Team

We review query patterns to minimise BigQuery costs, set up cost controls and alerts, and train your analysts on writing efficient queries and using the dashboard tools connected to your warehouse.

Transform your business with Google BigQuery

Unlock hidden efficiencies, reduce errors, and position your business for scalable growth. Contact us to arrange a no-obligation Google BigQuery consultation.