What is Balloon DataHub?

Balloon DataHub is the data intelligence vertical of Balloon Group. We develop Business Intelligence, Machine Learning, and Data Engineering solutions that transform enterprise data into actionable insights and measurable competitive advantages.

What types of Machine Learning models do you develop?

We develop demand forecasting models, churn prediction, customer segmentation, dynamic pricing, fraud detection, lead scoring, and sales forecasting, among others.

What BI tools do you work with?

We work with Tableau, Power BI, Looker, and custom tools. We build data warehouses on BigQuery, Snowflake, and Redshift, with pipelines in dbt and Apache Airflow.

What is your Data Scraping service?

Our Data Scraping service extracts real-time data on prices, competition, brand mentions, ratings, and product availability from any marketplace, retailer, or web source, delivered structured and ready for analysis.

How long does it take to implement a BI system?

A BI MVP with executive dashboards can be ready in 4-6 weeks. A complete data ecosystem with ML models takes 3-6 months depending on complexity and data availability.

DATAHUB

03 — DATAHUB

Data reveals what intuition cannot see

Advanced Business Intelligence, applied Machine Learning, and Data Engineering for organizations that make decisions with surgical precision. We turn data into real, actionable competitive advantages.

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94%

accuracy in predictive models

40%

average CAC reduction

Why
DATAHUB

90% of business data is never analyzed. At Balloon DataHub we transform that ocean of unexploited data into predictive models, strategic dashboards, and intelligence systems that operate in real time, giving your leadership team an information advantage that competitors don't have.

Capabilities

What we do

Business Intelligence

Strategic dashboards and executive reporting with real-time data.

Machine Learning

Predictive models for churn, demand, pricing, and advanced segmentation.

Data Scraping & Enrichment

Extraction and enrichment of market, competitive, and consumer data.

Data Engineering

Modern data architecture: scalable pipelines, data lakes, and warehouses.

Advanced Analytics

Cohort analysis, multi-channel attribution, and marketing mix models.