DATABRICKS SERVICES
Find the gaps in your e-commerce data.
Get a clear map of your customer, product, order, clickstream and inventory data, identify the biggest gaps and define what your e-commerce data platform should look like on Databricks.
Dateonic audits your current data landscape and turns it into a prioritized roadmap for analytics, AI and better e-commerce decisions.
We understand the data behind e-commerce
E-commerce data
We focus on the domains that actually run commerce — customers, products, orders, behavior, inventory and marketing.
Use cases drive the architecture
We don't recommend building a massive platform first. We identify the decisions and use cases that matter, then work backwards to the data required.
Databricks-ready roadmap
Your audit ends with a practical target architecture and roadmap for building the foundation on Databricks.
AI for E-commerce
Know what data you have. What you are missing. And what to build next.
Most e-commerce businesses already have plenty of data.
The problem is that customer behavior may sit in one system, products in another, orders somewhere else and inventory somewhere completely different. That makes it difficult to create a reliable Customer 360, forecast demand, personalize experiences or build AI.
We map those dependencies and show you what your data foundation needs to look like.
What we deliver
What We Audit
Customer & behavioral data
Map customer identity, transactions, interactions, clickstream, loyalty and behavioral signals across your systems.
Product & catalog data
Assess product attributes, catalog structure, pricing, availability and the relationships required for analytics and personalization.
Orders, transactions & inventory
Map the data behind orders, sales, fulfillment and inventory to identify gaps affecting operational and commercial decisions.
Data readiness for intelligence
Assess whether your current data can support Customer 360, forecasting, recommendations, personalization and AI — and identify what needs to change.
How we work
From fragmented data to an e-commerce data roadmap
01 · DISCOVER
Understand your data landscape
Identify source systems, domains, data owners, dependencies, latency requirements and critical business workloads
02 · DESIGN
Map the relationships
Understand how customer, product, order, clickstream and inventory data connect — and where they don’t.
03 · BUILD
Find the gaps
Identify missing data, quality issues, ownership problems, latency constraints and architectural bottlenecks.
04 · ENABLE
Know what to build first
Connect data gaps to business opportunities such as Customer 360, personalization, forecasting and inventory intelligence.
Selected Work
Case Studies
CASE STUDY
Near real-time inventory visibility and a unified data foundation for analytics and AI.
Dateonic unified POS, e-commerce, ERP and warehouse data on Databricks, enabling real-time inventory insights, consistent reporting and a scalable foundation for forecasting and AI.
CASE STUDY
Customer Intelligence for Premium Retail
A unified customer view with actionable insights for more personalized engagement.
Technical Leadership
Every signal behind your e-commerce business, gathered in one place.
E-commerce businesses generate enormous amounts of data across customers, products, orders, clickstream and inventory. The challenge isn’t collecting more data — it’s connecting it.
At Dateonic, we help e-commerce companies bring these signals together on Databricks and turn them into a trusted foundation for analytics, AI and better decisions.
FAQ
E-commerce Data Audit questions, answered
QUESTION 01
What exactly do you audit?
We look at the data behind the core e-commerce domains: customer, product, orders, transactions, clickstream, inventory and other relevant sources. We assess how the data is structured, connected, governed and made available for analytics and AI.
QUESTION 02
Do you need access to all of our systems?
No. We scope the audit around the questions we need to answer and the systems relevant to them. The goal is to build a useful picture of the data landscape without creating unnecessary disruption.
QUESTION 03
Can you do this if we don't use Databricks yet?
Yes. The audit focuses first on your business, data and use cases. We can then translate the findings into a target architecture and roadmap for Databricks where it is the appropriate platform.
QUESTION 04
What if our data quality is poor?
That’s exactly the type of issue the audit is designed to uncover.
We identify where data quality, missing attributes, inconsistent identifiers or unreliable pipelines could prevent a use case from working — and include those issues in the roadmap rather than hiding them behind a new platform.