High-volume photography platform
Photography & Imaging · High-Volume B2B2C Data Platform
Standardizing the data foundation behind a high-volume photography platform
The client operates a high-volume B2B2C photography platform processing millions of transactions across multiple production systems. Datics worked alongside its data and engineering team to improve how production data moved into Databricks and downstream analytics.
High-Volume B2B2C Data Platform
High-Volume B2B2C Data Platform
- Production data pipelines
- Databricks data foundation
- Analytics consumption
Live production data environment supporting a high-volume B2B2C platform.
The starting point
The client already operated a high-volume B2B2C photography platform processing millions of transactions across multiple production databases and applications. It also had its own engineering organization and Director of Data Strategy.
What had to change
Production data was spread across multiple applications and databases, making it harder to maintain a consistent downstream model for analytics and reporting.
What couldn't break
The operational systems generating that data were live and processing millions of transactions. Data-platform work had to fit around them rather than disrupt them.
Why this was hard
Multiple production systems, different data structures and downstream consumers all had to converge on a dependable model without changing the applications producing the data.
What Datics changed
Datics worked on the data and pipeline layer connecting the client's production systems with its Databricks analytics environment. The focus was on making data movement, transformation and downstream consumption more standardized and maintainable within the platform's existing operating environment.
Datics worked alongside the client's Director of Data Strategy and existing engineering team, focusing on data pipelines, modeling and production reliability within the environment already in use.
Production data pipelines
Standardize how production data moves from operational systems toward the analytics environment.
Databricks data foundation
Structure transformation and modeling around the existing lakehouse environment.
Analytics consumption
Prepare dependable downstream data for analytics and reporting tools.
Engagement at a glance
The client's engagement demonstrates the scale and complexity of improving the data layer beneath a live product: millions of transactions, multiple production systems, and an AWS and Databricks analytics environment.
- Platform scale
- Millions of transactions
- Production environment
- Multiple databases and applications
- Data and analytics stack
- AWS + Databricks
Under the hood
- Datics role
- Data engineering and architecture alongside the client's internal data and engineering team.
- Integrations
- Production databases and applications feeding Databricks and downstream analytics, including Metabase and Google Analytics.
- Deployment
- AWS and Databricks within the client's existing production data environment.
- Production boundary
- Live production data environment supporting a high-volume B2B2C platform.
Technology
What this unlocked
A stronger data foundation gives the client a more reliable base for downstream analytics and future AI capabilities without requiring changes to the operational applications generating the data.
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