Customer Analytics Through a Cloud Data Platform

WE ARCHITECTED A CLOUD DATA PLATFORM TO ENABLE TRUSTED, REAL-TIME ADVANCED ANALYTICS

Legacy data environment lacked agility
resulting in long time-to-market for new
analytical solutions and higher operating costs
Gaps in customer data created a disjointed
customer experience leading to missed cross
selling and conversion opportunities
Data was poorly understood, scattered across a
variety of repositories, and delivered in batches
with limited access to real-time data
Legacy platforms in data center and private
cloud could not scale and had increasing costs
Security and privacy risks for the data
platforms were managed reactively

Delivered multi-layered architecture for a Cloud Data Platform
including a data lake, streaming hub, data refineries, data
warehouse, user sandboxes, analytic workbenches, and data
governance tools
Introduced best practices for team-based architecture work
including decision management and architect core hours
Guided delivery teams using enterprise and data architecture as
“North Star”
Enabled automated ingestion and lineage for data lake using a
data registry
Architected solutions for security, access control, monitoring,
data tokenization, and individual rights
Applied agile delivery principles and orchestrated a multi-team
program; provided Scrum training and coaching
Established operational data governance framework

Enabled agile analytical solutions: Every day,
1000+ datasets are automatically ingested from
files and streams, 40 data scientists are developing
models, hundreds of data pipelines populate data
warehouse tables for user queries and dashboards
$7.5M – 30M projected revenue uplift
expected as a result of optimized global
marketing
The platform enabled improved propensity and
acquisition models resulting in a +8.5-10% lift
Enabled retirement of legacy systems resulting in
over $3M savings in operating costs and deferred
investments