EMEA data foundation
Established a centralised Big Data and Data Lake environment supporting enterprise information across EMEA.
Big Data, Data Lake & Single Customer View Programme
One Data Foundation.One Customer View.
Building the EMEA Data & Analytics Foundation
A UK£4.4M EMEA-wide transformation programme establishing a centralised data platform, Single Customer View, Data Quality Management and self-service analytics across Policy Administration, Employee Benefits, Underwriting, Claims and Finance.
- Role
- Business Analyst & Project Manager
- Dates
- October 2018 – August 2019
- Programme
- £4.4M · 24 people · EMEA
- 24-person team
- EMEA programme
- Big Data · Data Lake · DQM · SCV
Big Data, Data Lake & Single Customer View
Creating a Unified Data Foundation for EMEA
A strategic EMEA-wide transformation programme focused on establishing a centralised Big Data Platform and Data Lake, enabling Single Customer View, data governance, data quality, analytics and self-service reporting across the organisation.
The programme brought together data from multiple source systems, data warehouses and structured and unstructured datasets into a centralised environment designed to support enterprise reporting, analytics and data-driven decision-making.
Architecture overview
The EMEA Data Journey
Conceptual representation of the programme’s data flow, from source systems to business insight.
Multiple EMEA source systems
Customers · Policies · Claims · Employee Data
Data ingestion
Hadoop / Data Lake
Hadoop · HortonWorks
Data Quality / MDM
Informatica
Single Customer View
Analytics & Reporting
Qlik Sense
Business insights
01 · Big Data & Data Lake
Building the EMEA Data Foundation
Supported the implementation of an EMEA-wide Data Hub / Data Lake using the Hadoop ecosystem to provide centralised storage and processing for:
- Customers
- Policies
- Claims
- Employee Data
Data ingestion
Supported ingestion from multiple source systems, data warehouses, structured datasets and unstructured datasets into the central data environment.
Hadoop data ecosystem
Created a scalable foundation for data ingestion, processing, storage and downstream analytics.
- Apache Hadoop
- HortonWorks
- Hive
- Sqoop
- Oozie
Data processing
Used technologies including the following to support data processing and analytical workloads.
- Hive
- Apache Pig
- Sqoop
- Oozie
Single Customer View
Built the data foundation required to bring customer-related information together across EMEA, enabling a more connected view of customers, policies, claims and employee benefits.
02 · Single Customer View & Business Intelligence
Turning Enterprise Data Into Actionable Insight
Enabled business teams to explore and analyse centralised data through:
- Qlik Sense
- Apache Pig
- Data Mining Tools
- MS Excel
Interactive dashboards
Supported the development of analytics, dashboards and interactive visualisations designed to provide greater visibility across EMEA data.
Self-service analytics
Enabled business users to perform self-service analysis and reporting, reducing dependence on manually prepared information.
Customer intelligence
Established the data foundation supporting a Single Customer View, bringing together information across business domains.
03 · Data Quality Management
Embedding Quality Into the Data Lifecycle
A dedicated Data Quality Management (DQM) workstream was established alongside the Big Data & Data Lake initiative.
Automated data quality
Used Informatica to automate data-quality checks across five internal source systems.
Exception management
Identified invalid records and routed exceptions for review, correction and remediation.
Source-system correction
Corrected data was automatically pushed back toward the relevant source systems, helping establish a continuous quality-improvement process.
Master data management
Embedded Data Quality and Master Data Management (MDM) capabilities into the broader data transformation.
Data governance
Established data governance frameworks, controls and processes around managing information within the Data Lake.
04 · Data Governance & Business Glossary
Creating Structure Around Enterprise Data
Data governance framework
Supported the creation and implementation of a structured Data Governance Framework, including controls and processes for managing data within the central platform.
Business glossary
Created a Business Glossary to establish common understanding of business terminology and data concepts.
Data management
Supported improved management of enterprise information across:
- Customers
- Policies
- Claims
- Employee Benefits
- Finance
Target operating model
Contributed to the Target Operating Model and supported transition toward the new way of working.
05 · Process & Data Capture Improvement
Improving Data Quality From the Point of Capture
Identified opportunities to improve upstream processes and data capture across external brokers and agents.
Workflow improvement
Supported streamlined workflows and improved data-capture practices.
Error reduction
Addressed data-quality issues at earlier stages of the information lifecycle.
Broker & agent data
Supported improvements to information captured from external distribution and business partners.
This created a stronger connection between:
- Data capture
- Data quality
- Data platform
- Analytics
06 · Product Ownership & Project Leadership
Leading a Complex EMEA Transformation
Alongside Business Analysis responsibilities, acted as Product Owner for the UK Single Customer View and Data Quality Management solutions.
Product ownership
Owned and coordinated requirements and delivery for application components supporting the UK SCV & DQM solutions.
Multi-location delivery
Led and coordinated teams distributed across multiple EMEA locations.
Vendor management
Worked with offshore services vendor TCS and onshore services vendor BI4ALL to support delivery.
Programme planning
Established and managed:
- Scope
- Requirements
- Deliverables
- Timelines
- Stakeholders
- Resources
- Dependencies
- Budgets
Project governance
Created and maintained the Project Plan, tracked progress and produced status reporting for programme sponsors and stakeholders.
RAID management
Managed:
- Risks
- Assumptions
- Issues
- Dependencies
- Actions
- Decisions
- Impacts
- Escalations
Stakeholder leadership
Chaired the following, and managed meeting outputs, actions and follow-up activities:
- Project Steering Meetings
- Stakeholder Meetings
- Sponsor Meetings
Transformation impact
What the programme put in place
Single Customer View
Created the data foundation for a connected view of customers, policies, claims and employee data.
Data quality
Embedded automated quality checks and exception management across five internal source systems.
Data governance
Introduced governance frameworks, controls and processes for managing data within the Data Lake.
Self-service analytics
Enabled business users to analyse data using Qlik Sense, Apache Pig, data-mining tools and Excel.
Project leadership
Coordinated a 24-person, multi-location programme team across a UK£4.4M transformation programme.
Technology ecosystem
Platforms and tools referenced
Big Data & Data Lake
- Hadoop
- HortonWorks
- Hive
- Sqoop
- Oozie
- Apache Pig
Data Quality
- Informatica
- Master Data Management
- Data Quality Management
Business Intelligence
- Qlik Sense
- Data Mining
- Excel
Database
- SQL Server
Business domains
- Policy Administration
- Employee Benefits
- Underwriting
- Claims
- Finance
Core capabilities
Data transformation
- Big Data
- Data Lakes
- Data Integration
- Data Ingestion
- Data Modelling
- Data Quality
Data governance
- Data Governance
- MDM
- Business Glossary
- Data Controls
- Data Management
Business intelligence
- Qlik Sense
- Analytics
- Dashboards
- Interactive Visualisation
- Self-Service Reporting
Project management
- Programme Planning
- Workstream Management
- RAID Management
- Stakeholder Management
- Vendor Management
Business analysis
- Requirements Engineering
- Process Analysis
- Workshop Facilitation
- Stakeholder Engagement
- Business Change
Product ownership
- Product Ownership
- Backlog / Requirements Management
- Delivery Coordination
- Solution Alignment
From Fragmented Data to Connected Intelligence
Connecting source systems, strengthening data quality, establishing governance and enabling analytics to create a more unified view of customers, policies, claims and employee data across EMEA.
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