1. Delivering trusted data for analyst
autonomy and operational agility
with a unified big data fabric
Vishal Bamba, VP Strategy & Architecture, Transamerica
Murthy Mathiprakasam, Product Marketing, Informatica
1

2. Informatica Overview
Cloud Data IntegrationEnterprise Data Integration Data Quality Master Data Management
Over 20
years in
data mgmt
500+
partners
including
5 Hadoop
vendors
5000+
customers
globally

3. Transamerica’s Business
• Investments & Retirement
• Retirement and Benefit Plan services to employers/employees
• Mutual funds and variable annuities
• Mission to help people save and invest wisely to secure their retirement
dreams, the I&R business unit serves more than 3 million retirement plan
participants across the entire spectrum of defined benefit and defined
contribution plans.
• Life & Protection
• Term and Perm insurance products
• Medicare supplement, long term care, accidental death, final expense
• Mission to protect what you’ve built, secure what’s next.

4. Data Architecture - Complexity
Hard to ingest?
Slow to ingest?
Security?
Governance?
Access?

5. Data Architecture - Objectives
 Discover and mine data
relationships in a trusted fashion
 Leverage a 360 degree view of data
and its relationships to develop a
360 degree view of consumers
 Create highly targeted and
personalized multi-channel
marketing programs
 Set up a 30 Node Hadoop Cluster ingesting
approx 30TB of structured & semi-
structured data
 800 Million Rows of data from 1200+ input
files
 Ingest new types of data about consumers
 Ingest data into a collated data lake and
make it available quickly
 Mask sensitive information (eg like SSN)
and trace lineage through the pipeline
 Offer both “unmanaged” and “managed”
datasets for different purposes

6. Seven Habits of Highly Successful Big Data Projects
6
1
Establish 360 view of
data & relationships for
360 view of customers,
products, services,
and risk
4
Use a data lake for
different levels of
management and fit-
for-purpose confidence
2
Centralize data
management &
automate with high
performance
integration
3
Design to use cases
and execute using a
small, flexible teams
with rapid, iterative,
agile development
5
Establish tools,
taxonomies, & processes
for collaborative
validation, stewardship,
traceability, and masking
6
Identify and socialize
data issues earlier with
data scorecarding and
data quality
7
Partner with leading
vendors to accelerate
development and
ensure flexible
deployment

7. Habit #1: Design to Use Cases & Be Agile
 Tie development to established business use cases
 Build a small, flexible team to iterate on quick wins
 Staff with naturally innovative individuals
 Look for people who can wear multiple hats
 Use technology to drive agile processes
 Partner with the business
 Socialize the platform & the vision
 Data management requires evangelism
7
1
Design to use cases
and execute using a
small, flexible teams
with rapid, iterative,
agile development

8. Habit #2: Create a Big Data Integration Machine
 Leverage a centralized team to manage and deliver trusted
data assets
 Cross functional team - BizDevOps
 Core set of Informatica developers in IT to create mappings
 Data jobs are operationalized and monitored
 Leverage technology for heavy lifting of big data integration
 Use prebuilt connectors for RDBMS, OLAP, Salesforce, Social
Media, etc
 Use Natural Language Processing (NLP) to mine semi-
structured & unstructured data (emails, twitter feeds, facebook
posts, etc)
8
2
Centralize data
management &
automate with high
performance
integration

9. Habit #3: Manage Fit-for-purpose Data Assets
9
3
Use a data lake for
different levels of
management and fit-
for-purpose confidence
 IT-assisted onboarding process
 setting up directories
 reviewing data flows
 reviewing privileges
 Access is tracked and is included
in auditing reports/events
Autonomously managed Centrally managed
 Provision access upon request to
data with secure and governed
process
 Access is tracked and included in
auditing reports/events
Data fit for exploration Data fit for reporting
vs
vs
 Business analysts are empowered
to get timely access for holistic
exploration
 Data need not be at highest level of
quality for data scientist use
 Business analysts are empowered
to get trusted access to best data
 Data at higher level of quality for
reporting and business intelligence

10. Habit #4: Establish Collaborative Governance
10
4
Establish tools,
taxonomies, &
processes for
collaborative
validation,
stewardship,
traceability, and
masking
Apply
Data
Governance
Apply
Measure
and
Monitor
Define
Discover
IT Business
 Define Terms, Policies, and Rules
 business glossary
 technical metadata
 data taxonomy
 access policies
 data retention rules
 Apply and Execute Processes
 stewardship processes
 provisioning processes
 Measure and Monitor Continuously
 lineage validation
 security views

11. Habit #5: Drive Early Detection of Data Quality
5
Identify and socialize
data issues earlier with
data scorecarding and
data quality
Ingest
and Land
Data
Profile
and
Discover
Data
Define Data
Quality
Scorecards
Define DI
Mappings
and IR
Rules
Execute
Workflows
Monitor
Data Quality
Scorecards
Manage
Record
Exceptions
Generate
Audit
Reports
Implement
Security
Views

12. Habit #6: 360 View of Data = 360 Insights
6
Establish 360 view of
data & relationships for
360 view of
customers/intermederi
as, products, services,
and risk
 Protect sensitive data holistically
 Provide access on a ‘need to know’
basis
 Alert and audit on events that occur
 Utilize exception reporting for fast
action notification
360 View of Data for Security
 Match very large volumes of
weblog visitor data, Contact Center
data to Salesforce leads and to
policy holders to generate a sales
pipeline; time-series analysis
 Apply standardization, aggregation,
de-duping process to generate a
master record of party/ household
identification
360 View of Relationships for Matching

13. Habit #7: Why Informatica and Cloudera?
13
 Strong commitment to community
driven, open source platform
 Support for security & governance
with authentication; authorization;
auditing, etc
 Strong presence in Financial
Services Industry
 Increased developer productivity with
visual development and deployment
abstraction
 Fast deployment with prebuilt
connectors
 Natural Language Processing (NLP):
 Strong big data security and
governance with data profiling & data
quality on Hadoop
7
Partner with leading
vendors to accelerate
development and
ensure flexible
deployment

15. Q&A?
15
Vishal Bamba
vishal.bamba@transamerica.com
Twitter: @vishalbamba
Murthy Mathiprakasam
mmathipra@informatica.com
Twitter: @mmathiprakasam
Follow us at @Transamerica and @INFA_BD
Like us on Facebook: facebook.com/transamerica