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1 © Hortonworks Inc. 2011–2018. All rights reserved
10 Practical Lessons about
BigData & Analytics Journey
Real Insights from Customers
2 © Hortonworks Inc. 2011–2018. All rights reserved
1. There are clear
leaders in each market
Every Market has a select few companies
which are ahead of the pack and already
showing substantial benefits from using
BigData and Machine Learning.
The Gap is widening with the rest of their
peers and the cost of catching up Increases.
3 © Hortonworks Inc. 2011–2018. All rights reserved
Amazing Results
already
• Marcus:
• New Digital Offering
• Risk Modeling at the core
• USD$4 Billion in loans in 2 years
• Contract Intelligence (COiN) platform
• Manual review of 12,000 annual commercial credit
agreements normally requires approximately 360,000
hours
• Machine learning technology same amount of
agreements could be reviewed in seconds
• Risk Management
• Shameek Kundu, Standard Chartered’s chief data
officer says most of its AI risk projects “are about
improving our risk appetite, reducing the risk but also
increasing our ability to take risk in some situations”
4 © Hortonworks Inc. 2011–2018. All rights reserved
2. Real Transformation
requires Buy-in from the Top
• Needs full corporate focus to acquire data
and transform enterprise
• Reflected in New organization structures:
• New Innovation Centers
• New Positions - U.S. Bank’s Artificial
Intelligence Innovation Leader
• New Parallel Organizations
• Separate faciliies
5 © Hortonworks Inc. 2011–2018. All rights reserved
3. Follow the Money
• Don’t start a project without clear revenue impact objectives
• Pick Projects based on Return
• Measure Pre-Post
• A/B Sampling
6 © Hortonworks Inc. 2011–2018. All rights reserved
4. Old vs New
7 © Hortonworks Inc. 2011–2018. All rights reserved
Cost Reduction vs New Revenue
⬢ Easiest ROI to measure
⬢ Fastest economic impact
⬢ Long Implementation
cycles
⬢ Short Lived impact
⬢ Does not transform a
business
⬢ Selling a dream
⬢ Harder to Structure
⬢ Harder to Justify
⬢ Needs a business purpose
⬢ New measures to be created
⬢ Lasting Impact
⬢ Transforms a business
Cost Reduction New Revenue
8 © Hortonworks Inc. 2011–2018. All rights reserved
5. KISS - Short Cycles
(Fail-Fast)
• "Keep it simple”
• Teams improve with full
cycles
• Complexity is the enemy of
reliable models
9 © Hortonworks Inc. 2011–2018. All rights reserved
6. Intersection of Disciplines = Mixed Teams
Domain
Knowledge
Technology
Infrastructure
Mathematical
Models
How each market behaves
Buying/Selling Dynamics
What strategies work
Moving Average
Models which signal Divergence
Complex Multi-Variant models
Vast Data Storage
Analytics Platform
Back-Testing Platform
Interfaces to interact with the market
10 © Hortonworks Inc. 2011–2018. All rights reserved
7. Data is Your Most precious Resource
⬢ Assign Data Owners:
– Senior
– Liable
⬢ At the Source:
– Clean Data
– Label Data
– Cross Reference Data
⬢ Keep Everything in its
raw format
⬢ Label-Label-Label
⬢ Create Domains for
each Use
⬢ Data Governance
across all Data
⬢ Business driven
Access Policies
Organizational Data Policies
11 © Hortonworks Inc. 2011–2018. All rights reserved
8. The Cloud is Here
FSI Clients Cloud Adoption (Informal Survey)
12 © Hortonworks Inc. 2011–2018. All rights reserved
Hidden Costs
Cloud Lock-in
Different Paradigm, Complex Choices
Mistakes can be Public
Governance, Risk & Compliance
Caution!
13 © Hortonworks Inc. 2011–2018. All rights reserved
Develop an Enterprise Cloud Data Strategy for Your Business
Provide a single pane of glass for your enterprise data assets
Apply Universal data governance and security policies no matter where it resides
Avoid vendor lock-in - Remain Cloud Vendor Independent
Manage cost, reduce risk and optimize resources
14 © Hortonworks Inc. 2011–2018. All rights reserved
9. Making Models Great Again!
• Models improve with two things:
• More Data
• Frequent Running
• Machine learning algorithms have been
around since 1950 or earlier
• The breakthrough is the ability to perform
complex mathematical computations in a
short amount of time over huge sets of
Data (Big Data), over and over, faster and
faster
• Correlation does not mean Causation
Mathematical
Models
AI Algorithms
Parallel
Computing
BigData
Cheap
Storage &
CPU
Run Complex Models
In useful time
Data is the
Food for Models
BigData is possible
Due to Cheap Storage
And Hadoop
Fast Parallel Computing
Possible due to Fast Cheap
Computation Hardware
Store Large Amounts
Diverse Data
Scalable
Cost Efficient
Fast
Run Models in Parallel
Use Fast GPU’s
Use fast RAM
Off-the shelve Basic
Models
Adapt and train
models to my data
Run Models in Parallel
Simple Parallel
Processing Platform
& Implementation
Machine
Learning
Renaissance
15 © Hortonworks Inc. 2011–2018. All rights reserved
16 © Hortonworks Inc. 2011–2018. All rights reserved
17 © Hortonworks Inc. 2011–2018. All rights reserved
18 © Hortonworks Inc. 2011–2018. All rights reserved
19 © Hortonworks Inc. 2011–2018. All rights reserved
10. How does a leader look like?
• Full organization cultural transformation
• Data driven products, Data driven business
• Data Driven Organization
• Internal Data augmented with External
Data
• Data Library
• Data Domains
• Predictive
• Real-time
The Analytics Journey
DESCRIPTIVE
Analytics
What Happened?
PREDICTIVE
Analytics
What Could Happen?
PRESCRIPTIVE
Analytics
How Can We Achieve
The Best Outcome
COGNITIVE
Analytics
Tell Me The
Best Course of Action
INSIGHTS
HOW TO BE RIGHT
MOST OF THE TIME
DIAGNOSTIC
Analytics
Why did it Happen?
account distributions
average balances
household characteristics
branch statistics
small business information
cross-sell ratios
CompetitiveAdvantage
Alerts, querying,
searches, reporting,
static
visualizations,
dashboards,
tables, charts,
narratives,
correlations, simple
statistical analysis
Regression analysis,
A|B testing,
pattern matching,
data mining,
forecasting,
segmentation
Machine learning,
SNA,
geospatial pattern
recognition,
interactive
visualizations
Graph analysis,
Neural-networks,
Machine & Deep
learning,
AI
DESCRIPTIVE DIAGNOSTIC PREDICTIVE PRESCRIPTIVE COGNITIVE
FORWARD LookingBACKWARD Looking
Complexity
20 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
Title Goes Here
Thank you

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10 Lessons Learned from Meeting with 150 Banks Across the Globe

  • 1. 1 © Hortonworks Inc. 2011–2018. All rights reserved 10 Practical Lessons about BigData & Analytics Journey Real Insights from Customers
  • 2. 2 © Hortonworks Inc. 2011–2018. All rights reserved 1. There are clear leaders in each market Every Market has a select few companies which are ahead of the pack and already showing substantial benefits from using BigData and Machine Learning. The Gap is widening with the rest of their peers and the cost of catching up Increases.
  • 3. 3 © Hortonworks Inc. 2011–2018. All rights reserved Amazing Results already • Marcus: • New Digital Offering • Risk Modeling at the core • USD$4 Billion in loans in 2 years • Contract Intelligence (COiN) platform • Manual review of 12,000 annual commercial credit agreements normally requires approximately 360,000 hours • Machine learning technology same amount of agreements could be reviewed in seconds • Risk Management • Shameek Kundu, Standard Chartered’s chief data officer says most of its AI risk projects “are about improving our risk appetite, reducing the risk but also increasing our ability to take risk in some situations”
  • 4. 4 © Hortonworks Inc. 2011–2018. All rights reserved 2. Real Transformation requires Buy-in from the Top • Needs full corporate focus to acquire data and transform enterprise • Reflected in New organization structures: • New Innovation Centers • New Positions - U.S. Bank’s Artificial Intelligence Innovation Leader • New Parallel Organizations • Separate faciliies
  • 5. 5 © Hortonworks Inc. 2011–2018. All rights reserved 3. Follow the Money • Don’t start a project without clear revenue impact objectives • Pick Projects based on Return • Measure Pre-Post • A/B Sampling
  • 6. 6 © Hortonworks Inc. 2011–2018. All rights reserved 4. Old vs New
  • 7. 7 © Hortonworks Inc. 2011–2018. All rights reserved Cost Reduction vs New Revenue ⬢ Easiest ROI to measure ⬢ Fastest economic impact ⬢ Long Implementation cycles ⬢ Short Lived impact ⬢ Does not transform a business ⬢ Selling a dream ⬢ Harder to Structure ⬢ Harder to Justify ⬢ Needs a business purpose ⬢ New measures to be created ⬢ Lasting Impact ⬢ Transforms a business Cost Reduction New Revenue
  • 8. 8 © Hortonworks Inc. 2011–2018. All rights reserved 5. KISS - Short Cycles (Fail-Fast) • "Keep it simple” • Teams improve with full cycles • Complexity is the enemy of reliable models
  • 9. 9 © Hortonworks Inc. 2011–2018. All rights reserved 6. Intersection of Disciplines = Mixed Teams Domain Knowledge Technology Infrastructure Mathematical Models How each market behaves Buying/Selling Dynamics What strategies work Moving Average Models which signal Divergence Complex Multi-Variant models Vast Data Storage Analytics Platform Back-Testing Platform Interfaces to interact with the market
  • 10. 10 © Hortonworks Inc. 2011–2018. All rights reserved 7. Data is Your Most precious Resource ⬢ Assign Data Owners: – Senior – Liable ⬢ At the Source: – Clean Data – Label Data – Cross Reference Data ⬢ Keep Everything in its raw format ⬢ Label-Label-Label ⬢ Create Domains for each Use ⬢ Data Governance across all Data ⬢ Business driven Access Policies Organizational Data Policies
  • 11. 11 © Hortonworks Inc. 2011–2018. All rights reserved 8. The Cloud is Here FSI Clients Cloud Adoption (Informal Survey)
  • 12. 12 © Hortonworks Inc. 2011–2018. All rights reserved Hidden Costs Cloud Lock-in Different Paradigm, Complex Choices Mistakes can be Public Governance, Risk & Compliance Caution!
  • 13. 13 © Hortonworks Inc. 2011–2018. All rights reserved Develop an Enterprise Cloud Data Strategy for Your Business Provide a single pane of glass for your enterprise data assets Apply Universal data governance and security policies no matter where it resides Avoid vendor lock-in - Remain Cloud Vendor Independent Manage cost, reduce risk and optimize resources
  • 14. 14 © Hortonworks Inc. 2011–2018. All rights reserved 9. Making Models Great Again! • Models improve with two things: • More Data • Frequent Running • Machine learning algorithms have been around since 1950 or earlier • The breakthrough is the ability to perform complex mathematical computations in a short amount of time over huge sets of Data (Big Data), over and over, faster and faster • Correlation does not mean Causation Mathematical Models AI Algorithms Parallel Computing BigData Cheap Storage & CPU Run Complex Models In useful time Data is the Food for Models BigData is possible Due to Cheap Storage And Hadoop Fast Parallel Computing Possible due to Fast Cheap Computation Hardware Store Large Amounts Diverse Data Scalable Cost Efficient Fast Run Models in Parallel Use Fast GPU’s Use fast RAM Off-the shelve Basic Models Adapt and train models to my data Run Models in Parallel Simple Parallel Processing Platform & Implementation Machine Learning Renaissance
  • 15. 15 © Hortonworks Inc. 2011–2018. All rights reserved
  • 16. 16 © Hortonworks Inc. 2011–2018. All rights reserved
  • 17. 17 © Hortonworks Inc. 2011–2018. All rights reserved
  • 18. 18 © Hortonworks Inc. 2011–2018. All rights reserved
  • 19. 19 © Hortonworks Inc. 2011–2018. All rights reserved 10. How does a leader look like? • Full organization cultural transformation • Data driven products, Data driven business • Data Driven Organization • Internal Data augmented with External Data • Data Library • Data Domains • Predictive • Real-time The Analytics Journey DESCRIPTIVE Analytics What Happened? PREDICTIVE Analytics What Could Happen? PRESCRIPTIVE Analytics How Can We Achieve The Best Outcome COGNITIVE Analytics Tell Me The Best Course of Action INSIGHTS HOW TO BE RIGHT MOST OF THE TIME DIAGNOSTIC Analytics Why did it Happen? account distributions average balances household characteristics branch statistics small business information cross-sell ratios CompetitiveAdvantage Alerts, querying, searches, reporting, static visualizations, dashboards, tables, charts, narratives, correlations, simple statistical analysis Regression analysis, A|B testing, pattern matching, data mining, forecasting, segmentation Machine learning, SNA, geospatial pattern recognition, interactive visualizations Graph analysis, Neural-networks, Machine & Deep learning, AI DESCRIPTIVE DIAGNOSTIC PREDICTIVE PRESCRIPTIVE COGNITIVE FORWARD LookingBACKWARD Looking Complexity
  • 20. 20 © Hortonworks Inc. 2011 – 2016. All Rights Reserved Title Goes Here Thank you