Accelerate Digital London Technical Masterclass

Technical Master Class
17 July 2014
Accelerate Digital London

17.07.2014
Architecture for Tomorrow
bernhard@apigee.com

• The Challenge
• Shortcomings of the current Enterprise IT
• Introduction of the "Digital Business Platform"
• Location of the Digital Business Platform in the
Enterprise Architecture
• Digital Business Platform and Orchestration

© 2014 Apigee Confidential – All Rights Reserved
Partner
Integration
Web site
Wearable
Electronics
Gaming Consoles
Smart
Appliances
Smart
Sensors
Smart
phones
Connected
Cars
Tablets
KiosksAPI
API
Your
Digital
Assets
API
API
4
Your
Digital
Assets
The changing demands for Enterprise IT

SOA implementation projects
• choose tools with care
• built well designed services
• designed contracts through solid engineering
principles
Overall system-to-system communication across
the company got
• decoupled to ease maintenance
• properly secured
• made reliable
One of the current standards of Enterprise IT: SOA
SoR
Data
base
Back
end
SOA Middleware
SOA
Service
SOA
Service
The created infrastructure is great for complex business logic and process
integration e.g. with long running transactions and human interaction

Is your architecture fit for these challenges?
7
Partner
Integration
Web site
Wearable
Electronics
Gaming Consoles
Smart
Appliances
Smart
Sensors
Smart
phones
Connected
Cars
Tablets
KiosksAPI
API
Your
Digital
Assets
API
API
SoR
Data
base
Back
end
SOA
Service
SOA
Service
?
?
SOA Middleware

© 2013 Apigee. Confidential – All Rights Reserved© 2013 Apigee. Confidential – All Rights Reserved
Different Focus
8
DeveloperUser API API Team BackendApp
Inside-Out approach
Integration
Transactional
Predictable usage
Outside-In approach
Consumption
Interactive
Unpredictable usage
External Internal

Aspect SOA / ESB Apps and APIs
Some Technical Aspects
Enable developers, either
external or internal, to build
nifty, compelling apps, and
allow users to run them
High-latency, untrusted
(Mobile wireless network)
Web technologies, REST,
JSON, Javascript
Internet standards including
oAuth and OpenID
Of primary importance
Enable Internal developers
and systems to connect, while
complying with IT department
standards
Low-latency, trusted
SOAP, XML, proprietary
Internal mechanisms, WS-
Security, LDAP
Limited use, secondary
importance.
Core goal
Network
Technologies
Authentication and
Authorization
Usage Analytics
9

Backend
Speed up while preserving the existing invests
Digital Business Platform layer
SOA Middleware layer
System of
Record
YearsMonths
IT Applications Partner Apps Mobile Clients
"Internet of
Things"
Days
Database

• Fast, light and stateless
• Quickly configurable, but at the same time extensible
• Improve response time (caching, paging, …)
• Self service onboarding for developers
• Comprehensive and holistic view on API usage and performance
• Support both vertical and horizontal scaling
• Deployable across regions, e.g. disaster recovery, geo load balancing
• …
Selected features of a Digital Business Platform
12

A Digital Business Platform – Logical View
Mobile clients / Apps
Provide data or need access to digital assets
ESB/MQ
System of
Record
System of
Record
API Router
Calls / data needs to be routed to the ideal target
API Proxy
Some calls / data will be routed to an SOR
App Services
Custom data for the apps
App metrics
Apps require metrics
API metrics
APIs require metrics
Data mining
Machine
Learning
Predictive
Analytics
Data Lake
Insights
APIs driven by data
Developer Portal
Devs need access

• To achieve fault tolerance, horizontal scalability and high performance (high throughput, low
latency) a Digital Business Platform needs to be thoroughly designed
Design of a Digital Business Platform
API
Router
API
Proxy
Data
Platform
API
Router
API
Proxy
API
Router
API
Proxy
runtime
db
runtime
db
…
…
load balancer
Metrics
Insights
Stateless
components
to easily scale
horizontally
Replicating NoSQL to be fault
tolerant and to scale horizontally
(even across regions)
Geo location aware, round robin,
monitoring API Router/Proxy availability
Scalable,
Real time access,
central data
platform for
modeling
Dev
Mgmt

A Generic Digital Business Platform – Summary
API Router
API Proxy
App Services
App metrics
API metrics
Developer Portal
Insights
Developer
Management
API Services
API Intelligence

The simplified new Integration Architecture
SOA
Services
External
Clients
Partner
Clients
SOA Middle-ware
(ESB)
Back
end
API
Services
Back
end
Back
end
Adapter
Developer
Management
API
Intelligence
SOA
Manage-
ment
Digital
Business
Platform
Integration / Soa
Architecture
API API
Internal
Clients
Data
Plat-
form

OUTSIDE
DMZ
It can can be deployed on premise …
External
Clients
Partner
Clients
Internal
Clients
Developer
Management
API
Intelligence
API
Services
SOA
Services
SOA Middle-ware
(ESB)
Back
end
Back
end
Back
end
Adapter
SOA
Manage-
ment
API API
Data
Plat-
form
CORE

DMZ
… but for agility reasons cloud is best
SOA
Services
SOA Middle-ware
(ESB)
Back
end
Back
end
Back
end
Adapter
Developer
Management
API
Intelligence
SOA
Manage-
ment
API API
External
Clients
Internal Clients
API
Services
Partner Clients
OUTSIDE
CORE
Data
Plat-
form

A composite service combines different services to deliver a value-added new service and
can be categorized into different types:
1. User Experience centric Mashup
• Enhance UI
– by adding public cloud data (e.g. maps, stock info, weather info, ...)
– by combination of content from different sources (e.g. RSS, ATOM,…)
2. Intermediation / Customization
• Enhance services
– with public cloud data (e.g. maps, stock info, weather, ...) or partner data
– by payload/security mediation to homogenize the service use
3. Arbitration/Aggregation
• Unify services by combination in a read-only way or with data changes that are completely
independent
• Route services to provide one access point onto several different services without knowing
implementation details
4. Process Integration/Package
• Create new services by tight integration into business workflows
• Resource changes will most probably be transactional and depend on each other
Definitions
21
Unsafe with
depen-dencies
Indepen-
dently
consistent
Safe
Safe

Placement in the Integration Architecture
22
Type Exposure
Layer / API
Gateway
Implementation
Layer / Integration
Architecture
1. User Experience
centric Mashup
Yes No
2.
Intermediation/Cust
omization
Yes Not advised
3.
Aggregation/Arbitrat
ion
Yes Not advised
4. Process
Integration
No Yes
SOA
Services
SOA Middle-
ware (ESB)
Back
end
Back
end
API
API Services
Back
end
Back
end
Adapter
Developer
Management
API
Intelligence
SOA
Manage-
ment
API API
Back
end
API
DIGITAL
BUSINESS
PLATFORM

• The need for higher speed and agility demands for a new layer / system in the Enterprise IT
• The Digital Business Platform optimizes access for a large amount of different devices and an
increasing number of business partners from the outside of the Enterprise
• It has to be deployed in a fault tolerant, high available, horizontally scalable manner to be
prepared for the load of the near future
• It complements existing capabilities in the architecture:
– Services exposed by Middleware / SOA
– (Big) Data platform for data analysis / data mining / machine learning
Summary
23

17 July 2014
APIs are Interaction, not just Integration
S

Agenda
25
Interaction
Explosion of devices - User centric
Developers
Empowered developer - Usability is key
Integration
Ubiquitous - Cheap and easy - Integration Explosion

Partner
Integration
Web site
Wearable
Electronics
Gaming Consoles
Smart
Appliances
Smart
Sensors
Smart
phones
Connected
Cars
Tablets
KiosksAPI
API
Your
Digital
Assets
API
API
27
Your
Digital
Assets
App and Partner Interaction take Centre Stage

Interaction Patterns Govern APIs
Backend
Services
App
Server
Web
Partner ESB
Mobile API A
API B
API C
API Tier

Interaction Patterns Govern APIs
Backend
Services
App
Server
Web
Partner ESB
Mobile API A
API B
API C
API Tier
Chattiness
Mash Ups and
Aggregation
Data & Format
Feedback Loop
(email, push
notification)
Security

Developers are the Key Actor
31
DeveloperUser API API Team BackendApp

This applies …
32
Jakob's Law of the Internet User Experience:
Users spend most of their time on other sites. This
means that users prefer your site to work the same
way as all the other sites they already know.
Developers spend most of their time
developing against other APIs. This
means that developers prefer your API to
work the same way as all the other APIs
they already know.

34
Application developers are raison d'être for APIs.

35
Be pragmatic.
For the benefit of application developers.

Design – intuitive and simple
Consumption – ease of use and relevance
Packaging – developer and use case centric
Security – simple and consistent

API Design & Pragmatic REST
37
• https://groups.google.com/forum/#!forum/api-craft
• http://info.apigee.com/Portals/62317/docs/web%20api.pdf
• http://www.youtube.com/user/apigee

APIs are Integration Technology

APIs – Easy Integration
39
Complex and Visible
CORBA, RMI, RPC
Simple and Abstract
EAI, EJB, ESB
Simple and Visible
REST/HTTP
Integration is hard
however System
Impedance and
Remote Nature is
obvious

40
Complex and Visible
CORBA, RMI, RPC
Simple and Abstract
EAI, EJB, ESB
Simple and Visible
REST/HTTP
Integration is easier
System Impedance
and Remote Nature is
hidden

41
Complex and Visible
CORBA, RMI, RPC
Simple and Abstract
EAI, EJB, ESB
Simple and Visible
REST/HTTP
Integration is easier
System Impedance
and Remote Nature is
hidden
Abstractions
break!

42
Complex and Visible
CORBA, RMI, RPC
Simple and Abstract
EAI, EJB, ESB
Simple and Visible
REST/HTTP
Easy integration
based on simple,
standardised
principlesUsed
everywhere!

App
Backend
APIs are Everywhere
API

App
Front end
Backend
APIs are Everywhere
App
Backend
API
API

App
Front end
Backend
AppApp
APIs are Everywhere
API
API
APIAPI

Front end
Backend
AppApp
Service Service Service
Micro service architecture
APIs
APIs
APIAPI
API
API
APIs are Everywhere

APIs not an Integration Platform

• Every Developer is an Integration Developer
– Bye bye centralized integration platform
– Hello point to point integration
• Integrations are use case centric
– Bye bye canonical data model
– Bye bye one size fits all interaction model
What’s the consequence of ubiquitous APIs?

Front end
Backend
AppApp
Micro service architecture
APIs
APIs
APIAPI
API
API
The API Landscape will shift!
Requires
• Making APIs consumable
and accessible
• Adding governance

Add Visibility, Governance and Decoupling
Backend
Services
App
Server
Web apps
Social
apps
ESB
Mobile
apps
Persistence
Security
Orchestration
Analytics
All Apps API Tier

Wrap Up
51
Interaction
Explosion of devices - User centric
API Design
Empowered developer - Usability is key
Integration
Ubiquitous - Cheap and easy - Integration Explosion

Data: Powering
the Digital
Economy
Pankaj Sodhi, Accenture UK/I
Big Data Lead
@AccentureDigiUK

Every business is a Digital Business

Data is the lifeblood of the organisation
Most business leaders – CEO, CMO and CFOs now
view data as among their most valuable assets

Copyright © 2014 Accenture All rights reserved. 57
Data Supply Chain
Data should flow easily and
usefully through the entire
organisation
80% of high performing companies are
investing in analytics, yet only 40% day
they are getting the value that they want

Application
Service Interface Layer
In-Memory
IMDB, CEP,
Cache
IMDB, CEP Distributed Cache In-Memory DB
Streaming CEP
Graph
Stream
1 Pass
Stream
Big Data Core
Query Engine
In-Memory Analytics
InteractiveBulk Transfer
Sources
Streaming
Organisations can choose from different data technology components to build the architecture
needed to support data acceleration. These include big data platforms, complex event processing,
ingestion, in-memory databases, cache clusters, and appliances.

Decision
Learning
Discovery
Memory
Perception
Optimization
Prediction
Causality
Tagging
Filtering
Raw Data
Actionable Insights
Data Ingestion
Capabilities
Data Discovery &
Visual Analytics
Capabilities
Advanced Data
Analytics
Capabilities
Known Business
Questions
Business
Hypothesis
Data Raising
Interesting
Questions
Insight
Generation
Patterns in the
Data
Operational
Analytics
Opportunities
Accenture Data Discovery

Accenture’s Data Discovery Platform

Advanced Visualizations
Get deeper insights from analytics by using interactive best practice advanced visualizations that
enable drill-to-detail. For maximum effectiveness use these visualizations in combination with
blended data and advanced analytic models.
Text & Unstructured
Segmentation/Clustering
Predictions & Simulations
Behavior
Networks and Relationships
Geospatial
Treemaps and scatter plots visualize
aggregate and individuals size, proximity
and concentration of clusters
Parallel coordinates visualize patterns in
multivariate discrete and continuous
datasets with parameterized colors
Visualize location and geographic network
data on multi-layered maps give insights
into event concentrations.
Parameterize time-series predictions for
‘What-if’ analysis. Confidence bands
visualize the models strength
Find relationship clusters and patterns with
network diagrams are used chord charts for
hierarchical entity relationships
Text clouds combined with sentiment scores
are powerful for generating insights from
social and unstructured data.

@AccentureDigiUK
Join the Conversation

Who we are
Helps business quickly achieve digital acceleration, with
scale, insights and agility
More API deployments run on Apigee than any other
platform
Customers include 20% of the Fortune 100, 50% of the top
global brands, 50% of the top retailers
Customer-driven product leadership with APIs and
Big Data
Over 100k developers in the fast growing Apigee developer
community
Products
Services
Knowledge

Apigee customers span multiple industries
66Updated 5/31/14

Agenda
Predictive Analytics on Big Data, enabling a new
generation of businesses
Customer Success
Apigee Insights

Enterprises need to operate differently to stay relevant
68
Omni-channel AgilityIndividualization
Individualized interactions
Relevant experiences
Accelerate decisions
Proactive response
Adaptive processes
Continual learning
Be where customers are
Holistic view
Contextual journey
Proliferation of Mobile
and Digital
Accelerating Pace of
Change
Evolving Customer
Expectations

Predictive Analytics on Big Data key to operating differently
69
DeveloperUser API API Team Backend
Predictive Insight
Hadoop
Data Warehouse
AppAdaptive
App
Data Scientist
Adaptive
API

Existing Big Data investments lack key capabilities
70
Data Lake /
Data Warehouse
• Big Data Infrastructure
• Lack specialized data structures to analyze
fine-grain event data
• Lower precision resulting from predictive
analytics on summarized, tabular data
• Difficult to incorporate signals from
unstructured data in analysis
• Difficult to access insights in real-time
• Difficult to integrate predictive insights into
apps and APIs
Business
Intelligence
• BI Visualization &
Reporting
Data Science • Statistical Analysis
• Scientific Visualization
ChallengesCurrent Big Data Investments

71
In addition, many challenges to address
Best Practices
Global Deployment
Unstructured Data
Processors
Real Time Processing
Continual Improvement
APIs & Automation
Sophisticated Machine Learning
Model Building
Monetization
Security
System Management
Big Data Structure
Adaptive
Apps & APIs

Business
& Technical
User
Rapidly realize value API Team
Apps
Developer
Develop more precise insights
Discover complex hidden patterns
Data
Scientist
Apigee Insights: Enable adaptive apps and APIs
Hadoop
Data Warehouse
Other
Developer & Business User Tools
Predictive & Descriptive Analytics
Graph & Sequence Processing (GRASP)

Business User
Tools
Developer
Tools
RESTful
APIs
Graph Machine
Learning
Modeling
Workbench
Real Time Scoring
Data Loaders
Unstructured Data
Processor
Temporal Graph
Database
Apigee Insights: Enable adaptive apps and APIs
Business
& Technical
User
API Team
Apps
Developer
Data
Scientist
Hadoop
Data Warehouse
Other
Predictive & Descriptive Analytics
Developer & Business User Tools
Graph & Sequence Processing (GRASP)

How do you detect hidden patterns and
relationships?
75
Data Data
• How do you discover hidden patterns in
interactions across touch points & channels?
• How do you understand the customer journey
across siloed channels?
• How do you deliver a contextual journey vs.
channel optimized interactions?

• Unique big data structure (GRASP) purpose-built to analyze fine-grain time-aware
interaction data – at scale
• Identify complex hidden patterns and relationships in customer behavior
• Dramatically improve ability to predict future actions
Use specialized big data structure to analyze customer
journey
76
PROFILE
ConsumerID: U56
Gender: M
Geo: San Francisco
Interests: Bikes
PROFILE
ConsumerID: U60
Gender: F
Interests: News
Age: 35-40
2 4
1 3 40
0 3
View product
A
on web
Buy product
A on mobile
Call
customer
service
Return
Product A
in store
3
2
4
1
0
Time
GRASP
(Graph and Sequence Processing)
time-sequenced graph database on
Hadoop
Fine-grain event and entity data

How do you improve prediction accuracy?
77
• How do you avoid losing precision when working
with sampled or summarized data?
• How do you detect signals hidden in
unstructured data such as text?
• How do you prevent prediction accuracy from
degrading over time?

Apply powerful machine learning on fine-grained event
data
• Significantly improve prediction accuracy by applying powerful machine learning
algorithms directly on fine-grained event data in GRASP
• Always deliver fresh, relevant interactions with a continual learning feedback loop
78
Rules
Based
Approach
Traditional
Statistical
Analytics
Apigee
Insights
Precision
Traditional Analytics Apigee Insights
(Machine Learning on Big Data)
Static Model Dynamic Model
Focuses only on top
attributes
Leverages both strong and weak
signals
Batch only Batch and real time
Adapts to changing conditions
Easier to put into action
Significantly better results

Discover hidden signals in unstructured data
79
MBRS payment was rcvd the same day as
dunning took effect. Dunning was not posted until after
payment was processed. Final notice sent out
after payment was sent out as well. Payment was sent out
and postmarked before due date. The member was
termed correctly.
88%
45%
With
Unstructured
Data
Without
Unstructured
Data
Prediction Accuracy
(Likelihood for member to complain)
Healthcare Payer Example
2x
• Unstructured data is difficult to analyze but holds valuable signals
• Improve prediction accuracy by extracting signals hidden in text

How do you realize value from data?
80
• How do you enable developers to build new
adaptive apps and APIs?
• How do you enable business users and analysts
to interact with predictive insights?
• How do you integrate predictive insights into
existing apps and systems?
Predictive
Insights
Business
Value

Access insights in real-time
81
• In-memory real-time processor to enable fast access to insights
• Regularly updated to always provide fresh, relevant scores
Real-time access to insights using NoSQL
Propensity Free Shipping 10% Off Churn
User 1 0.72 0.68 0.33
User 2 0.56 0.23 0.55
User 3 0.32 0.45 0.67
User 4 0.20 0.32 0.18
User 5 0.44 0.69 0.22

Easily consume insights via APIs and visualization
82
Predictive insights
Descriptive insights
• Use RESTful APIs to build new adaptive apps and APIs or extend existing ones
• Enable developers and business users to act on predictive insights
Build new adaptive apps and APIs, extend existing
ones, or use or extend visualization tools provided

Deliver individualized interactions across multiple channels
83
Direct Mail
Email
Web
Mobile
Outreach
Fine grained
event data
Individualized interactions
across multiple channels
Machine Learning on
GRASP
Predictive Models
Targeting Recommendations
Churn Other Advanced
3
2
4
1
0
Propensity
Free
Shipping
10% Off Churn
User 1 0.72 0.68 0.33
User 2 0.56 0.23 0.55
User 3 0.32 0.45 0.67
User 4 0.20 0.32 0.18
User 5 0.44 0.69 0.22
0 View product
page on web
1 Receive mobile
offer
2 Call customer
service
3 Agent note:
dissatisfied
4 Return product in-
store
5 Purchase
Online
Customer
Profile

85
IBC: Proactive Customer Service with Predictive
Analytics
“Apigee has helped us move from simply answering customers’ calls to proactively reaching
out to our members before they have issues.”
Somesh Nigam, SVP and Chief Informatics Officer, Independence Blue Cross
• $1.2B Medicare Advantage
business
• 50+% Reduction in
complaints to Medicare
• Transformed from reactive
to proactive customer
service
• Identified root causes for
dissatisfaction

Typical Use Cases
Proactive Churn Reduction
Reduce churn by predicting customers likely to be at-risk
and proactively responding to them
Individualized Targeting & Recommendations
Improve customer retention, cross-sell, up-sell, loyalty, and
acquisition
20% increase in profit
Individualized daily deals emails
Leading Online Services Company
100% increase in revenue & profit
Individualized website recommendations
Leading Shopping Site
164% lift in conversions
60% more clicks, 55% fewer emails
Recommended products - game launch
Leading Gaming Company
50% fewer complaints
6x more precise predictions
1 month in advance
Leading Healthcare Insurer

Apigee Insights
87
Deep Predictive Analytics Expertise
• Team led Big Data @
Yahoo!, IBM, and others
• Thought leaders in machine
learning and big data
• Extensive Vertical expertise
from client engagements
Accelerate
Business Growth
• Increase revenue, profitability
and customer satisfaction
• Individualized targeting and
recommendations
• Proactive Churn Reduction
Develop
Adaptive Apps & APIs
• GRASP on Hadoop
• Machine Learning on GRASP
• Unstructured & API data
• Real Time
• APIs and Automation
• Cloud or on-premise
Apigee
Insights

Accelerate Digital London Technical Masterclass

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