Pervasive Analytics Gets Real

Pervasive
Analytics Gets
Real
December 2014

© 2014 Cloudera, Inc. All rights reserved. 2
Agenda
1. Forrester – Pervasive analytics & industry trends
1. Intel – Healthcare use cases
1. Cloudera – Financial Services & Retail use cases
1. Q&A

Pervasive Analytics Gets Real
Mike Gualtieri, Principal Analyst
December 2014

Growth and customer experience are priorities
to business leaders
© 2013 Forrester Research, Inc. Reproduction Prohibited 4

Demand for analytics is strong across all business
functions and across all industries that generate and
consume data.
© 2012 Forrester Research, Inc. Reproduction Prohibited
5
Research &
Development
Operations
Marketing &
Advertising
Sales
Execution
Customer
Experience
Finance

Businesses often think of analytics as a set of
historical reports and dashboards…

…but, analytics is also about the future.

It’s important to have all kinds of analytics.
Past Present Future
Learn React Anticipate
Predictive
Analytics
Streaming
Analytics
Descriptive
Analytics

Pervasive analytics is the winning strategy.

PERVASIV
Information-driven business culture that uses
ubiquitously available analytics of all kinds to
continuously improve customer experience,
operations efficiency, and decision-making.
E
ANALYTICS

Momentum is strong for streaming and predictive
analytics, but underadopted.
“What is your firm's/business unit's current use of the following technologies?”
21%
21%
20%
18%
13%
10%
20%
16%
29%
24%
37%
33%
57%
54%
50%
49%
58%
56%
81%
15%
21%
32%
27%
19%
33%
42%
35%
50%
59%
77%
Reporting
Dashboard
Web Analytics
Performance analytics
Embedded Analytics
Olap
Process Analytics
Location Analytics
Search/Interactive Discovery
Predictive Analytics
Metadata Generated Analytics
Text Analytics
Advanced Visualization
Streaming Analytics
Non Modeled Data Exploration And…
2014
2012
Source: Forrester Research
+52%
+62%

Most want deeper insights through advanced analytics
but familar challenges persist.
What are the main business and technical requirements or inadequacies of earlier-generation business
intelligence technologies that lead you to consider new BI techniques and technologies?
2%
2%
We want deeper insights through advanced analytics
Data volumes have grown beyond what we can cost-…
Data changes or becomes available much faster than…
We want to access data that was not accessible for us…
We don't know what our entire data universe contains,…
The performance of certain analysis is not sufficient
Analysis requirements change too fast to keep up with
The number of data formats that we must be able to…
The velocity of data is too high for earlier technologies
Earlier-generation technology is too expensive
Other (please specify)
Base: 452 North American technology decision-makers
Respondents answering “don’t know” are not shown
Source: Global Data and Analytics Survey, 2014
14%
16%
20%
33%
35%
34%
31%
32%
32%
31%
27%
28%
29%
26%
28%
23%
35%
Business decision makers
Technology decision makers
Base: 249 North American business decision-makers
Respondents answering “don’t know” are not shown
Source: Global Data and Analytics Survey, 2014
44%
45%
12%

Quiz
What percentage of enterprise data do firms
use for analytics?
A. 12%
B. 34%
C. 53%
D. 76%
Enterprise
Data

Quiz
What percentage of enterprise data do firms
use for analytics?
A. 12%
B. 34%
C. 53%
D. 76%
Enterprise
Data
Source: Forrester Research

110010011011001
010011001101101
010010011011001
010010011011001
Security
Transactions
Historical
Customer data
Silos must disappear or appear to disappear.

Data quality must be unassailable.

Structured, unstructured, and binary analytics
must converge.

Confidential information must be secure.

Access and analysis must be blazing fast.

Fault-tolerance is non-negotiable.

Pervasive analytics must fit seamlessly into
existing enterprises architectures.

Analytics must be embedded in cross-device
applications.

Every industry is graced with more data…
› Richer transactional data from portfolio of dozens or
hundreds of business applications
› Usage and behavior data from web and mobile apps
› Social media data
› Sensor and event data from IoT devices
› Data economy – firms buying and selling data
› Derived data from analytics

Advanced analytics, risk management, digital
technologies.
Financial
Services Trends

Financial services executives know that
digital is a threat
Base: 1,254 executives in companies with 250 or more employees
(respondents may be counted in multiple industry groups)
Source: Forrester/Russell Reynolds 2014 Digital Business Online Survey

Financial Services
Use Case
How can I use the process communication
model (PCM) to have better customer service?

Financial Services
Use Case
What are movers and shakers saying about
equities that we cover?

Healthcare
Trends
Shared EMRs, predictive patient care,
wearables, genomic drug discovery.

Healthcare
Use Case
How can you listen to customers to measure
share of voice, efficacy, and side effects?

Healthcare
Use Case
How can you know if your baby is sleeping
soundly or if something is wrong?

Retail Trends
Customer obsession, omni-channel planning,
personalized marketing, in-store technology.

More than half of all US retail sales will either
be influenced by or occur online
($ billions)
Source: Forrester Research Web-Influenced Retail Sales Forecast, 2012 To 2017 (US)

Retail Use
Case
What if you knew your customer was near your
store on a sunny day?

Retail Use
Case
How can you prevent this dude from fleecing
you?

Pervasive analytics is
a strategy.

Change your industry with analytics
› Walk through critical or challenging business processes
• At each step of the business process ask how analytics could
improve the process
› Walk through customer journey to improve customer
experience
• At each step of the customer journey, ask how analytics could
improve the customer experience

Pervasive Analytics in
Health Care

Health Care and Pervasive Analytics
42
Unlocking Insight – Key Sources of Data for Health Care
Clinical Data
• Health history
• Medications
Genomics Data
• Genetic pre-dispositions
• Tumor gene sequencing
Patient Data (IoT)
• Vitals
• Activity
• Bio-signals
Diagnostic Data
• Lab results
• Imaging

Health Care and Pervasive Analytics – Key Use Cases
• Reduction of patient readmission rates
• Predict patterns in the transmission of infectious diseases
• Personalized health care treatment
• More efficient drug clinical trials
• Remote patient and at home elder care
• Identification of new treatments for degenerative diseases
43

Parkinson’s is an Increasingly Common Neurodegenerative
Disease
44

45
Disease

46
Disease

Research
Today:
Small, infrequent
clinical trials
Subjective data
Difficult to share
between researchers
47

Applying Big Data Technologies to Accelerate
Research
Wearable
Devices
Cloud
Infrastructure
Discovery
Data &
Analytics
Platform
48

Parkinson’s Research with Big Data
49
Smartphone App
24 x 7 monitoring Wearable Monitor
- 1 GB / person / day
Big Data Analytics
Objective measurements
- Location
- Movement
- Medications
Activity Identification
- Sleep Patterns
- Gait
- Balance
- Tremors
Anomaly Detection
1 GB/Patient/Day

Analytics Embedded
Throughout the
Data Value Chain
Ryan Goldman // Director of Product Marketing

Information is the Primary Resource of FinServ
Mapping and Consolidation Are the Tip of the Iceberg for Big Data
Retail Banking
• Bank Transactions
• Customer Data
• ATM Activity
• Online Activity
• Mobile Activity
• Demographic / Census
Data
• Marketing / CRM
• Social / Sentiment
Credit Cards &
Payments
• Card Transactions
• Customer Data
• Online Activity
Data
• Marketing / CRM
• Integration with
Retailers / Loyalty
Investment
Banking
• Trade / Tick Data
• Customer Data
• Web Logs
• Research /
Publications
• Market Data
• Communications /
Documentation
Insurance
• Claims / Policy Data
• Customer Data
Data
• Weather Data
• Vehicle Telemetry
• Video / Surveillance
• Sensors
• Internet of Things
Services & SROs
• Trade Data
Documentation
• Market Data
• Research / Publications
• Surveys

Retail Banking
• Bank Transactions
• Customer Data
• ATM Activity
• Online Activity
• Mobile Activity
Data
• Marketing / CRM
Credit Cards &
Payments
• Card Transactions
• Customer Data
• Online Activity
Data
• Marketing / CRM
• Integration with
Retailers / Loyalty
Investment
Banking
• Trade / Tick Data
• Customer Data
• Web Logs
• Research /
Publications
• Market Data
Documentation
Insurance
• Claims / Policy Data
• Customer Data
Data
• Weather Data
• Vehicle Telemetry
• Sensors
Services & SROs
• Trade Data
Documentation
• Market Data
• Research / Publications
• Surveys
Compliance Cost Savings
Customer
Insights
Competitive
Advantage

A Predictive Analytics strategy helps address the business’s biggest challenges and opportunities
Compliance Cost Savings
Customer
Insights
Competitive
Advantage

More Value from More Data for More Users in Less Time
Maximize Benefit from All Your Data for Mission-Critical Jobs and Innovation
Process Discove
r
Model Serve
Data
Access
Data
Systems
Data
Sources
Business
Analytics
Custom
Applications
Databases
Existing
Data
Operational
Applications
New Data
Unlock Value from Data
From analytics for some,
to insights for all.
Manage Compliance
From risk due to regulations and
customer privacy concerns,
to trust in a secure and
compliant platform.
Keep Unlimited Data
From disparate and limited views,
to unlimited information access.
Enterprise Data Hub
Security and Administration
Unlimited Storage

Full Regulatory Compliance
Centralized Management of and Reporting on All Your Data in Full Fidelity
PORTFOLIO RISK
Basel III: liquid capital
coverage for changing
stress, volatility, rates
Apache Spark
Impala
E-RECORDS
WORM: retention of all
records without deletion or
alteration
Apache HBase
Cloudera Search
TRADE REPORTING
OATS: reporting on all
orders, quotes, trades, etc.
Precursor to CAT
MapReduce, Spark,
HBase, Impala
DATA SECURITY
PCI DSS: ensure credit
cardholder privacy and
transaction security
Cloudera Navigator:
Encrypt & Key Trustee
Full risk, fraud, retention, and
transaction security compliance
enabled by an enterprise data hub
• Consolidate ETL, linkage, analysis,
reporting, storage
• Offset high opportunity cost of
specialized systems
• Centralize and increase utilization of
requisite data
• Improve speed and reduce pain of
compliance reporting

Problem
Solution
Operational Data Store
OATS regulation requires electronic auditing and reporting capabilities on all stock and
equity orders, quotes, trades, and cancelations for greater scrutiny.
Moving Data to Compute
Expanding reporting requirements—for both financial services firms and SROs—are
overwhelming systems built on traditional enterprise data warehouses.
Active Archive
Search and Impala provide in-cluster investigation and reporting capabilities to centralize
diverse data in a multi-tenant environment for multiple use cases.
Use Case

How can we cut our storage footprint and
costs and improve data governance?

With a compliant big data environment, can we
extend the value of Hadoop from IT to Risk and Marketing?

With a compliant big data environment, can we
extend the value of Hadoop from IT to Risk and Marketing?
© 2014 Cloudera, Inc. All rights reserved.
6622
Machine learning for advanced security and threat analytics.
Analytical automation for next-best-offer recommenders.

Where Is the Retail Data?
No Single Record in a Silo Is as Valuable as a Navigable Convergence of All Data
Customer
Transactions
• POS / TLOG
• E-commerce /
Mobile Sales
• Memberships /
Loyalty Programs
• Warranties
Consumer
Behaviors
• Sensors /
• Search / Clickstreams
• Consumer Habits /
Consumption
Merchandising
& Operations
• Schematic / Displays
• Store Layout /
Characteristics
• Orders / Receipts
• Staffing / Scheduling
• Retailtainment
• Supply Chain /
Inventories
Marketing &
CRM
• Promotions / Offers
• Website / SEO
• Campaigns / Affiliate
• Surveys
• Competitive
Intelligence
Public & Trade
• Psychographic
• Inflation /
Macroeconomic
• Gas Prices
• Labor Statistics
• Weather Data
• Public Health Data
• Media Trends
• Industry Research

One Platform, Many Workloads
Advance from Strategy to ROI with Best Practices and Peak Performance
Batch, Interactive,
and Real-Time.
Leading performance and
usability in one platform.
• End-to-end analytic
workflows
• Access more data
• Work with data in new ways
• Enable new users
Process
Ingest
Sqoop, Flume
Transform
MapReduce,
Hive, Pig, Spark
Discover
Analytic
Database
Impala
Search
Solr
Model
Machine
Learning
SAS, R, Spark,
Mahout
Security and Administration
Serve
NoSQL
Database
HBase
Streaming
Spark Streaming
YARN, Cloudera Manager
Cloudera Navigator
Unlimited Storage HDFS

The Journey to a Data Strategy
Operational Efficiency Buys Option on Exploration, Data Science, and Convergence
Opera onal Efficiency New Business Value
Process Discover Model Serve
Security and Administra on
Unlimited Storage
Op mize your architecture.
IT
Discover the value in your data.
analysts and data scien sts
Empower users directly.
everyone

Enterprise-Grade Security
Governing Access to and Management of All Data-at-Rest and Data-in-Motion
AUTHENTICATION
Guarding access to the
system, its data, and its
various systems
LDAP
Kerberos RPC
PROTECTION
Encryption for data at rest
or in motion with full key
management
Cloudera Navigator:
Encrypt & Key Trustee
AUTHORIZATION
Controlling who or what has
access to a resource or
service
POSIX Permissions
Apache Sentry
AUDIT
Capture a complete and
immutable record of all
activity
Cloudera Navigator
SIEM Tools
Achieve full PCI DSS compliance
native to Cloudera Enterprise
• Cloudera Manager and Navigator
automate protections for Hadoop
and related projects
• Perimeter security
• Role-based access control
• The only complete policy-based
management of sensitive data
• Data lineage and discoverability

Problem
Solution
Unified Customer Identity
Compress the customer IDs created through various siloed and third-party touch points to
correlate as a single customer identity across all operational systems.
Data without a Master
Metadata across legacy systems is insufficient to eliminate profile duplication and
implement master data management as databases converge.
Single Source of Truth
HBase is a real-time database accommodating complex historical data of massive size,
regardless of origin or channel, which enables entity reconciliation at scale.
Use Case

With a compliant big data environment, can we extend the value of
Hadoop beyond IT to Merchandising and Marketing?

With a compliant big data environment, can we extend the value of
Hadoop beyond IT to Merchandising and Marketing?
Regression analysis for market basket optimization.
Customer graph analytics for real-time dynamic offers and pricing.

Q&A
Mike Gualtieri
Principal Analyst at Forrester
Research
Ron Kasabian
GM of Big Data Solutions at
Intel
Ryan Goldman
Product Marketing Dir. at
Cloudera

Pervasive Analytics Gets Real

More Related Content

What's hot

Similar to Pervasive Analytics Gets Real

More from Cloudera, Inc.

Recently uploaded

Pervasive Analytics Gets Real