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Welcome to…
The Future of Analytics In Action
© 2015 IBM Corporation
Goals for Today
•  Share the cloud-based data management and analytics technologies that
are enabling rapid development of new mobile applications
•  Discuss examples of how these technologies are being applied to
transform a diverse set of industries
•  Hear from you about your most pressing challenges to harness the data
you have to provide additional value for your customers
2
Today’s Agenda
8:30 am to 9:00 am
9:00 am to 10:00 am
10:00 am to 10:30 am
10:30 am to 10:45 am
10:45 to 11:15 am
11:15 to 11:45 am
11:45 am to 12:00 pm
12:00 pm to 1:00 pm
3
Registration and Continental Breakfast
The Future of Analytics in Action: The Art of the Possible
Demonstration
Break
Real World Insights: Comdata’s Journey
Open Q&A
Wrap-Up
Lunch and Networking
The Future of Analytics In Action:
The Art of the Possible
Why the Journey to Cloud-based Analytics?
5
FASTER
INNOVATION
BETTER IT
ECONOMICS
LOWER RISK OF
FAILURE
Instant provisioning
saves weeks of data
center setup
Pay as you go with no
big up-front capital
investments
Fully managed 24x7
so you can focus on
new development
The Future of Analytics – From Our DBaaS Offerings…
Transactional DBaaS
6
Analytic DBaaS
Cloudant
SQL DB
dashDB
BigInsights on Cloud
NoSQL DBaaS
Relational DBaaS
Relational Data Mart
Enterprise
Hadoop
…To our Business Analytics and Intelligence Offerings
Predictive Analytics
n 
n 
n 
SPSS Data Collection
SPSS Modeler Gold
Social Media Analytics
Watson
n 
n 
Watson Analytics
Watson Curator
Content Management
n 
Navigator
Risk
n 
n 
n 
n 
n 
n 
Algo Managed Services
Algo Risk Content
Algo Risk Reports
Algo Risk Service
Algo Pension Monitoring
IBM Open Pages GRC
Business Intelligence
n 
Cognos Business Intelligence
Performance Management
n 
n 
n 
n 
n 
n 
7
Cognos TM1
Cognos Concert
Cognos Disclosure Management
Cognos Quota Management
Cognos Territory Management
Cognos Incentive Management Compensation
IBM can help your organization deliver new insights at
every level, and in every department, in your organization.
Have real time visibility
into stock levels
Optmize staffing mix,
reduce employee turnover
Operations
Human
Resources
Reduce churn
by knowing what the
cusotmers are saying
Product
Development
Customer
Service
IT
Sales
Access key customer
information in the office and
on the road
Marketing
8
Work on scenarios to
align development
resources
Combine personal and
corporate data to create fresh
insights
Provide discovery and
planning tools to reduce errorFinance
prone spreadsheet work
Drive growth and profit through
resource alllocation
Manage rolling
comply with confidence
expenses
IBM voted #1 cloud provider by enterprise users
“Who would you choose as your cloud provider?”
Amazon Web Services
Microsoft
IBM
Based on an April 2015 451 Research survey of more than 2,000 enterprise cloud users - commissioned by Microsoft
9
IBM’s Latest Cloud Analytics Offerings and How
They’re Changing Analytics for our Clients Today.
10
IBM Cloudant
11
IBM Cloudant – NoSQL Operational Data Store
•  Innovator of “Database as a
Service” (DBaaS)
•  JSON document database
IBM Cloudant
For apps that need:
-  Elastic scalability
-  High availability
-  Data model flexibility
-  Data mobility
-  Text search
-  Geospatial
Available as:
-  Fully managed DBaaS
Build More.
Grow More.
Sleep More.
-  On-premises private cloud
-  Hybrid architecture
12
13
The Future of Cloud Based Analytics: A foundation with
dashDB
§  Fully managed data warehouse in the cloud
§  In-memory acceleration capabilities with
columnar technology, advanced compression,
and buffer pool technology
§  In-database predictive analytics & R-support
§  Integrated with Cloudant for analytics on JSON
data from web & mobile apps
§  True “Load & Go” approach – no need to
predefine indexes
§  Built-in Netezza analytic algorithms
Coming in 2Q!
§  Enhanced Netezza Compatibility
§  Oracle compatibility mode
§  MPP
14
BLU !
Acceleration!
Netezza !
In-Database
Analytics!
Cloudant
Database !
as a Service!
IBM BigInsights on Cloud
15
IBM BigInsights Cloud – Enterprise Hadoop as a Service
Big Data – easier, faster, richer
IBM BigInsights Cloud
•  Analyze petabytes of any kind of data on
elastic compute clusters
•  Easy to integrate
•  Connect common 3rd party BI tools
16
Enterprise Capabilities
•  Native Hadoop enriched with:
•  Faster performance
•  ~4x faster than open source Hadoop
•  Visualization tools
•  Built-in R, streaming & text analytics
•  Data protection & governance
Development Tools
Advanced Engines
Connectors
Workload Optimization
Administration & Security
Open
source
•  Easy to adopt
•  Provisioned, hosted, scaled for you
Visualization & Exploration
Open source
Hadoop components
Watson Analytics
17
IBM Watson Analytics for smarter data discovery
100’s of new ques3ons asked each day through explora3on and discovery Watson Analy3cs Business user led analy3cs 18
10’s of insigh:ul discoveries presented to, and evaluated by decision makers 1 change, improves alignment, opera3ons and repor3ng; governed and scalable Analy3c pla:orms and database sources Advanced user and IT managed analy3cs © 2015 IBM Corporation
Watson Analytics
Single Interface … Explore > Predict > Assemble
Quick start
intuitive
interface
Guided
discovery &
visualization
Easy data
upload and
search
capabilities
19
Key business
driver insights
Natural
language
dialogue
Dashboard
and
storytelling
authoring
IBM Cloud-based analytics summary
100s of Paying
Customers
Global
Operations
50,000+
Users
300% Growth
Y2Y
300+ CDS Team
Members
20
Use cases and customer examples
21
Use Case: Cloud Analytics for Web & Mobile
§  Build an app and analyze usage to:
Cloudant Sync
-  Understand user behavior
-  Increase monetization
§  Millions of users transact with
Cloudant via REST
(iOS & Android)
Data
Center 1
Continuous, filtered
replication & sync
(Active DR)
HTTPS
HTTPS
§  Off-line mobile data access enabled
by Cloudant Sync
Continuous, filtered
replication & sync
HTTPS
§  Perform analytics with dashDB
Data
Center 2
Continuous
sync
(Active DR)
-  Data is continuously synched
with Cloudant
-  Accessed by BI Tools such as
Watson Analytics via Dataworks
22
Dataworks
dashDB
data mart
BI Tool
User
Payment Processor
leverages the advanced geospatial capabilities of Cloudant to
build a new mobile application
23
The combination of Cloudant’s advanced geospatial
capabilities, security, and managed service give Comdata a
competitive advantage in terms of the experience they can
deliver to their end users
IBM Internal Use Only
Use Case: Comdata
Company Background
-  Payment processor and issuer of fleet fuel cards headquartered
in Tennessee.
Need
-  A mobile app that delivers a better experience for end users of
Comdata’s payment processing system.
Success Criteria
-  Show locations of vendors that use Comdata’s payment
processing, enable offline usage, and optimize routes.
-  Complete within 20 months
Solution & Results
-  A new mobile application launched in 9 months!
-  Advanced geospatial capabilities give Comdata a competitive
advantage
-  Cloudant’s managed service means Comdata can keep overhead
costs down
24
20
months
9
months
-  Comdata avoids the costs, overhead, or latencies of ETL by with
the schema flexibility Cloudant’s JSON document store provides
Use Case: Comdata - Reference Architecture
Mobile
Devices
Local
Storage
MobileFirst on
Softlayer
Cloudant
User profiles, preferences,
point of interest, etc.
MobileFirst
adapter
Geolocation information originally
stored in DB2
Comdata Firewall
25
Relational
Database
Use Case: Cloud Analytics for Agility
§  How quickly can you
create a 1TB data mart?
Web & Mobile
users
-  Average Oracle &
Teradata data marts take
>50 days to implement
(ITG)
§  What are you spending
on QlikView per year?
-  Cloud faster, cheaper?
§  Equip users with dashDB
and Big Insights for
modern, agile analytics
SQL DB
Aggregations
Big Insights
on the Cloud
ODBC
dashDB
data mart
ODBC
BI Tool Users
26
A Large Investment
Research & Management Firm
needed a persistent data store to maintain and access financial
analytical reports
Cloudant’s schema-less architecture and horizontal scalability
enables their users users to have real-time access to reports and
analytics generated by IBM PureData for Analytics
27
Use Case: Investment Research & Management Firm
Company Background
-  Global Investment & financial services research firm
Need
-  Provide real-time access to data for a new system of engagement
application for accessing and visualizing reports from Netezza
through a custom API
Success Criteria
-  Support for high volume of user concurrency – something a
warehouse environment like Netezza cannot provide
-  Integration with other IBM products – like Netezza
Solution & Results
-  Schema-less architecture enables the ability to store the data
without needing a schema definition prior to inserting the data from
Netezza.
-  Does not require time consuming schema changes when different
data must be captured and processed
-  With Cloudant, the firm is transforming how their users access data
28
Use Case: Investment Research & Management Firm
The architecture diagram of the Transient
Query Result Storage (TQRS) use-case is
shown below. The process and data flow
are as follows: 1.  An end user requests a dataset to be visualized
by the firm’s service. 2.  The request is processed through an API which
queries a Netezza data warehouse for the
requested data. API
3.  Netezza returns the requested dataset back to
the API. 4.  The API internally prepares the data for
visualization and storage by converting it into
JSON format. A small subset of the data will be
sent to the calling application for visualization
while the full dataset will be persisted into
Cloudant. 5.  The initial requesting application can now query,
page, sort … etc against the data in Cloudant
until they are finished.
29
An Insurance Company
uses Cloudant Local to create a persistent data store to manage
customer policy information.
Having a need to have real-time visibility to customer data from
different Systems of Record, the Insurance Company values
Cloudant’s ability to manage data from different systems and
navigate the data with embedded search capabilities.
30
Use Case: Insurance Company
Company Background
-  Global insurance company with annual revenues of over $40B and
locations in the US, Europe, Latin America, China, and more
Need
-  Improve customer experience for roughly 40 million customers by
enabling the ability to efficiently search all data such as: personal
information, policies, claims, etc.
Success Criteria
Cloudant Managed or
Local deployment
-  To manage and search data from different Systems of Records without
having to design a web app with a schema-first mentality
-  A solution that can be managed on-premises for sensitive customer
information but still have the ability to move to the Cloud in the future
Solution & Results
-  Implemented Cloudant Local on-premises and then will move some
applications to a public cloud deployment
-  Provided the ability to manage all the data in one location while enabling
the full-text search capabilities
•  Previously, the company struggled using SOLR with their existing solutions.
31
JSON
Auto
Policy
JSON
Auto
Policy
JSON
Auto
Policy
Use Case: Insurance Company – Architecture Details
3: Develop apps leveraging
Cloudant's API & enable
systems of engagement to
operate at webscale
2: Push 360o data to
Cloudant for mobile
workers
1: Cloudant JSON data
sent to Watson Explorer to
index
Watson
Explorer
Cloudant Managed or
Local deployment
JSON
32
Auto
Policy
JSON
Home
Policy
JSON
Billing
Data
CRM
FILE SHARES
HTML
RDMS
SOCIAL
EMAIL
SHAREPOINT
Use Case: Insurance Company – Deeper Look
TIME SENSITIVE ANALYTICS PROJECT:
Seasoned analytics and warehouse customer, but looking at new analytics project that must
get off the ground quickly. Time to value, speed, simplicity, reduced risk of project failure are
all important.
Data Warehouse
& Analytics
Service!
33
• Data warehousing and analytics in the
cloud!
• Cloud agility and flexibility!
• Analytics for cloud data, data marts,
and development & test environments!
A Pharmaceutical Distributor
creates an analytics dashboard with IBM Cloud-based analytics
34
Use Case: Pharmaceutical Distributor
Company Background
-  A globally distributed Fortune 500 Pharmaceutical Distributor
Need
-  After acquiring another organization they needed to create a supplier
spend analytics dashboard for synergy capture
-  Provide enterprise wide visibility to the global procurement team to
facilitate negotiations with suppliers and track alignment on terms
-  Deliver the project in 10 weeks
Success Criteria
- 
- 
Key focus areas: Cost savings with vendors, Compliance with
suppliers, Identify growth trends
Time to value
Solution & Results
-  DashDB + Information Server on Softlayer allowed us provide a cloud
warehouse and hosted data integration tool
-  The IBM team delivered the solution in weeks and exceeded
customers expectations.
35
Use Case: Pharmaceutical Distributor – Architecture Details
Pharma UK branch
Netezza
Rancho
Cordova,
USA
Infinium/
MBA
Montreal,
Canada
1
1
SAP
Stuttgart,
Germany
1
6
Softlayer Dallas
Private Network
2, 3
Information
Server
Tableau
Server
4
Softlayer Dallas
Public Cloud
5
36
1. 
2. 
3. 
4. 
5. 
6. 
Connect to company
Extract from sources
Transform into target model
Load into warehouse
Analyze
Report & visualize
Use Case: Pharmaceutical Distributor – Deeper Look
New data warehouse environment.
-  Customer does not have an existing analytics / warehouse solution.
-  This is often coupled with lack of skills/resources, preference to opex
environments, needs something quickly, does not have 100+TB environment.
Extend / Modernize!
37
• Extend on-premises data warehouse
environments to the cloud!
• Flexible, cost-effective growth!
• Hybrid cloud models support ground to cloud!
A Food Distributor
had been using Oracle but required better insight into streamlining sales
operations through their various channels/businesses
38
Use Case: Food Distributor
Company Background
-  An international food distributor with zero analytics or insight around
financial data from different areas of the business
Need
-  Required better insight into streamlining sales operations through
their various channels (consumer, wholesale, pet food, retail)]
Success Criteria
- 
- 
Traditionally, an Oracle Shop, but the marketing department
brought in and required integration with Tableau
Someone to perform rapid provisioning of the data warehouse on
the cloud without requiring any DBA expertise
Solution & Results
-  They were able to access the data seamlessly using Tableau.
-  Without a DBA, they were able to load data into the dashDB data
warehouse and used Watson Analytics in along with dashDB to
perform even deeper analytics
39
Use Case: Food Distributor– Architecture Details
Softlayer Dallas
Public Cloud
The company’s team
created their own scripts
to load the data
Oracle database
environment
•  Arkansas
datacenter
•  Financial data
40
Use Case: Food Distributor– Deeper Look
COMPLETE CLOUD BASED ANALYTICS
-  New analytics project that leverages our offerings, Cloudant, dashDB, and SaaS
based Analytics through Cognos.
41
Cloudant Analytics!
• Easy synchronization of JSON to structured data!
• Allows analytics via standard BI tools!
• In-database predictive algorithms allow greater
insight for Cloudant users than ever before!
Data Warehouse &
Analytics Service!
• Data warehousing and analytics in the cloud!
• Cloud agility and flexibility!
• Analytics for cloud data, data marts, and
development & test environments!
A Car Manufacturer
requires a data management or analytic solution to
understand campaign effectiveness.
42
Use Case: Car Manufacturer
Company Background
-  A multinational car manufacturer is equipping their 2015
and later models with an "interactive" infotainment system.
Need
-  A data management or analytic solution to understand
campaign effectiveness.
Success Criteria
-  Take unstructured data, automatically format it, and report
against it in the cloud, allowing the company’s marketing
team & merchants to segment customers and measure
campaign effectiveness.
Solution & Results
43
-  Provisioned a prototype environment of dashDB with
Cloudant in 24 hours illustrating the speed and agility
possible
-  Flexibility and power of the IBM portfolio was critical for the
project’s success
-  The car manufacturer is getting a lot of value and analytics
from their infotainment systems.
Use Case: Car Manufacturer– Architecture Details
Vehicle Data
-  Bulk load of 6-8 million
accounts, 28 millions
cars (~1TB of data)
-  Deltas continued to be
load for user/vehicle
Other Data Sources
data
IBM Datastage
-  Softlayer Dallas
-  Data movement into
SFDC and into dashDB
JSON data to relational
Cloudant Schema Discovery
Protocol
44
IBM Cloudant
-  3 node production cluster
-  3 node dev cluster
IBM dashDB
-  4 TB production system
-  4 TB dev system
Questions?
45
Demonstration
Let’s Take a Break
Real World Insights: Comdata’s Journey
Driving Smarter
Fuel Choices
49
Questions?
50
Learn More
51

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