This presentation discusses using Qlik and Teradata platforms for data science. It introduces Teradata's Unified Data Architecture (UDA) which allows integrating data from Teradata, Aster and Hadoop. A customer example of BICS is provided that uses Qlik and Teradata to analyze over 1TB of telecom data. The presentation also covers collaborative filtering and nPath analysis use cases demonstrated on Teradata platforms. Finally, benefits of using Teradata Cloud with Qlik are discussed.

1. Data Science with Qlik®
Using Teradata, Aster, Hadoop to gain insight
Judd Watts, Teradata
John Park, Qlik
April, 2015

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Jud Watts
• Global Alliance Manager for Teradata.
• Enterprise application sales and sales management
• BA & MBA in the areas of marketing, management &
accounting
• Twitter: @MrJWatts
Presenters
John Park
• Senior Solution Architect, Partner Engineering
• ETL, data warehousing, software design, *NIX,
architecture,
• 2 years at Qlik, 7 years data warehouse consultant
• Twitter: @jpark328

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Agenda: Data Science with Qlik ®
• Introduction
• Can Qlik do Data Science ?
• Teradata the Best Platform for Data Scientist
– Explanation of UDA (R, Hadoop, Query Grid)All Capabilities
– Qlik + Teradata Customer Snapshot – BICS
– Qlik + Teradata Joint Customers
• Teradata Cloud and Qlik
– Teradata Cloud Value Proposition
• Demo
– Qlik Demo with Collabarative Filtering with Aster and Hadoop
– Qlik Demo with nPath Analysis
• Summary and key takeaways

5. Teradata the Best Platform for Data Scientist
Judd Watts

6. QlikView on
Teradata’s Unified Data Architecture (UDA)

7. QlikView now Certified on
Teradata’s Unified Data Architecture (UDA)
Aster Integration:
Dynamic Sankey & nPath SQL-MR
• Demo app on teradata.qlik.com
• Leverage QlikView’s in-memory
associative data model to create dynamic
visualizations with UDA.
• Merge Data from UDA Platform
(Horton, Aster and Teradata)
• Leverage Aster analytical functions
(SQL –MR, SQL-Graph)
• Leveraging nPath for churn and other
customer behavioral analytics
• Enriched results with further context for
business discovery
• Other examples tested for Market Basket
& Collaborative Filtering

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Qlik®
Teradata Mutual Customers
Telecom
• BICS Belgacom International Carrier Services
• AT&T
• T-Mobile
• Swisscom
Retail
• Target Corporation
• Cabela’s
• Safeway
• William’s-Sonoma
Healthcare
• CIGNA
• Geisinger
• Blue Cross Blue Shield MN & NC
• HCA Information Technology & Services
Over 200+ mutual customers worldwide:
Financial Services
• Bank of America
• Citibank
• JP Morgan Chase
• HSBC

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Qlik®
Teradata Joint Customer Snapshot
BICS Telecom
Challenges
• All carriers face challenges planning and monitoring
network performance due to growth of traffic volumes,
technology changes and product options
• Cross border traffic has to be managed
• International network that spans the globe
• Need for service operators to better analyze big data
Solution
• Launch the SMART project (Subscribers Monitoring &
Advance Reporting Tool)
• An advanced (BI) solution for monitoring, measuring,
tracking, tracing and reporting of roaming traffic.
• 2 billion records daily: Call detail records, SMS/MMS
data and billing data all aggregated for analysis
Benefit
• Improved customer satisfaction
• Near real-time availability
• Response times to queries at the speed of thought
• No limitations in available datasets
• SMART differentiates BICS from the competition
• Combination of in-memory & direct discovery with Teradata
Teradata and Qlik allow our providers to access large
data sets for business discovery and intuitively analyze
over a terabyte of data with ‘speed of thought’ response
times, without limitations.
“ “
– Stefaan Paridaens, Data Warehouse Development Manager, BICS
Belgacom International Carrier Services (BICS)
• BICS serves over 800 fixed and mobile
communication service providers worldwide
• Providing best-in-class wholesale solutions, including
IP transport, roaming services and payment transfers
• One of the top voice carriers in the world
• #1 in international traffic for mobile data
• Mission to provide customers with the highest levels
of quality, reliability and interoperability

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Drivers for Cloud Computing
• Agility
– Rapid provisioning
– Ability to scale-up quickly
• Financial Flexibility
– OPEX pricing model, flexible
payment terms
– Less capital required to start
• Focus on Business, not Technology
– No internal data centers required
– Internal technical resources can
focus on high value activities
Teradata Cloud Vision
• “Gold Standard” for Cloud Analytics
– Best in Class Performance,
Functionality, Security, and Reliability
• Fast, Flexible Provisioning & Scale-Up
– Teradata or Discovery Platform
– Running and upsize in 24-48 hours
• Simple, Competitive Flexible Pricing
– Price per Performance Unit
• (Monthly, 1 Year, 3 Year Options)
– All Inclusive Nodes, Software, Storage,
Maint, Operations & Back-ups
• TD Integrated Workload Management
• Highest Levels of Security
Introducing Teradata Cloud and Qlik

11. Teradata Cloud Vision – Unified Data Cloud

12. Let’s Jump into the Demos

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Method of Making Automatic Predictions of User Preference or
Taste from many users (Collaborating)
“If a person A has the same opinion as a
person B on an issue, A is more likely to
have B's opinion on a different issue x than
to have the opinion on x of a person
chosen randomly”
http://asillywhim.blogspot.com/2013/09/huggies-chuggies.html
Data Science Use Case 1 - Collaborative Filter
Up Sell and Cross Sell
Collaborative Filter is part of a larger group of
Data Science function called Associative Analysis.

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Method of looking at series of Data Points and determine how
events are attributed and how certain out comes arrive.
“If a person purchased product A and
there was 10 events that happened prior to
purchase decision the 10 events could
have attributed to the decision. If we can
see what the attributing event and path to
purchase; we are more likely to optimize
purchase decisions of product A. “
http://blogs.nd.edu/oblation/2013/09/30/badly-broken-a-spoiler-free-analysis-of-breaking-bad-as-a-deeply-human-drama/
Data Science Use Case 2 – Path and Pattern
Discovery
Recommendation Engine
Attribution and nPath are part of a larger group of
Data Science function in Path and Pattern
Discovery.

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Let’s Break Down the Analytics Cycle for Data
Science
Qlik and Teradata (Teradata, Aster, Hadoop) are in unique position to Serve Data
Scientist and Business users.
• Finding Insight is all about Ideas stemming
from Business Problems
• Very resources intensive
• Finding the right platforms/tools can be
everything.
• Use Qlik as a visualization tool for Data
Scientists
• Use Teradata as Platform for Data Scientists
+

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Combine Teradata and Qlik for maximum benefits
• Provide your clients with production scale rapid deployment
• An affordable flexible option that also scales for big data needs
– No Hardware or Software to Buy
– Industry Expertise
– Get Started Quickly
“Teradata Cloud provides data warehousing for the masses, with access to
industry expertise and best practices previously available only to top tier
customers. All built on Teradata, the gold standard for analytics.”
Teradata Cloud
Bob Graham, Vice President of IT, BevMo

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• Teradata and Qlik:
– Allow you to solve hard problems
– Allow business users to participate in data science
– Provide an unified platform for data scientist to business users
– Is a proven analytics platform for any type of data
Key takeaways

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Web resources
• www.teradata.com/partners/qlik
• http://aster.qlik.com
• http://teradata.qlik.com
Go-to-market resources
• Mike Foster – Alliance Technology
Officer
• Hugo Sheng – Senior Director of
Partner Engineering
• Judd Watts – Teradata Global
Alliance Manager
Further your learning
Teradata Cloud
Animated Video
The Cloud: An
Abundance of Choices
“The Perfect Fit”
Teradata Magazine
Article
Where Affordability and
Flexibility Meet

19. Question & Answer

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Feedback survey
• Please complete the track session survey via the mobile app
• Access the track session survey through the mobile app
• Enter track session code T61
• Provide your feedback

21. Thank You