Sources for pictures are Wikipedia.

1. A Picture is worth a 1000 words
Visualizing your Big Data
John Park – Sr. Solution Architect, Partner Engineering - Qlik
Adam London – Sr. Solution Architect, Teradata Aster
November 19, 2014

2. Notice
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3. Introduction
Today’s Agenda
Why Pictures are Important
Visualizing Big Data
Teradata Aster Overview
Banking Customer Journey

4. Why are Pictures so important to humans ?
“words divide, pictures unite” -Otto Neurath
ISOTYPE(International Study of Typographical Education) 1934

5. A Better Visualization is needed for Big Data
5
• Self Explanatory
• Expose Hidden Facts and allow
deeper insights
• Show data complexity
• Easily Detect Patterns
• Tradition graphs and plots don’t fit the
need of data visualization anymore.

6. Asking the Why’s
Predictive
Analytics
Diagnostic
Analytics
Customer Needs
and Analytic Value
Typical Customer Journey
(gradual over time)
Descriptive Analytics
Viz Tools
Hindsight Insight Foresight
Complex
Simple
What is likely
to happen?
Time, Scope of Offering
and Customer Evolution
Start
Narrow Wide
What
happened,
where and
when?
Why did it
happen?
QlikView

7. Big Data is Finding Patterns
• Association – broader, more flexible application
• Exploration – un-paralleled navigation
• Search – flexible and powerful
• Real-time collaboration
All of this in an Intuitive and Fast Interface
Better Insights = Greater Business Value

8. Rich API to create Visualization to Find Pattern

9. Qlik + Aster
Aster Data Discovery Platform and Qlik Business Discovery Platform are
Complementary to Deliver Data Science insight to the Business Analyst
Visualization Platform
Geared toward Business
Analyst
Allows Business discovery by
associative model
Relational Database / Map Reduce /
Graph / Analytic Platform
Geared toward Data Scientist and
Subject Matter Experts
Complex Algorithms – Path Analysis,
Market Basket, Classification,
Attribution and more.
Qlik Simplifies access to Aster’s Sophisticated analytics and makes aster
consumable by the your average business users.

10. Teradata Aster Overview

11. Big Data “Analytics”
The Problem
Data Warehouse/
Business Intelligence
Advanced
Analytics
Proliferation of Big Data analytics
environments has resulted in fragmented data,
higher costs, expensive skills, longer time to
insight
The Solution
SQL Framework Access Layer
Integrated
Discovery Platform
(IDP)
Pre-Built Analytics Functions
An Integrated Discovery Platform provides deeper
insight, integrated access, ease of use, lower cost of
ownership

12. Discovery Platform Requirements
ALL DATA
Non-
Relational
Data
Multi-
Structured
Data
Structured
Data
DISCOVERY All ANALYTICS USERS
Discovery
Platform
Data
Scientist
SQL
MapReduce
Statistical
Functions
OLTP
DBMS’s
• Doesn’t require
extensive
modeling
• Doesn’t balance
the books
• Data
completeness can
be good enough
• No stringent SLAs
Behavioral
• Customer
• Product
• Machine
• Supply chain
Data
Analyst
ITERATIVE ANALYSIS
Text
Graph

13. What is Teradata Aster?
Industry’s next-generation, integrated big data discovery solution optimized for
multiple analytics on all data to accelerate time to value.
Value
Reduces complexity, breaks down analytic silos, and magnifies analytic ability making it
faster and easier for a wider group of users to generate high impact business insights.
Unique Features
• Complete Appliance
• MPP architecture for rapid analysis on all data at scale
• 120+ prebuilt analytic functions
• Integrates with existing analytic & BI tools like Qlik
• Integrates with Hadoop, EDW’s, RDBMS, and more
Sample Client List (Over 100+ installations)
Proven solution to accelerate
complex analytic insights
by 3X to 5X

14. Customers Business Analysts Data Scientists
Data Acquisition
Module
Data Preparation
Module
Analytics Module Visualization Module
Teradata Access
Hadoop Access
RDBMS Access
Data Adaptors
Data Transformers
Flow Visualizer
Hierarchy Visualizer
Graph
Time Series
Pattern Matching
Text
Statistical
SNAP FRAMEWORK™
Email Web Logs ERP, CRM Social Media, EDW
Sensor
Row Store
Databases Hadoop
Teradata Aster
Discovery Platform
Analytic
Engines
Multi-Type
Store
SQL-MapReduce® SQL-GR™
ROW STORE HADOOP FILE
STORE
COLUMN STORE
INTEGRATED
OPTIMIZER
INTEGRATED
EXECUTOR
UNIFIED SQL
INTERFACE
STORAGE SYSTEM
AND SERVICES
SNAP
Framework™
CUSTOM
BIG ANALYTIC
APPS
BI
TOOLS SQL Client Teradata Aster Lens™ IDE
Affinity Visualizer
SQL

15. Aster’s Deep Analytic Function Set - 120+
Inverse) nPathviz
Connection
Analytics
Wavelet
Transformations
(Discrete, 2D,
Time Series Analysis
Aster Advanced Analytics SQL-GR & SQL-MR Functions
Closeness
Betweenness
Eigen Vector
Local Clustering
PageRank
K-degree
Shortest Path
Loopy Belief
Hidden Markov
Modularity
Personalized
SALSA*
Load Geometrics
Point in Polygon
Geom Overlay
Shapley Value
G
r
a
p
h
C
e
n
t
r
a
l
i
t
y
N
e
t
w
o
r
k
S
t
r
u
c
t
u
r
e
M
L
&
L
o
c
A
n
a
l
y
t
i
c
s
Statistics and Machine
Learning
Minhash
Naïve Bayes
PCA
Percentile
Random Forest
Single Decision
Tree
SVM
GLM
Histogram
K-Means
KNN
LASSO
Linear Regression
Logistic Regression*
Data Prep and ETL
Murmurhash
Outlier filter
Pack/Unpack
Pivot/Unpivot
Sampling
Sessionization
Antiselect
Apache Log Parser
E-Mail Parser
JSON Parser
XML Parser
Identity Matching
IPGEO
Multicase
Chinese Text
Segmentation
LDA
Levenshtein Dist
Naïve Bayes Text
NER
nGram
Sentiment
Extraction
Text Categorization
Path and Pattern
Analyses
Attribution
Basket Generator
cFilter
Frequent Paths
Path Generator,
Starter, Summarizer
nTree
Teradata Aster
nPath®
WSRecommender
Text and Sentiment
Attensity Functions Extraction
Text Chunker
Text Parser
Insights Visualizations
Dynamic Time
Warping
SAX
cFilterviz
SOURCE: http://assets.teradata.com/resourceCenter/downloads/WhitePapers/EB6844_Teradata_Aster_Discovery_Portfolio_Whitepaper.pdf

16. SQL-MR: Ease of SQL, Power of MapReduce
nPath: Identifying Top Pathing Occurrences (for any event of interest)
1. Select Name of Operator/Function
2. Select Data Sets for Input
3. Identify Pattern of Interest
4. Provide Pattern Definition
5. Define Output desired
SELECT click_path, count(*) as path_frequency
FROM nPath(
ON clicks
PARTITION BY user_id
ORDER BY timestamp
MODE( overlapping )
PATTERN(‘(RELEVANT|IGNORE)*.BUY’)
SYMBOLS(
page_type IN (‘help.asp’) AS IGNORE,
page_type NOT IN (‘help.asp’) AS RELEVANT,
page_type = ‘checkout’ as BUY)
RESULT( accum( page_id of RELEVANT) as
click_path )
) T
GROUP BY click_path
ORDER BY count(*) desc
LIMIT 10;
“Find the top ten paths that
lead to a purchase ignoring
help pages”

17. Simplifying Analytics with SQL-MR
Easier development and faster execution with single-pass analytics
SQL Query
• 29 lines of custom, multi-pass SQL
• Requires three multi-dimensional self-joins
SQL-MR Query
• 10 lines of standard SQL
• Extensible basket size
• Can call from SQL in-database
• Easier to code
• Faster
Hundreds of lines to do in java

18. Consume the Analytics Through Visualizations
• Unique visualizations
for Map Reduce and
Graph analytics
• Interactive visualization
capabilities on top of
Aster for business
discovery
• The ‘easier button’
Pre-Built Apps, Custom Visuals, BI Tools
• Tool to easily use and
manage Aster
visualizations

19. Customer Journey - Banking

20. Key Highlights
• Multi-Genre Aster analytics - SQL / SQL-MR / Statistical
• Analytical Functions
– Attribution
– nPath
– Naïve Bayes prediction
• Visualization
– Qlik Sense with SQL - MR
• Business Insights
• Iterative Discovery
• Ease of use for the Business User

21. Retail banking customer journey covers
important interactions over time
Customer Journey 

22. Multi-Channel Interactions
• Customers interact through multiple channels generating multi-structured data
Teller Withdrawal
ATM Deposit Teller Complaint
Online Transfer
Call Center Inquiry
ONLINE
CALL
CENTER
Email Complaint Cancel account
ATM
ATM ID,
Event, $$
TELLER
Teller ID,
Event
E-MAIL
Text Category
(Intent)
BRANCH
Branch ID, Mgr
ID, Event
BRANCH
Teller ID,
Event
Page Type,
Action
Event

23. Demo

24. Resources
Qlik Sense Download – Free Download Qlik Desktop
http://qlik.com/download
Branch - Qlik Open Source Collaboration Portal
http://branch.qlik.com
Qlik Aster Demo Portal - Demo site for Qlik Sense + Aster Integration
http://aster.qlik.com
Qlik Teradata Demo Portal - Demo site QlikView + Teradata Integration
http://teradata.qlik.com
Aster Express VM - No-charge Windows Download-http://
downloads.teradata.com/download/aster/aster-express
Aster Documentation – Instruction on running SQL MR Analytical
http://www.info.teradata.com/AsterData/eBrowseBy.cfm
Get Started Today !

25. Questions?
Please email John.Park@qlik.com
Please email Adam.london@teradata.com
Thank You