Teradata Aster: Big Data Discovery Made Easy

Big Data Discovery Made Easy
(well, easier)
Brad Elo – Vice President Teradata Aster

Confidential and proprietary. Copyright © 2012 Teradata Corporation.2
Teradata – The Clear Data Warehousing Leader
Leadership in Execution and Vision
Gartner Magic
Quadrant for Data
Warehouse DBMS,
2013
The Magic Quadrant is copyrighted 23 December 2008 by Gartner, Inc. and is reused with permission. The Magic Quadrant is a graphical representation of a
marketplace at and for a specific time period. It depicts Gartner's analysis of how certain vendors measure against criteria for that marketplace, as defined by
Gartner. Gartner does not endorse any vendor, product or service depicted in the Magic Quadrant, and does not advise technology users to select only those
vendors placed in the "Leaders" quadrant. The Magic Quadrant is intended solely as a research tool, and is not meant to be a specific guide to action. Gartner
disclaims all warranties, express or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
Ability to Execute
Completeness of Vision

Need for a Unified Data Architecture for New Insights
Enabling Any User for Any Data Type from Data Capture to Analysis
Discover and Explore
Reporting and Execution
in the Enterprise
Capture, Store and Refine
Audio/
Video
Images Docs Text
Web &
Social
Machine
Logs
CRM SCM ERP
Java, C/C++, Python, R, SAS, SQL, Excel, BI, Visualization

Big Data: From Transactions to Interactions
BIG DATA
WEB
Petabytes
CRM
Terabytes
Gigabytes
ERP
Exabytes
Increasing Data Variety and Complexity
User Generated
Content
Mobile Web
SMS/MMS
Sentiment
External
Demographics
HD Video
Speech to Text
Product/
Service Logs
Social Network
Business Data
Feeds
User Click Stream
Web Logs
Offer History A/B Testing
Dynamic Pricing
Affiliate Networks
Search Marketing
Behavioral
Targeting
Dynamic Funnels
Payment
Record Support Contacts
Customer TouchesPurchase
Detail
Purchase
Record
Offer Details
Segmentation
Behavioral Analytics

Shift from a Single Platform to an Ecosystem
“Big Data requirements are solved
by a range of platforms including
analytical databases, discovery
platforms, and NoSQL solutions
beyond Hadoop.”
“We will abandon the old models
based on the desire to
implement for high-value
analytic applications.”
“Logical” Data Warehouse
Source: “Big Data Comes of Age”. EMA and 9sight Consulting. Nov
2012.
1%
2%
2%
6%
8%
28%
26%
27%
Hybrid Data Ecosystem Nodes in Use
One Node
Two Nodes
Three Nodes
Four Nodes
Five Nodes
Six Nodes
Seven Nodes
Eight Nodes
Column-Store
DBMS
CEPContent
& XML
Complex
Data Types
Cloud
DBMS
Data in
HDFS
In-Memory
DBMS

AUDIO & VIDEO IMAGES TEXT WEB & SOCIAL MACHINE LOGS CRM SCM ERP
INTEGRATED
DATA
WAREHOUSE
UNIFIED DATA ARCHITECTURE
LANGUAGES MATH & STATS DATA MINING BUSINESS INTELLIGENCE APPLICATIONS
Engineers
Data Scientists
Business Analysts
Front-Line WorkersCustomers / PartnersQuants
Operational SystemsMarketing

• Single View of Your Business
• Cross-Functional Analysis
• Shared Source for Analytics
• Balance the Books
• Customer/Product Profitability
• Operational Applications
• CRM Execution
• Fast Time-to-Market For New Apps
• Mission Critical Service Levels
Integrated Data Warehouse
Requirements

DISCOVERY
PLATFORM
INTEGRATED
DATA
WAREHOUSE
Engineers
Data Scientists
Business Analysts

Requirements of a Discovery Platform
DATA SOURCES
Structured
Data
Multi-
Structured
Data
Non-
Relational
Data
DISCOVERY DISCOVERY TOOLS USERS
Discovery
Platform Data
Scientist
Business
Analyst
SQL
MapReduce
Statistical Functions
OLTP
DBMS’s
• Structured and
multi-structured
data
• Doesn’t require
extensive data
modeling
• Doesn’t balance the
books
• Data completeness
can be good enough
• No stringent SLAs
• Fraud patterns
• Customer behavior
• Digital marketing
optimization
• Supply chain and
supply line sensors

DISCOVERY
PLATFORM
INTEGRATED
DATA
WAREHOUSE
Engineers
Data Scientists
Business Analysts
CAPTURE | STORE | REFINE

• Land/source operational data
• History or long term storage
• Preprocess data
• Transformations
Big Data Management Requirements
Machine Generated
Social Media

DISCOVERY
PLATFORM
INTEGRATED
DATA
WAREHOUSE
Engineers
Data Scientists
Business Analysts
Big Data
Analytics
Big Data
Management

Confidential and proprietary. Copyright © 2012 Teradata Corporation.14 AUDIO & VIDEO IMAGES TEXT WEB & SOCIAL MACHINE LOGS CRM SCM ERP
DISCOVERY
PLATFORM
INTEGRATED
DATA WAREHOUSE
LANGUAGES MATH & STATS DATA MINING BUSINESS INTELLIGENCE APPLICATIONSVIEWPOINT SUPPORT
Engineers
Data Scientists
Business Analysts
Operational SystemsExecutives
TERADATA UNIFIED DATA ARCHITECTURE
Aster Connector for
Hadoop
Teradata Connector
for Hadoop
Aster Teradata
Connector
SQL-H
Aster Loader Teradata Loader
SQL-H

Teradata Unified Data Architecture™
Partners Support Many Layers of the UDA
Updated: April 24, 2013

Summary
World is Moving Towards Hybrid Architectures
- FAST
Teradata Provides the Most Complete
Unfiied Data Architecture – includes Data
Warehousing, Discovery, Hadoop & Spotfire
Discovery is Key Big Data Use Case –
Optimally Done with Teradata Aster, Spotfire &
Hadoop
1
2
3

Teradata Aster: Big Data Discovery Made Easy

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Teradata Aster: Big Data Discovery Made Easy