SlideShare a Scribd company logo
​Investor Presentation
​Second Quarter 2015
2
Note to Investors
• Certain non-GAAP financial information regarding operating results may
be discussed during this presentation. Reconciliations of the differences
between GAAP and non-GAAP measures are available on the Investor
page at www.teradata.com/investor.
• Remarks and responses associated with this presentation include
forward-looking statements that are based on current expectations and
assumptions. These forward-looking statements are subject to a number
of risks and uncertainties that could affect our future results and could
cause actual results to differ materially from those expressed in such
forward-looking statements.
• These risks and uncertainties are detailed in Teradata’s Registration
Statement on Form 10 and in our SEC reports, including, but not limited
to, our periodic and current reports on Forms 10-K, 10-Q, and 8K, as well
as the company’s annual report to shareholders.
3
Two Streamlined DivisionsThree Large & Growing Markets
Teradata Today
Aligned for Accelerating Growth
Data Warehouse
Big Data Analytics
Marketing
Applications
Data &
Analytics
Division
Marketing
Applications
Division
Shared Services:
Corp. Marketing, IT, Operations
Best-in-Class Consulting & Support Services
Everything Available On-Premises and/or Cloud
4
Gartner & Forrester – Teradata Leads In Analytics
The Forrester Wave™:
Enterprise Data
Warehousing Platforms,
Q4 2013
Gartner Magic Quadrant
for Data Warehouse and
Data Management
Solutions for Analytics
February 2015
INTEGRATED DISCOVERY PLATFORM
INTEGRATED DATA WAREHOUSE
DATA
PLATFORM
UNIFIED DATA ARCHITECTURE
Marketing
Executives
Operational
Systems
Frontline
Workers
Customers
Partners
Engineers
Data
Scientists
Business
Analysts
Math
and Stats
Data
Mining
Business
Intelligence
Applications
Languages
Marketing
USERS
ANALYTIC TOOLS &
APPS
Search
TERADATA ASTER DATABASE
TERADATA DATABASE
INTEGRATED
BIG DATA PLATFORM
TERADATA
PORTFOLIO FOR
HADOOP
REAL TIME PROCESSINGERP
SCM
CRM
Images
Audio
and Video
Machine
Logs
Text
Web and
Social
SOURCES
Marketing
Executives
Operational
Systems
Knowledge
Workers
Customers
Partners
Engineers
Data
Scientists
Business
Analysts
USERS
6
Teradata Analytical Ecosystem
1000 series
2000 series
500 series
6000 series
2000 series
6000 series
7
Teradata Workload-Specific Platforms
Data Mart
Appliance
Extreme Data
Appliance
Data
Warehouse
Appliance
Active
Enterprise
Data
Warehouse
Appliance
for Hadoop
Aster Big
Analytics
Appliance
600 Series 1000 Series 2000 Series 6000 Series
Scale Up to 8TB Up to 186PB Up to 1.6PB Up to 61PB Up to 10PB Up to 5PB
Workloads
Test /
Development
or Smaller
Data Marts
Analytical
Archive,
Deep Dive
Analytics
Strategic
Intelligence,
Decision
Support System,
Fast Scan
Strategic &
Operational
Intelligence,
Real Time
Update, Active
workloads
Appliance for
Storing, Capturing
and Refining Data.
Hortonworks HDP
1.1
Discovery Platform
for Big Data
Analytics with
embedded SQL
MapReduce for
new data types &
sources
8
Broadest, Most Flexible Hadoop Offerings in Market
Aster Big Analytics
Appliance
Appliance for Hadoop
Commodity Offering
with Dell
Software Only
Overview Premier Premier Commodity Commodity
Value Proposition
Big data analytics in an
integrated package
Enterprise-ready Hadoop
with single vendor support
Pre-designed, cost-
effective commodity
hardware with Teradata
software support
Flexible hardware
options with Teradata
software support
Value Add
 Single best analytics &
discovery platform
 SQL-MapReduce & 70+
analytics
 Integrated
hardware/software
 Software to simplify
operation of Hadoop
 Integrated
hardware/software that is
engineered, staged, &
delivered complete.
 Data staging & refining
 Software to simplify
operation of Hadoop
 Hardware staged,
delivered by Dell
 Teradata software
install & support
 Teradata software
install & support
Segment
Business Value Based IT
“Buy it”
Value Based IT
“Buy it”
Cost-Based IT
“Buy it, Build it”
Engineering IT
“Build it”
100% Open Source, Community-Driven Enterprise Apache Hadoop
9
Continuous update
and time-sensitive
queries become
important
OPERATIONALIZING
WHAT IS
happening now?
Event-based
triggering takes
hold
ACTIVATING
MAKE it happen!
Primarily batch and
some ad hoc
reports
Increase in
ad hoc analysis
ANALYZING
WHY
did it happen?
REPORTING
WHAT
happened?
Analytical
modeling
grows
PREDICTING
WHAT WILL
happen?
WorkloadSophistication
Scalability
Stage 1
Stage 2
Stage 3
Stage 4
Stage 5
Teradata’s Data Warehouse Evolution/Vision
10
Teradata’s Industry-Leading Technology
Technology Demands
• Extreme scalability
• Extreme performance
• Extreme availability
• Extreme data load and
access
Scalability Across Multiple Dimensions
Data Volume
(Raw, User Data)
Schema
Sophistication
Query
Freedom
Query
Complexity
Query
Concurrency
Mixed
Workload
Query Data Volume
Data
Freshness
Teradata can scale
simultaneously across
multiple dimensions.
Driven by business!
Competition scales one
dimension at the expense of
others.
Limited by technology!
Mission critical 7x24
11 © 2014 Teradata
Teradata Cloud
As a Service…..
Easy
Scale-up
Secure
&
Reliable
High
Performance
Workload
Management
Data
Warehouse Discovery
Data
Management
INTEGRATED DATA
WAREHOUSE
DATA
PLATFORM
DISCOVERY
PLATFORM
12
Teradata Integrated Marketing Cloud – Solutions
MARKETING PLANS
SPEND MANAGEMENT
WORKFLOW & COLLABORATION
ASSET MANAGEMENT
OFFER MANAGEMENT
MARKETING RESOURCE
MANAGEMENT
INBOUND & OUTBOUND
COMMUNICATIONS
REAL-TIME DECISIONING
DIGITAL DELIVERY
OPTIMIZATION
ACTIONABLE
ANALYTICS
OMNI-CHANNEL
MARKETING
EMAIL MARKETING
MOBILE MARKETING
SOCIAL MARKETING
WEB MARKETING
DIGITAL ANALYTICS
DIGITAL
MARKETING
MARKETING
ANALYTICS
BUSINESS INTELLIGENCE BIG DATA ANALYTICS PREDICTIVE ANALYTICS
Teradata Marketing Applications
13
Revenue Mix
Approximate percentages of product and consulting services revenue by industry
Financial Services 24% 29% 28% 28% 28% 30% 31% 31%
Communications 28% 28% 23% 24% 24% 21% 19% 19%
Retail 19% 16% 17% 16% 16% 16% 14% 14%
Manufacturing 9% 11% 10% 13% 12% 12% 13% 13%
Healthcare 5% 4% 8% 6% 7% 7% 8% 6%
Travel &
Transportation
6% 6% 6% 6% 5% 6% 6% 7%
Government 7% 5% 7% 7% 6% 6% 6% 7%
Other 2% 1% <1% <1% 2% 2% 3% 3%
Operating Segments
Marketing Applications
8% of total revenue
40% + of Teradata’s revenue is from
recurring revenue sources.
Data & Analytics
92% of total
revenue
Products (SW / HW) $1,227M 45%
Consulting Services 817M 30%
Maintenance Services 688M 25%
Total Revenue $2,732M
Revenue by Type 2014 % of Total
Industry Vertical 2007 2008 2009 2010 2011 2012 2013 2014
14
Strong Balance Sheet & Cash Flow
Cash and Cash
Equivalents $270 $402 $661 $883 $772 $729 $695 $834 $881
Working Capital $301 $475 $609 $837 $717 $728 $787 $577 $741
Total Assets $1,294 $1,430 $1,569 $1,883 $2,616 $3,066 $3,096 $3,132 $3,103
Debt 0 0 0 0 $301 $289 $274 $468 $600
Total Deferred Revenue $246 $283 $280 $290 $363 $405 $415 $388 $508
Total Shareholders’ Equity $631 $777 $910 $1,189 $1,494 $1,779 $1,857 $1,707 $1,444
Net Income $200 $250 $254 $301 $353 $419 $377 $367
Cash from Operations $387 $440 $455 $413 $513 $575 $510 $680
Free Cash Flow $292 $369 $367 $330 $403 $427 $372 $551
Balance Sheet 2007 2008 2009 2010 2011 2012 2013 2014 3/31/2015
($ in millions)
Cash Flow 2007 2008 2009 2010 2011 2012 2013 2014
($ in millions)

More Related Content

What's hot

Sprint fiscal 1 q15 earnings slides final
Sprint   fiscal 1 q15 earnings slides finalSprint   fiscal 1 q15 earnings slides final
Sprint fiscal 1 q15 earnings slides final
sprint1
 
Big Data for Product Managers
Big Data for Product ManagersBig Data for Product Managers
Big Data for Product Managers
Pentaho
 
Predictive Data Analytics and Artificial Intelligence by 40°
Predictive Data Analytics and Artificial Intelligence by 40°Predictive Data Analytics and Artificial Intelligence by 40°
Predictive Data Analytics and Artificial Intelligence by 40°
40° Labor für Innovation
 
Data Mashups for Analytics
Data Mashups for AnalyticsData Mashups for Analytics
Data Mashups for Analytics
Katharine Bierce
 
A New Day for Oracle Analytics
A New Day for Oracle AnalyticsA New Day for Oracle Analytics
A New Day for Oracle Analytics
Rich Clayton
 
Big Data Predictions for 2015
Big Data Predictions for 2015 Big Data Predictions for 2015
Big Data Predictions for 2015
Pentaho
 
Up Your Analytics Game with Pentaho and Vertica
Up Your Analytics Game with Pentaho and Vertica Up Your Analytics Game with Pentaho and Vertica
Up Your Analytics Game with Pentaho and Vertica
Pentaho
 
Accretive Health - Physician Advisory Services - Medical Coding
Accretive Health - Physician Advisory Services - Medical CodingAccretive Health - Physician Advisory Services - Medical Coding
Accretive Health - Physician Advisory Services - Medical Coding
AccretiveHealth
 
Why our customers choose teradata.
Why our customers choose teradata.Why our customers choose teradata.
Why our customers choose teradata.
Adam Swaney
 
Alteryx investor presentation
Alteryx investor presentationAlteryx investor presentation
Alteryx investor presentation
alteryxinvestor
 
Open Analytics 2014 - Pedro Alves - Innovation though Open Source
Open Analytics 2014 - Pedro Alves - Innovation though Open SourceOpen Analytics 2014 - Pedro Alves - Innovation though Open Source
Open Analytics 2014 - Pedro Alves - Innovation though Open Source
OpenAnalytics Spain
 
Big Data Integration Webinar: Reducing Implementation Efforts of Hadoop, NoSQ...
Big Data Integration Webinar: Reducing Implementation Efforts of Hadoop, NoSQ...Big Data Integration Webinar: Reducing Implementation Efforts of Hadoop, NoSQ...
Big Data Integration Webinar: Reducing Implementation Efforts of Hadoop, NoSQ...
Pentaho
 
Exclusive Verizon Employee Webinar: Getting More From Your CDR Data
Exclusive Verizon Employee Webinar: Getting More From Your CDR DataExclusive Verizon Employee Webinar: Getting More From Your CDR Data
Exclusive Verizon Employee Webinar: Getting More From Your CDR Data
Pentaho
 
Alteryx q218 investor deck ir original format-final for website
Alteryx q218 investor deck   ir original format-final for websiteAlteryx q218 investor deck   ir original format-final for website
Alteryx q218 investor deck ir original format-final for website
alteryxinvestor
 
Top ten data and analysis technology trends in 2021
Top ten data and analysis technology trends in 2021Top ten data and analysis technology trends in 2021
Top ten data and analysis technology trends in 2021
Ruchi Jain
 
Data Integration and Advanced Analytics for MongoDB: Blend, Enrich and Analyz...
Data Integration and Advanced Analytics for MongoDB: Blend, Enrich and Analyz...Data Integration and Advanced Analytics for MongoDB: Blend, Enrich and Analyz...
Data Integration and Advanced Analytics for MongoDB: Blend, Enrich and Analyz...
MongoDB
 
Pentaho Analytics for MongoDB - presentation from MongoDB World 2014
Pentaho Analytics for MongoDB - presentation from MongoDB World 2014Pentaho Analytics for MongoDB - presentation from MongoDB World 2014
Pentaho Analytics for MongoDB - presentation from MongoDB World 2014
Pentaho
 
Cox Automotive: data sells cars
Cox Automotive: data sells carsCox Automotive: data sells cars
Cox Automotive: data sells cars
Cloudera, Inc.
 
Alteryx q1'18 investor deck ir
Alteryx q1'18 investor deck   irAlteryx q1'18 investor deck   ir
Alteryx q1'18 investor deck ir
alteryxinvestor
 
Alteryx investor presentation 052017 final
Alteryx investor presentation 052017 finalAlteryx investor presentation 052017 final
Alteryx investor presentation 052017 final
alteryxinvestor
 

What's hot (20)

Sprint fiscal 1 q15 earnings slides final
Sprint   fiscal 1 q15 earnings slides finalSprint   fiscal 1 q15 earnings slides final
Sprint fiscal 1 q15 earnings slides final
 
Big Data for Product Managers
Big Data for Product ManagersBig Data for Product Managers
Big Data for Product Managers
 
Predictive Data Analytics and Artificial Intelligence by 40°
Predictive Data Analytics and Artificial Intelligence by 40°Predictive Data Analytics and Artificial Intelligence by 40°
Predictive Data Analytics and Artificial Intelligence by 40°
 
Data Mashups for Analytics
Data Mashups for AnalyticsData Mashups for Analytics
Data Mashups for Analytics
 
A New Day for Oracle Analytics
A New Day for Oracle AnalyticsA New Day for Oracle Analytics
A New Day for Oracle Analytics
 
Big Data Predictions for 2015
Big Data Predictions for 2015 Big Data Predictions for 2015
Big Data Predictions for 2015
 
Up Your Analytics Game with Pentaho and Vertica
Up Your Analytics Game with Pentaho and Vertica Up Your Analytics Game with Pentaho and Vertica
Up Your Analytics Game with Pentaho and Vertica
 
Accretive Health - Physician Advisory Services - Medical Coding
Accretive Health - Physician Advisory Services - Medical CodingAccretive Health - Physician Advisory Services - Medical Coding
Accretive Health - Physician Advisory Services - Medical Coding
 
Why our customers choose teradata.
Why our customers choose teradata.Why our customers choose teradata.
Why our customers choose teradata.
 
Alteryx investor presentation
Alteryx investor presentationAlteryx investor presentation
Alteryx investor presentation
 
Open Analytics 2014 - Pedro Alves - Innovation though Open Source
Open Analytics 2014 - Pedro Alves - Innovation though Open SourceOpen Analytics 2014 - Pedro Alves - Innovation though Open Source
Open Analytics 2014 - Pedro Alves - Innovation though Open Source
 
Big Data Integration Webinar: Reducing Implementation Efforts of Hadoop, NoSQ...
Big Data Integration Webinar: Reducing Implementation Efforts of Hadoop, NoSQ...Big Data Integration Webinar: Reducing Implementation Efforts of Hadoop, NoSQ...
Big Data Integration Webinar: Reducing Implementation Efforts of Hadoop, NoSQ...
 
Exclusive Verizon Employee Webinar: Getting More From Your CDR Data
Exclusive Verizon Employee Webinar: Getting More From Your CDR DataExclusive Verizon Employee Webinar: Getting More From Your CDR Data
Exclusive Verizon Employee Webinar: Getting More From Your CDR Data
 
Alteryx q218 investor deck ir original format-final for website
Alteryx q218 investor deck   ir original format-final for websiteAlteryx q218 investor deck   ir original format-final for website
Alteryx q218 investor deck ir original format-final for website
 
Top ten data and analysis technology trends in 2021
Top ten data and analysis technology trends in 2021Top ten data and analysis technology trends in 2021
Top ten data and analysis technology trends in 2021
 
Data Integration and Advanced Analytics for MongoDB: Blend, Enrich and Analyz...
Data Integration and Advanced Analytics for MongoDB: Blend, Enrich and Analyz...Data Integration and Advanced Analytics for MongoDB: Blend, Enrich and Analyz...
Data Integration and Advanced Analytics for MongoDB: Blend, Enrich and Analyz...
 
Pentaho Analytics for MongoDB - presentation from MongoDB World 2014
Pentaho Analytics for MongoDB - presentation from MongoDB World 2014Pentaho Analytics for MongoDB - presentation from MongoDB World 2014
Pentaho Analytics for MongoDB - presentation from MongoDB World 2014
 
Cox Automotive: data sells cars
Cox Automotive: data sells carsCox Automotive: data sells cars
Cox Automotive: data sells cars
 
Alteryx q1'18 investor deck ir
Alteryx q1'18 investor deck   irAlteryx q1'18 investor deck   ir
Alteryx q1'18 investor deck ir
 
Alteryx investor presentation 052017 final
Alteryx investor presentation 052017 finalAlteryx investor presentation 052017 final
Alteryx investor presentation 052017 final
 

Similar to Q2 2015 investor presentation

Q4 2015 investor presentation web copy 11 5 2015 435pm
Q4 2015 investor presentation web copy 11 5 2015 435pmQ4 2015 investor presentation web copy 11 5 2015 435pm
Q4 2015 investor presentation web copy 11 5 2015 435pm
teradata2014
 
Q1 2016 investor presentation 2 5 2016 web copy
Q1 2016 investor presentation 2 5 2016 web copyQ1 2016 investor presentation 2 5 2016 web copy
Q1 2016 investor presentation 2 5 2016 web copy
teradata2014
 
Q2 2016 investor presentation 5 6 2016 final
Q2 2016 investor presentation 5 6 2016 finalQ2 2016 investor presentation 5 6 2016 final
Q2 2016 investor presentation 5 6 2016 final
teradata2014
 
Overview of Operations
Overview of OperationsOverview of Operations
Overview of Operations
Glenture
 
It budget
It budgetIt budget
It budget
sucesu68
 
2015 02 12 talend hortonworks webinar challenges to hadoop adoption
2015 02 12 talend hortonworks webinar challenges to hadoop adoption2015 02 12 talend hortonworks webinar challenges to hadoop adoption
2015 02 12 talend hortonworks webinar challenges to hadoop adoption
Hortonworks
 
NVIDIA-Investor-Presentation-Oct-2022-(1).pptx
NVIDIA-Investor-Presentation-Oct-2022-(1).pptxNVIDIA-Investor-Presentation-Oct-2022-(1).pptx
NVIDIA-Investor-Presentation-Oct-2022-(1).pptx
PrajwalKumar921407
 
Monetize Data with Embedded Analytics
Monetize Data with Embedded AnalyticsMonetize Data with Embedded Analytics
Monetize Data with Embedded Analytics
GoodData
 
Software_AG_Investor_Fact_Book _December 2015_tcm16-137105
Software_AG_Investor_Fact_Book _December 2015_tcm16-137105Software_AG_Investor_Fact_Book _December 2015_tcm16-137105
Software_AG_Investor_Fact_Book _December 2015_tcm16-137105
Bapi Reddy Medapati
 
Capturing big value in big data
Capturing big value in big data Capturing big value in big data
Capturing big value in big data
BSP Media Group
 
Stay Ahead in Telecom Business
Stay Ahead in Telecom BusinessStay Ahead in Telecom Business
Stay Ahead in Telecom Business
Dhiren Gala
 
Navigating the Workday Analytics and Reporting Ecosystem
Navigating the Workday Analytics and Reporting EcosystemNavigating the Workday Analytics and Reporting Ecosystem
Navigating the Workday Analytics and Reporting Ecosystem
Workday, Inc.
 
Top 20 Big Data Companies 2014
Top 20 Big Data Companies 2014Top 20 Big Data Companies 2014
Top 20 Big Data Companies 2014
Visiongain
 
Cardtronics Future Ready with Oracle EPM Cloud
Cardtronics Future Ready with Oracle EPM CloudCardtronics Future Ready with Oracle EPM Cloud
Cardtronics Future Ready with Oracle EPM Cloud
Perficient, Inc.
 
SAP-ERP By Satya Kiran
SAP-ERP By Satya KiranSAP-ERP By Satya Kiran
SAP-ERP By Satya Kiran
Satya Kiran
 
Powering the Intelligent Edge: HPE's Strategy and Direction for IoT & Big Data
Powering the Intelligent Edge: HPE's Strategy and Direction for IoT & Big DataPowering the Intelligent Edge: HPE's Strategy and Direction for IoT & Big Data
Powering the Intelligent Edge: HPE's Strategy and Direction for IoT & Big Data
DataWorks Summit
 
Tableau reseller partner in Albania Bilytica Best business Intelligence compa...
Tableau reseller partner in Albania Bilytica Best business Intelligence compa...Tableau reseller partner in Albania Bilytica Best business Intelligence compa...
Tableau reseller partner in Albania Bilytica Best business Intelligence compa...
Carie John
 
Tableau reseller partner in Bahrain Bilytica Best business Intelligence Compa...
Tableau reseller partner in Bahrain Bilytica Best business Intelligence Compa...Tableau reseller partner in Bahrain Bilytica Best business Intelligence Compa...
Tableau reseller partner in Bahrain Bilytica Best business Intelligence Compa...
Carie John
 
Tableau reseller partner in Algeria Bilytica Best business Intelligence compa...
Tableau reseller partner in Algeria Bilytica Best business Intelligence compa...Tableau reseller partner in Algeria Bilytica Best business Intelligence compa...
Tableau reseller partner in Algeria Bilytica Best business Intelligence compa...
Carie John
 
Tableau reseller partner in Afghanistan Bilytica Best business Intelligence c...
Tableau reseller partner in Afghanistan Bilytica Best business Intelligence c...Tableau reseller partner in Afghanistan Bilytica Best business Intelligence c...
Tableau reseller partner in Afghanistan Bilytica Best business Intelligence c...
Carie John
 

Similar to Q2 2015 investor presentation (20)

Q4 2015 investor presentation web copy 11 5 2015 435pm
Q4 2015 investor presentation web copy 11 5 2015 435pmQ4 2015 investor presentation web copy 11 5 2015 435pm
Q4 2015 investor presentation web copy 11 5 2015 435pm
 
Q1 2016 investor presentation 2 5 2016 web copy
Q1 2016 investor presentation 2 5 2016 web copyQ1 2016 investor presentation 2 5 2016 web copy
Q1 2016 investor presentation 2 5 2016 web copy
 
Q2 2016 investor presentation 5 6 2016 final
Q2 2016 investor presentation 5 6 2016 finalQ2 2016 investor presentation 5 6 2016 final
Q2 2016 investor presentation 5 6 2016 final
 
Overview of Operations
Overview of OperationsOverview of Operations
Overview of Operations
 
It budget
It budgetIt budget
It budget
 
2015 02 12 talend hortonworks webinar challenges to hadoop adoption
2015 02 12 talend hortonworks webinar challenges to hadoop adoption2015 02 12 talend hortonworks webinar challenges to hadoop adoption
2015 02 12 talend hortonworks webinar challenges to hadoop adoption
 
NVIDIA-Investor-Presentation-Oct-2022-(1).pptx
NVIDIA-Investor-Presentation-Oct-2022-(1).pptxNVIDIA-Investor-Presentation-Oct-2022-(1).pptx
NVIDIA-Investor-Presentation-Oct-2022-(1).pptx
 
Monetize Data with Embedded Analytics
Monetize Data with Embedded AnalyticsMonetize Data with Embedded Analytics
Monetize Data with Embedded Analytics
 
Software_AG_Investor_Fact_Book _December 2015_tcm16-137105
Software_AG_Investor_Fact_Book _December 2015_tcm16-137105Software_AG_Investor_Fact_Book _December 2015_tcm16-137105
Software_AG_Investor_Fact_Book _December 2015_tcm16-137105
 
Capturing big value in big data
Capturing big value in big data Capturing big value in big data
Capturing big value in big data
 
Stay Ahead in Telecom Business
Stay Ahead in Telecom BusinessStay Ahead in Telecom Business
Stay Ahead in Telecom Business
 
Navigating the Workday Analytics and Reporting Ecosystem
Navigating the Workday Analytics and Reporting EcosystemNavigating the Workday Analytics and Reporting Ecosystem
Navigating the Workday Analytics and Reporting Ecosystem
 
Top 20 Big Data Companies 2014
Top 20 Big Data Companies 2014Top 20 Big Data Companies 2014
Top 20 Big Data Companies 2014
 
Cardtronics Future Ready with Oracle EPM Cloud
Cardtronics Future Ready with Oracle EPM CloudCardtronics Future Ready with Oracle EPM Cloud
Cardtronics Future Ready with Oracle EPM Cloud
 
SAP-ERP By Satya Kiran
SAP-ERP By Satya KiranSAP-ERP By Satya Kiran
SAP-ERP By Satya Kiran
 
Powering the Intelligent Edge: HPE's Strategy and Direction for IoT & Big Data
Powering the Intelligent Edge: HPE's Strategy and Direction for IoT & Big DataPowering the Intelligent Edge: HPE's Strategy and Direction for IoT & Big Data
Powering the Intelligent Edge: HPE's Strategy and Direction for IoT & Big Data
 
Tableau reseller partner in Albania Bilytica Best business Intelligence compa...
Tableau reseller partner in Albania Bilytica Best business Intelligence compa...Tableau reseller partner in Albania Bilytica Best business Intelligence compa...
Tableau reseller partner in Albania Bilytica Best business Intelligence compa...
 
Tableau reseller partner in Bahrain Bilytica Best business Intelligence Compa...
Tableau reseller partner in Bahrain Bilytica Best business Intelligence Compa...Tableau reseller partner in Bahrain Bilytica Best business Intelligence Compa...
Tableau reseller partner in Bahrain Bilytica Best business Intelligence Compa...
 
Tableau reseller partner in Algeria Bilytica Best business Intelligence compa...
Tableau reseller partner in Algeria Bilytica Best business Intelligence compa...Tableau reseller partner in Algeria Bilytica Best business Intelligence compa...
Tableau reseller partner in Algeria Bilytica Best business Intelligence compa...
 
Tableau reseller partner in Afghanistan Bilytica Best business Intelligence c...
Tableau reseller partner in Afghanistan Bilytica Best business Intelligence c...Tableau reseller partner in Afghanistan Bilytica Best business Intelligence c...
Tableau reseller partner in Afghanistan Bilytica Best business Intelligence c...
 

Recently uploaded

Understanding-the-E-Way-Bill-A-Digital-Transformation-in-Logistics.pptx
Understanding-the-E-Way-Bill-A-Digital-Transformation-in-Logistics.pptxUnderstanding-the-E-Way-Bill-A-Digital-Transformation-in-Logistics.pptx
Understanding-the-E-Way-Bill-A-Digital-Transformation-in-Logistics.pptx
cosmo-soil
 
Collective Mining | Corporate Presentation - June 2024
Collective Mining | Corporate Presentation - June 2024Collective Mining | Corporate Presentation - June 2024
Collective Mining | Corporate Presentation - June 2024
CollectiveMining1
 
一比一原版(UW毕业证)华盛顿大学毕业证成绩单专业办理
一比一原版(UW毕业证)华盛顿大学毕业证成绩单专业办理一比一原版(UW毕业证)华盛顿大学毕业证成绩单专业办理
一比一原版(UW毕业证)华盛顿大学毕业证成绩单专业办理
ybout
 
MUTUAL FUNDS (ICICI Prudential Mutual Fund) BY JAMES RODRIGUES
MUTUAL FUNDS (ICICI Prudential Mutual Fund) BY JAMES RODRIGUESMUTUAL FUNDS (ICICI Prudential Mutual Fund) BY JAMES RODRIGUES
MUTUAL FUNDS (ICICI Prudential Mutual Fund) BY JAMES RODRIGUES
WilliamRodrigues148
 
Cleades robinson:The Diplomat is Blue
Cleades robinson:The Diplomat is BlueCleades robinson:The Diplomat is Blue
Cleades robinson:The Diplomat is Blue
Cleades Robinson
 
2024-deutsche-bank-global-consumer-conference.pdf
2024-deutsche-bank-global-consumer-conference.pdf2024-deutsche-bank-global-consumer-conference.pdf
2024-deutsche-bank-global-consumer-conference.pdf
Sysco_Investors
 
Mandalay Resouces June 2024 Investor Relations PPT
Mandalay Resouces June 2024 Investor Relations PPTMandalay Resouces June 2024 Investor Relations PPT
Mandalay Resouces June 2024 Investor Relations PPT
MandalayResources
 
Osisko Development - Investor Presentation - June 24
Osisko Development - Investor Presentation - June 24Osisko Development - Investor Presentation - June 24
Osisko Development - Investor Presentation - June 24
Philip Rabenok
 
ppt-namibia-worldeconomy-standardbank.ppt
ppt-namibia-worldeconomy-standardbank.pptppt-namibia-worldeconomy-standardbank.ppt
ppt-namibia-worldeconomy-standardbank.ppt
TestOrg1
 
ZKsync airdrop of 3.6 billion ZK tokens is scheduled by ZKsync for next week.pdf
ZKsync airdrop of 3.6 billion ZK tokens is scheduled by ZKsync for next week.pdfZKsync airdrop of 3.6 billion ZK tokens is scheduled by ZKsync for next week.pdf
ZKsync airdrop of 3.6 billion ZK tokens is scheduled by ZKsync for next week.pdf
SOFTTECHHUB
 
AGM Presentation Probe June 11 Final.pdf
AGM Presentation Probe June 11 Final.pdfAGM Presentation Probe June 11 Final.pdf
AGM Presentation Probe June 11 Final.pdf
Probe Gold
 
Cyberagent_For New Investors_EN_240424.pdf
Cyberagent_For New Investors_EN_240424.pdfCyberagent_For New Investors_EN_240424.pdf
Cyberagent_For New Investors_EN_240424.pdf
CyberAgent, Inc.
 
Methanex Investor Presentation - April 2024
Methanex Investor Presentation - April 2024Methanex Investor Presentation - April 2024
Methanex Investor Presentation - April 2024
Methanex Corporation
 
快速办理(CUBoulder毕业证书)科罗拉多大学博尔德分校毕业证录取通知书一模一样
快速办理(CUBoulder毕业证书)科罗拉多大学博尔德分校毕业证录取通知书一模一样快速办理(CUBoulder毕业证书)科罗拉多大学博尔德分校毕业证录取通知书一模一样
快速办理(CUBoulder毕业证书)科罗拉多大学博尔德分校毕业证录取通知书一模一样
f3wjr2q2
 

Recently uploaded (14)

Understanding-the-E-Way-Bill-A-Digital-Transformation-in-Logistics.pptx
Understanding-the-E-Way-Bill-A-Digital-Transformation-in-Logistics.pptxUnderstanding-the-E-Way-Bill-A-Digital-Transformation-in-Logistics.pptx
Understanding-the-E-Way-Bill-A-Digital-Transformation-in-Logistics.pptx
 
Collective Mining | Corporate Presentation - June 2024
Collective Mining | Corporate Presentation - June 2024Collective Mining | Corporate Presentation - June 2024
Collective Mining | Corporate Presentation - June 2024
 
一比一原版(UW毕业证)华盛顿大学毕业证成绩单专业办理
一比一原版(UW毕业证)华盛顿大学毕业证成绩单专业办理一比一原版(UW毕业证)华盛顿大学毕业证成绩单专业办理
一比一原版(UW毕业证)华盛顿大学毕业证成绩单专业办理
 
MUTUAL FUNDS (ICICI Prudential Mutual Fund) BY JAMES RODRIGUES
MUTUAL FUNDS (ICICI Prudential Mutual Fund) BY JAMES RODRIGUESMUTUAL FUNDS (ICICI Prudential Mutual Fund) BY JAMES RODRIGUES
MUTUAL FUNDS (ICICI Prudential Mutual Fund) BY JAMES RODRIGUES
 
Cleades robinson:The Diplomat is Blue
Cleades robinson:The Diplomat is BlueCleades robinson:The Diplomat is Blue
Cleades robinson:The Diplomat is Blue
 
2024-deutsche-bank-global-consumer-conference.pdf
2024-deutsche-bank-global-consumer-conference.pdf2024-deutsche-bank-global-consumer-conference.pdf
2024-deutsche-bank-global-consumer-conference.pdf
 
Mandalay Resouces June 2024 Investor Relations PPT
Mandalay Resouces June 2024 Investor Relations PPTMandalay Resouces June 2024 Investor Relations PPT
Mandalay Resouces June 2024 Investor Relations PPT
 
Osisko Development - Investor Presentation - June 24
Osisko Development - Investor Presentation - June 24Osisko Development - Investor Presentation - June 24
Osisko Development - Investor Presentation - June 24
 
ppt-namibia-worldeconomy-standardbank.ppt
ppt-namibia-worldeconomy-standardbank.pptppt-namibia-worldeconomy-standardbank.ppt
ppt-namibia-worldeconomy-standardbank.ppt
 
ZKsync airdrop of 3.6 billion ZK tokens is scheduled by ZKsync for next week.pdf
ZKsync airdrop of 3.6 billion ZK tokens is scheduled by ZKsync for next week.pdfZKsync airdrop of 3.6 billion ZK tokens is scheduled by ZKsync for next week.pdf
ZKsync airdrop of 3.6 billion ZK tokens is scheduled by ZKsync for next week.pdf
 
AGM Presentation Probe June 11 Final.pdf
AGM Presentation Probe June 11 Final.pdfAGM Presentation Probe June 11 Final.pdf
AGM Presentation Probe June 11 Final.pdf
 
Cyberagent_For New Investors_EN_240424.pdf
Cyberagent_For New Investors_EN_240424.pdfCyberagent_For New Investors_EN_240424.pdf
Cyberagent_For New Investors_EN_240424.pdf
 
Methanex Investor Presentation - April 2024
Methanex Investor Presentation - April 2024Methanex Investor Presentation - April 2024
Methanex Investor Presentation - April 2024
 
快速办理(CUBoulder毕业证书)科罗拉多大学博尔德分校毕业证录取通知书一模一样
快速办理(CUBoulder毕业证书)科罗拉多大学博尔德分校毕业证录取通知书一模一样快速办理(CUBoulder毕业证书)科罗拉多大学博尔德分校毕业证录取通知书一模一样
快速办理(CUBoulder毕业证书)科罗拉多大学博尔德分校毕业证录取通知书一模一样
 

Q2 2015 investor presentation

  • 2. 2 Note to Investors • Certain non-GAAP financial information regarding operating results may be discussed during this presentation. Reconciliations of the differences between GAAP and non-GAAP measures are available on the Investor page at www.teradata.com/investor. • Remarks and responses associated with this presentation include forward-looking statements that are based on current expectations and assumptions. These forward-looking statements are subject to a number of risks and uncertainties that could affect our future results and could cause actual results to differ materially from those expressed in such forward-looking statements. • These risks and uncertainties are detailed in Teradata’s Registration Statement on Form 10 and in our SEC reports, including, but not limited to, our periodic and current reports on Forms 10-K, 10-Q, and 8K, as well as the company’s annual report to shareholders.
  • 3. 3 Two Streamlined DivisionsThree Large & Growing Markets Teradata Today Aligned for Accelerating Growth Data Warehouse Big Data Analytics Marketing Applications Data & Analytics Division Marketing Applications Division Shared Services: Corp. Marketing, IT, Operations Best-in-Class Consulting & Support Services Everything Available On-Premises and/or Cloud
  • 4. 4 Gartner & Forrester – Teradata Leads In Analytics The Forrester Wave™: Enterprise Data Warehousing Platforms, Q4 2013 Gartner Magic Quadrant for Data Warehouse and Data Management Solutions for Analytics February 2015
  • 5. INTEGRATED DISCOVERY PLATFORM INTEGRATED DATA WAREHOUSE DATA PLATFORM UNIFIED DATA ARCHITECTURE Marketing Executives Operational Systems Frontline Workers Customers Partners Engineers Data Scientists Business Analysts Math and Stats Data Mining Business Intelligence Applications Languages Marketing USERS ANALYTIC TOOLS & APPS Search TERADATA ASTER DATABASE TERADATA DATABASE INTEGRATED BIG DATA PLATFORM TERADATA PORTFOLIO FOR HADOOP REAL TIME PROCESSINGERP SCM CRM Images Audio and Video Machine Logs Text Web and Social SOURCES Marketing Executives Operational Systems Knowledge Workers Customers Partners Engineers Data Scientists Business Analysts USERS
  • 6. 6 Teradata Analytical Ecosystem 1000 series 2000 series 500 series 6000 series 2000 series 6000 series
  • 7. 7 Teradata Workload-Specific Platforms Data Mart Appliance Extreme Data Appliance Data Warehouse Appliance Active Enterprise Data Warehouse Appliance for Hadoop Aster Big Analytics Appliance 600 Series 1000 Series 2000 Series 6000 Series Scale Up to 8TB Up to 186PB Up to 1.6PB Up to 61PB Up to 10PB Up to 5PB Workloads Test / Development or Smaller Data Marts Analytical Archive, Deep Dive Analytics Strategic Intelligence, Decision Support System, Fast Scan Strategic & Operational Intelligence, Real Time Update, Active workloads Appliance for Storing, Capturing and Refining Data. Hortonworks HDP 1.1 Discovery Platform for Big Data Analytics with embedded SQL MapReduce for new data types & sources
  • 8. 8 Broadest, Most Flexible Hadoop Offerings in Market Aster Big Analytics Appliance Appliance for Hadoop Commodity Offering with Dell Software Only Overview Premier Premier Commodity Commodity Value Proposition Big data analytics in an integrated package Enterprise-ready Hadoop with single vendor support Pre-designed, cost- effective commodity hardware with Teradata software support Flexible hardware options with Teradata software support Value Add  Single best analytics & discovery platform  SQL-MapReduce & 70+ analytics  Integrated hardware/software  Software to simplify operation of Hadoop  Integrated hardware/software that is engineered, staged, & delivered complete.  Data staging & refining  Software to simplify operation of Hadoop  Hardware staged, delivered by Dell  Teradata software install & support  Teradata software install & support Segment Business Value Based IT “Buy it” Value Based IT “Buy it” Cost-Based IT “Buy it, Build it” Engineering IT “Build it” 100% Open Source, Community-Driven Enterprise Apache Hadoop
  • 9. 9 Continuous update and time-sensitive queries become important OPERATIONALIZING WHAT IS happening now? Event-based triggering takes hold ACTIVATING MAKE it happen! Primarily batch and some ad hoc reports Increase in ad hoc analysis ANALYZING WHY did it happen? REPORTING WHAT happened? Analytical modeling grows PREDICTING WHAT WILL happen? WorkloadSophistication Scalability Stage 1 Stage 2 Stage 3 Stage 4 Stage 5 Teradata’s Data Warehouse Evolution/Vision
  • 10. 10 Teradata’s Industry-Leading Technology Technology Demands • Extreme scalability • Extreme performance • Extreme availability • Extreme data load and access Scalability Across Multiple Dimensions Data Volume (Raw, User Data) Schema Sophistication Query Freedom Query Complexity Query Concurrency Mixed Workload Query Data Volume Data Freshness Teradata can scale simultaneously across multiple dimensions. Driven by business! Competition scales one dimension at the expense of others. Limited by technology! Mission critical 7x24
  • 11. 11 © 2014 Teradata Teradata Cloud As a Service….. Easy Scale-up Secure & Reliable High Performance Workload Management Data Warehouse Discovery Data Management INTEGRATED DATA WAREHOUSE DATA PLATFORM DISCOVERY PLATFORM
  • 12. 12 Teradata Integrated Marketing Cloud – Solutions MARKETING PLANS SPEND MANAGEMENT WORKFLOW & COLLABORATION ASSET MANAGEMENT OFFER MANAGEMENT MARKETING RESOURCE MANAGEMENT INBOUND & OUTBOUND COMMUNICATIONS REAL-TIME DECISIONING DIGITAL DELIVERY OPTIMIZATION ACTIONABLE ANALYTICS OMNI-CHANNEL MARKETING EMAIL MARKETING MOBILE MARKETING SOCIAL MARKETING WEB MARKETING DIGITAL ANALYTICS DIGITAL MARKETING MARKETING ANALYTICS BUSINESS INTELLIGENCE BIG DATA ANALYTICS PREDICTIVE ANALYTICS Teradata Marketing Applications
  • 13. 13 Revenue Mix Approximate percentages of product and consulting services revenue by industry Financial Services 24% 29% 28% 28% 28% 30% 31% 31% Communications 28% 28% 23% 24% 24% 21% 19% 19% Retail 19% 16% 17% 16% 16% 16% 14% 14% Manufacturing 9% 11% 10% 13% 12% 12% 13% 13% Healthcare 5% 4% 8% 6% 7% 7% 8% 6% Travel & Transportation 6% 6% 6% 6% 5% 6% 6% 7% Government 7% 5% 7% 7% 6% 6% 6% 7% Other 2% 1% <1% <1% 2% 2% 3% 3% Operating Segments Marketing Applications 8% of total revenue 40% + of Teradata’s revenue is from recurring revenue sources. Data & Analytics 92% of total revenue Products (SW / HW) $1,227M 45% Consulting Services 817M 30% Maintenance Services 688M 25% Total Revenue $2,732M Revenue by Type 2014 % of Total Industry Vertical 2007 2008 2009 2010 2011 2012 2013 2014
  • 14. 14 Strong Balance Sheet & Cash Flow Cash and Cash Equivalents $270 $402 $661 $883 $772 $729 $695 $834 $881 Working Capital $301 $475 $609 $837 $717 $728 $787 $577 $741 Total Assets $1,294 $1,430 $1,569 $1,883 $2,616 $3,066 $3,096 $3,132 $3,103 Debt 0 0 0 0 $301 $289 $274 $468 $600 Total Deferred Revenue $246 $283 $280 $290 $363 $405 $415 $388 $508 Total Shareholders’ Equity $631 $777 $910 $1,189 $1,494 $1,779 $1,857 $1,707 $1,444 Net Income $200 $250 $254 $301 $353 $419 $377 $367 Cash from Operations $387 $440 $455 $413 $513 $575 $510 $680 Free Cash Flow $292 $369 $367 $330 $403 $427 $372 $551 Balance Sheet 2007 2008 2009 2010 2011 2012 2013 2014 3/31/2015 ($ in millions) Cash Flow 2007 2008 2009 2010 2011 2012 2013 2014 ($ in millions)