Cloudera Toolkit (Dark) 2018€¦ · • Innovation driving substantial competitive advantage and extending category ... IT early & Data Scientists adopters & Developers DIGITAL TRANSFORMATION

CORPORATE OVERVIEWDecember 2018

2 © Cloudera, Inc. All rights reserved.

Statements in this presentation that are not historical in nature are forward-looking statements that, within the meaning of the federal securities laws including the safe harbor provisions of the Private

Securities Litigation Reform Act of 1995, involve known and unknown risks and uncertainties. Words such as "may", "will", "expect", "intend", "plan", "believe", "seek", "could", "estimate", "judgment",

"targeting", "should", "anticipate", "goal" and variations of these words and similar expressions, are also intended to identify forward-looking statements. The forward-looking statements in this

presentation address a variety of subjects, including our belief that the enterprise machine learning and analytics market will quickly emerge and that we will continue to lead its direction through

technology and product innovation, our expectation that we will continue our momentum in machine learning, analytics and the cloud, and our “Progress Towards Our Long Term Model”. Readers are

cautioned that actual results could differ materially from those implied by such forward-looking statements due to a variety of factors, including global economic conditions, competitive pressures and

pricing declines, intellectual property infringement claims, and other risks or uncertainties that are described under the caption “Risk Factors” in our Quarterly Report filed with the Securities and

Exchange Commission, or the SEC, on September 6, 2018, and in our other SEC filings. Although we believe the expectations reflected in such forward-looking statements are based upon

reasonable assumptions, we can give no assurances that our expectations will be attained. We undertake no obligation to update or revise any forward-looking statements, whether as a result of new

information, future events or otherwise.

We report all financial information required in accordance with U.S. generally accepted accounting principles (GAAP). To supplement our unaudited condensed consolidated financial statements

presented in accordance with GAAP, we use certain non-GAAP measures of financial performance. The presentation of these non-GAAP financial measures is not intended to be considered in

isolation from, as a substitute for, or superior to, the financial information prepared and presented in accordance with GAAP, and may be different from non-GAAP financial measures used by other

companies. In addition, these non-GAAP measures have limitations in that they do not reflect all of the amounts associated with the results of our operations as determined in accordance with GAAP.

We believe that these non-GAAP financial measures, when taken together with the corresponding GAAP financial measures, provide meaningful supplemental information regarding our performance

by excluding certain items that may not be indicative of our core business, operating results or future outlook. Management uses, and believes that investors benefit from referring to, these non-GAAP

financial measures in assessing our operating results, as well as when planning, forecasting and analyzing future periods. We use these non-GAAP financial measures in conjunction with traditional

GAAP measures to communicate with our board of directors concerning our financial performance. These non-GAAP financial measures also facilitate comparisons of our performance to prior

periods.

Please see the slides entitled GAAP to Non-GAAP Reconciliation at the end of this presentation for a reconciliation of each of these measures to the most directly comparable GAAP financial

measure. This reconciliation can also be found in the earnings release dated December 5, 2018, which is available on www.cloudera.com or on the “Investor Relations” section of our website.

Unless otherwise noted, the information in this presentation is as of October 31, 2018.

Cloudera and associated marks are trademarks or registered trademarks of Cloudera, Inc. All other company and product names may be trademarks of their respective owners.

SAFE HARBOR STATEMENT


INVESTMENT HIGHLIGHTS

• The modern platform for machine learning

and analytics optimized for the cloud

• Large addressable market – big data,

cloud, IoT, ML/AI, digital transformation

• Innovation driving substantial competitive

advantage and extending category

leadership

• Vast and growing ecosystem of solution

and service provider partners

• Rapid growth with powerful land and

expand economics

net expansion

Driven by new use cases and data growth

recurring

Subscription software revenue

TTM revenue

33% TTM subscription revenue growth

Customers

$100K+ software annual recurring revenue

Notes:

1. FQ3’18: 475, FQ4’18: 501, FQ1’19: 538, FQ2’19: 568

2. Our quarterly net subscription revenue expansion rate equals: the subscription revenue in a given quarter from all customers that had

subscription revenue in the same quarter of the prior year, divided by the subscription revenue attributable to that same group of customers in

that prior quarter. Our net expansion rate equals the simple arithmetic average of our quarterly net subscription revenue expansion rate for the

four quarters ending with the most recently completed fiscal quarter.

(2)(1)


of unstructured data is analyzed or used at all (3)

THE DATA-DRIVEN ENTERPRISE

connected devices

more data

(2)

AN UNTAPPED OPPORTUNITY

(1)

of structured data is actively used in making decisions (3)

1. IDC estimates that there will be 30B IoT and connected devices in 2020

2. IDC estimates that there will be 440x more data in 2020 than 2005

3. Harvard Business Review 2017

THE DATA ECONOMY


WE DELIVER THE MODERN PLATFORM FOR MACHINE LEARNING AND ANALYTICS OPTIMIZED FOR THE CLOUD

SCALABLEENTERPRISE GRADE RUNS ANYWHERE

✓ Elastic

✓ Cost-effective

✓ Lower TCO

✓ Secure

✓ Performant

✓ Compliant

✓ Cloud

✓ Multi-cloud

✓ On-premises


WE EMPOWER PEOPLE TO TRANSFORM COMPLEX DATA INTO CLEAR AND ACTIONABLE INSIGHTS

CONNECT PRODUCTS &

SERVICES (IoT)

GROW BUSINESS PROTECT BUSINESS


ENABLING THE DATA-DRIVEN ENTERPRISE

Using deeper customer insights

to personalize customer solutions

GROW BUSINESS

Reducing manufacturing costs and

•improving product quality with IoT analytics

CONNECT PRODUCTS &

SERVICES (IoT)

Uncovering zero-day attacks and stopping

advanced persistent threats more quickly

PROTECT BUSINESS


ENABLING THE DATA-DRIVEN ENTERPRISE

•Enhancing customer experience

with network visibility and tailored offers•Predicting electrical energy demand

with machine learning•Identifying deposit fraud

•with machine learning

GROW BUSINESS CONNECT PRODUCTS &

SERVICES (IoT)

PROTECT BUSINESS


LARGE AND GROWING MARKET

Source: IDC. Note: Transformative markets represented $12.7B in 2017 and $32.3B in 2022, approximately broken down into $14.3B for Cognitive/AI Systems and Content Analytics Software, $13.2B for Dynamic Data

Management Systems, $4.9B for Advanced and Predictive Analytics Software

2017 2022

$13B Dynamic data mgmt

$5B Advanced analytics

$14B Cognitive / AI

$13B

$32B

Relational /

Non-relational

DBMSs and

Data Warehouse

$51B

TAM

$83B

+ =21%CAGR


MARKET DEVELOPMENT & PHASES OF GROWTH

BIG DATA

TECH

DATA

PLATFORM

CIO

& Data Admins

ML, ANALYTICS

& CLOUD

LOB

& Data ScientistsIT early

adopters &

Developers

DIGITAL

TRANSFORMATIONpowered by data

C-suite &

Boards


INNOVATIONS IN ML, ANALYTICS & CLOUD

Cloudera

Data Warehouse

Modern, hybrid cloud data

warehouse supporting self-

service analytics and

petabyte-scale workloads

Recent announcement

Cloudera Data Science

Workbench

Secure, collaborative data

science at scale to speed

workflows from research to

production

Cloudera Fast Forward

Labs

Applied ML/AI research and

advisory services that enable

data science in the enterprise

Cloudera

Machine Learning

Simplifies machine learning

workflows with a unified

cloud-native experience for

data science and data

engineering on Kubernetes

Cloudera

Workload XM

Intelligent workload

management service designed

for today’s modern data

warehouse

Recent announcement

Cloudera Altus

Data Warehouse

Multi-cloud data warehouse

as a service delivering a

superior analytics experience,

governance, and performance

Recent announcement

Shared Data

Experience

SDX persisted metadata and

data security capabilities

extend to public cloud and

as-a-service workloads

Recent announcement

https://www.cloudera.com/more/news-and-blogs/press-releases/2018-08-28-cloudera-leads-the-way-in-data-warehousing-for-hybrid-cloud.html

https://www.cloudera.com/more/news-and-blogs/press-releases/2018-08-29-cloudera-advances-data-warehousing-leadership.html

https://www.cloudera.com/more/news-and-blogs/press-releases/2018-08-28-cloudera-leads-the-way-in-data-warehousing-for-hybrid-cloud.html

https://www.cloudera.com/more/news-and-blogs/press-releases/2018-12-05-cloudera-announces-preview-of-cloud-native-machine-learning-platform-to-accelerate-the-industrialization-of-ai.html


MODERN DATA ARCHITECTURE ML / AI

(DATA SCIENCE)ANALYTICS

CLOUD STORAGE ON-PREMISES STORAGE

MANAGEMENT & SECURITY

DATA

ENGINEERING


CLOUDERA ENTERPRISE DATA PLATFORM

The modern platform for

machine learning & analytics

optimized for the cloud

WORKLOADS 3RD PARTY

SERVICES

DATA

ENGINEERING

DATA

SCIENCE

DATA

WAREHOUSE

OPERATIONAL

DATABASE

DATA CATALOG

GOVERNANCESECURITY LIFECYCLE

MANAGEMENT

STORAGE Microsoft

ADLS

COMMON SERVICES

HDFS

Amazon

S3

CONTROL

PLANE

KUDU


SHARED DATA EXPERIENCEBuilt for multi-function analytics anywhere

• Security: role-based access control applied consistently across the platform.

Includes full stack encryption and key management

• Governance: enterprise-grade auditing, lineage, and governance capabilities

applied across the platform with rich extensibility for partner integrations

• Lifecycle Management: comprehensive ingest-to-purge management of data

set lifecycle activities

• Control Plane: multi-environment cluster provisioning, deployment,

management, and troubleshooting

• Data Catalog: a comprehensive catalog of all data sets, spanning on-

premises, cloud object stores, structured, unstructured, and semi-structured


Lead machine

learning in the

enterprise

Disrupt the data

warehouse market

Capitalize on cloud

adoption

STRATEGIC GROWTH DRIVERS


CLOUDERA MACHINE LEARNING

Tech

Preview

Cloud-native machine learning platform powered by Kubernetes

DATA

SCIENCE

DATA

ENGINEERING

MODEL

OPERATIONS

AI RUNTIME (CPU/GPU-optimized Python/R, Spark, …)

SHARED WORKSPACES FEATURE + MODEL CATALOG

Interactive Batch and Stream APIs

Spark-on-YARN

Microsoft

ADLS

Amazon

S3KUDUHDFS

DATA

WAREHOUSE

Same workflow as CDSW

Embeds Spark for optional separation

of storage & compute

Connects to HDFS & object storage

Elastic autoscaling with dependency

coordination

Fully containerized & deployable

on Kubernetes

Common runtime & shared metadata


MACHINE LEARNING FOR THE ENTERPRISE

• Open platform

• Open algorithms

• Team collaboration

• Enterprise ready

• Runs anywhere

DATA SCIENCE WORKBENCH

CLOUD ON-PREMISES

SPARK | IMPALA |

GPUs | CPUs

ADLSS3 HDFSSTORAGE

COMPUTE

ALGORITHMS

OPEN SOURCE &

VENDOR

ECOSYSTEMEXPLORATORY

ANALYSIS

SOLUTIONS | USE CASES | UXDATA APPS

KUDU

DATA SCIENCE WORKBENCHPRODUCTION


MACHINE LEARNING PRODUCTION LIFECYCLE ANALYZE

Workbench

TRAINExperiments

DEPLOYModels

SERVEJobs

SHAREReports

INGESTData

DataSecurity

Governance Metadata Catalog

ModelSecurity

Governance LineageAccess


HYBRID IS THE NEW NORMAL IN ML & ANALYTICS

CLOUD

• Elastic

• Transient

• IoT

• Dev / Test

• New locations

ON-PREMISES

• Data sovereignty

• Persistent

• Legacy

• Cost

• Performance

+

Choice | Economics | Migration | Governance | Control

20© Cloudera, Inc. All rights reserved.

DATA

WAREHOUSE FOR

HYBRID CLOUD

We enable customers to securely

share petabytes of data across

thousands of users while maintaining

SLAs and minimizing costs

● Ultimate hybrid choice

● Self-service analytics

● No data copies or moves

Before Cloudera, several data warehouse appliances were necessary to support our complex

analytic requirements including market surveillance and member compliance analysis.

Because the warehouse appliances could not scale we were forced to silo our data by market.

Cloudera's ease of scalability and performance efficiency enabled us to consolidate all of our

data platforms and today we run over 80,000 queries a day on Petabytes of data, while adding

30 TB of fresh data daily. With Cloudera, we eliminated data silos and improved our market

surveillance and member compliance analytics capabilities. Cloudera is the right partner for

NYSE.

- Steve Hirsch, Chief Data Officer, Intercontinental Exchange / NYSE

Analytical insights are the key for us to be able to differentiate ourselves and create more value

for our customers. With Cloudera Altus Data Warehouse and SDX [Shared Data Experience]

running on Microsoft ADLS (Azure Data Lake Storage), we were able to establish our Telekom

Data Intelligence Hub: a trusted, fully governed platform and ecosystem where our users are

empowered to exchange and analyze data and develop multi-function, data-driven applications

easier and securely.

- Sven Löffler, Business Development Executive, Deutsche Telekom

Gartner Peer Insights Customers’ Choice distinctions are determined by the subjective opinions of individual end-user customers based on their own

experiences, the number of published reviews on Gartner Peer Insights and overall ratings for a given vendor in the market, as further described

here, and are not intended in any way to represent the views of Gartner or its affiliates.

Recognized as one of the best data warehouse

solutions in the 2018 Gartner Peer Insights Customers’ Choice for

Data Management Solutions for Analytics

https://www.gartner.com/reviews-pages/peer-insights-customers-choice-methodology/

https://www.cloudera.com/more/news-and-blogs/press-releases/2018-08-06-cloudera-recognized-in-gartner-peer-insights-customers-choice.html


Research & Discovery

Textual + Relational Data

Correlation & Analytics

Operations

Web log & IoT data Reporting &

Analytics

Optimization

Offload EDWs

Migrate Data Marts

MODERN DATA WAREHOUSE USE CASES


CLOUDERA ALTUS DATA WAREHOUSEFirst cloud data warehouse with a scale-up architecture that routinely handles 50PB

• Bring the warehouse to the data with zero copy simplicity

• Use security policies with customer data - no proprietary stacks

• Apply enterprise governance to transient workloads

• Shared data experience, SDX, for analytic, ML & real-time

workloads

• Ultimate hybrid choice - storage, compute & control - H3

• Optimized for Azure & AWS


CLOUDERA WORKLOAD XM

• Proactively optimizes

workloads, application

performance, and

infrastructure capacity

• Supports Data Warehousing,

Data Engineering and Machine

Learning environments

• A cloud service for use with

public cloud, hybrid cloud, and

on-premises customer

deployments

OPTIMIZE

Delivers

predictable app

performance

Prescriptive

workload tuning

Controls & aligns

resource-to-cost

MIGRATE

Easy onboarding

of new apps

Reduces time to

production

Comprehensive

risk assessment

MANAGE

Defines and

monitors SLAs

Eliminates

bottlenecks

Dynamic

capacity planning

ANALYZE

Monitors

app health

Spots anti-

patterns & bad

hardware

Enables self-

service analytics

Intelligent workload management


EXTENSIVE INTEGRATION WITH PUBLIC CLOUD VENDORS

DATA

ENGINEERING

DATA

SCIENCE

DATA

WAREHOUSE

OPERATIONAL

DATABASE

CLOUDERA ENTERPRISE

Private Cloud

Infrastructure-as-a-Service

CLOUDERA ALTUS

DATA ENGINEERING DIRECTORDATA WAREHOUSE

Platform-as-a-Service

Bare Metal


CLOUDERA ALTUS PAAS

• Multi-Cloud

• Multi-Function

• Self-service

• Auto-elastic

• Role specific

DATA ENGINEERING DATA WAREHOUSE DIRECTOR

DATA CATALOG

GOVERNANCESECURITY CONTROL

PLANE

LIFECYCLE

MANAGEMENT

Amazon

S3

Microsoft

ADLS


Customer usage on AWS, Azure, and GCP

Notes for cloud-related metrics:

- Total Customers: all customers who share diagnostic data

- Cloud Customers: customers with utilization in prior six month

period on AWS, Azure and GCP

CLOUDERA IN THE CLOUD ERA

11%12%

14%

16% 17%18%

21% 21% 22%

24%25%

26% 26% 26% 26%

Q1 FY16 Q2 FY16 Q3 FY16 Q4 FY16 Q1 FY17 Q2 FY17 Q3 FY17 Q4 FY17 Q1 FY18 Q2 FY18 Q3 FY18 Q4 FY18 Q1 FY19 Q2 FY19 Q3 FY19

0%

3%

6%

9%

12%

15%

18%

21%

24%

27%

Cloud Customers (as % of Total)


PARTNER ECOSYSTEM

ISVs & SOLUTIONS

CLOUD & PLATFORM

SYSTEM

INTEGRATORSRESELLERS

Strategic partnerships

expand reach and accelerate

consumption


TOP GLOBAL

ADOPTION DRIVEN BY LARGE ENTERPRISES

TOP GLOBAL TOP GLOBAL TOP GLOBALCOUNTRIES WITH GOV

CUSTOMERS

BANKING TELCO HEALTHCARE TECHNOLOGYPUBLIC

Customers across

all verticals

601 Customers with

$100K+ Software ARR

Plant the flag

international strategy


KEY INDUSTRY VERTICALS & USE CASES

BANKING

• Fraud detection

• Anti-money

laundering

• Spend analytics

• Barclays

• Bank of America

• Citi

HEALTHCARE

• Patient care (IoT)

• Genomics research

• Regulatory

compliance

• GlaxoSmithKline

• Symphony Health

• Sharp Healthcare

TECHNOLOGY

• Customer

analytics

• Threat detection

• Predictive support

• Cisco

• Intel

• NetApp

TELCO

• Churn analysis

• Customer care

• Network

optimization

• Comcast

• British Telecom

• Bharti Airtel

MANUFACTURING

• Predictive

maintenance (IoT)

• Supply chain

optimization

• Remote monitoring

• Navistar

• Faurecia

• Sikorsky

USE CASES

CUSTOMERS


BENEFITTING FROM MULTIPLE GROWTH VECTORS


TOM REILLY

CEO

MIKE OLSON

CO-FOUNDER & CSO

AMR AWADALLAH

CO-FOUNDER & CTO

DANIEL STURMAN

SVP ENGINEERING

CHARLES

ZEDLEWSKI

SVP EMERGING

BUSINESSES

DAVID MIDDLER

CHIEF LEGAL

OFFICER

JIM FRANKOLA

CHIEF FINANCIAL

OFFICER

MICK HOLLISON

CHIEF MARKETING

OFFICER

BRITT SELLIN

VP HUMAN

RESOURCES

AMY O’CONNOR

CHIEF DATA &

INFORMATION OFFICER

HILARY MASON

GM MACHINE LEARNING

ANUPAM SINGH

GM ANALYTICS

VIKRAM MAKHIJA

GM CLOUD

CLOUDERA LEADERSHIP TEAM

© Cloudera, Inc. All rights reserved.32 © Cloudera, Inc. All rights reserved.

Rapid revenue growth

Powerful land & expand

economics

Proven pathto profitability

Large market

opportunity

FINANCIAL HIGHLIGHTS


HISTORIC QUARTERLY REVENUE ($M) HISTORIC ANNUAL REVENUE ($M)

29%Y/Y growth

$50$56

$64 $67$73

$80

$90$95

$103 $103$110

$118

Q4FY16

Q1FY17

Q2FY17

Q3FY17

Q4FY17

Q1FY18

Q2FY18

Q3FY18

Q4FY18

Q1FY19

Q2FY19

Q3FY19

$109

$166

$261

$367

$435

FY15 FY16 FY17 FY18 TTM atFQ3'19

Services Subscription

RAPID REVENUE GROWTH


STEADYCUSTOMER GROWTH

Customers With $100K+ Software Annual Recurring Revenue

475501

538

568

601

Q3 FY18 Q4 FY18 Q1 FY19 Q2 FY19 Q3 FY19


Note: Our quarterly net subscription revenue expansion rate equals: the subscription revenue in a given

quarter from all customers that had subscription revenue in the same quarter of the prior year, divided by

the subscription revenue attributable to that same group of customers in that prior quarter. Our net

expansion rate equals the simple arithmetic average of our quarterly net subscription revenue expansion

rate for the four quarters ending with the most recently completed fiscal quarter.

127%net

expansion

rate*

SIGNIFICANT EXPANSION IN EVERY COHORT


CORE PLATFORMPAAS & ADDITIONAL

OFFERINGSSUBSCRIPTION PRICING

BY

CONSUMPTION

BY NODE

BY USER

DIVERSIFIED REVENUE MODEL

Cloudera Enterprise Data Hub

Cloudera Data Science & Engineering

Cloudera Data Warehouse

Cloudera Machine Learning

Cloudera Operational DB

Cloudera Essentials

Cloudera Data Science Workbench

Cloudera Altus Data Warehouse

Cloudera Altus Data Engineering

Cloudera Workload XM

Cloudera Fast Forward Labs


RAPID SOFTWARE GROWTH DRIVES GROSS MARGIN EXPANSION

• Software subscription

revenue growth

• Benefiting from cloud

deployment

• Machine learning powers

proactive support

60%

69%73%

79%

FY16 FY17 FY18 FQ3'19

78%82%

85%89%

FY16 FY17 FY18 FQ3'19

OVERALL SOFTWARE

NON-GAAP GROSS MARGIN TRENDS

Note: Presented on a non-GAAP basis. Please see appendix for a Non-GAAP to

GAAP reconciliation


NON-GAAP FY16 FY17 FY18 FQ3’19 Long-term

model

Subscription Margin

Services Margin

Total Gross Margin

78%

14%

60%

82%

24%

69%

85%

17%

73%

89%

26%

79%

90%+

20%+

82% - 84%

R&D / Revenue

S&M / Revenue

G&A / Revenue

46%

84%

13%

37%

75%

10%

31%

56%

12%

25%

42%

15%

16% - 20%

30% - 34%

5%

Operating Income Margin

Operating Cash Flow Margin

(83%)

(55%)

(54%)

(45%)

(26%)

(12%)

(3%)

(6%)

30%

>30%

Note: Presented on a non-GAAP basis. Please see appendix for a Non-GAAP to

GAAP reconciliation

(1) FQ3’19: Includes $6M of merger-related costs

PROGRESS TOWARD LONG-TERM MODEL

(1)

© Cloudera, Inc. All rights reserved.

• Machine learning and analytics platform

• Cloud-native and cloud-differentiated

• Enterprise scale, security and performance

• Open-source innovation and efficiency

• World-class partner ecosystem


Three Months Ended – October 31, 2018

GAAP TO NON-GAAP RECONCILIATION


Three Months Ended – October 31, 2017



Twelve Months Ended – Jan 31, 2018









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Cloudera Toolkit (Dark) 2018€¦ · • Innovation driving substantial competitive advantage and extending category ... IT early & Data Scientists adopters & Developers DIGITAL TRANSFORMATION