Corporate Overviews22.q4cdn.com/.../Cloudera-Investor-Deck-(3Q-2018).pdf · Unified security...

1© Cloudera, Inc. All rights reserved.

Corporate Overview

December 2017


Safe Harbor StatementStatements 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 Prospectus filed pursuant to Rule 424(b) filed with the Securities and Exchange Commission, or the SEC, on September 28, 2017 , our most recently filed Quarterly Report on Form 10-Q 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 7, 2017, which is available on www.cloudera.com or on the “Investor Relations” section of our website.

We periodically update the Global 8000 list based on the FORBES Global 2000 list and information from Data.com, using the most recently published FORBES Global 2000 list (which is updated by Forbes annually) and

the most recent Data.com information (which is continuously updated by Data.com). Our customer count is subject to ongoing adjustment and, when adjustments occur, previously disclosed numbers of customers are

updated to allow for comparability.

Unless otherwise noted, the information in this presentation is as of October 31, 2017.

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.


1. Represents total revenue as of FQ3’18

2. FQ3’17: 513, FQ4’17: 566, FQ1’18: 595, FQ2’18: 643

3. Please see footnote on page 25

666 135%Global 8000 customers net expansion

Across all industry verticals

Driven by data and new use cases

$337MTTM revenue

51% TTM subscription

revenue growth

83%recurring software

Subscription software revenue

(3)

Investment highlights

• The modern platform for machine learning

and analytics optimized for the cloud

• Large addressable market – big data,

cloud, IoT, ML

• 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

(1)

(2)


The data economy

<1%of unstructured data

is analyzed or used at all

The data-driven enterprise

30Bconnected

devices

440x more data

(2)

An untapped opportunity

(1)

<50%of structured data is actively used in making decisions

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


We deliverthe modern software platform for machine

learning and analytics optimized for the cloud

ENTERPRISE GRADE

✓ Secure

✓ Performant

✓ Compliant

SCALABLE

✓ Elastic

✓ Cost-effective

✓ Lower TCO

RUNS ANYWHERE

✓ Cloud

✓ Multi-cloud

✓ On-premises


We empower people to transform complex data

into clear and actionable insights

DRIVE

CUSTOMER INSIGHTS

CONNECT PRODUCTS &

SERVICES (IoT)

PROTECT

BUSINESS


Helping clients improve customer outreach with real-time insights

Doubling equipment utilization through IoT and machine learning

Enabling the data-driven enterprise

Improving risk prediction while maintaining compliance

Delivering greater value through improved customer understanding

Powering predictive analytics to increase performance and reduce

fleet downtime

Creating new revenue streams with an advanced anti-fraud solution

DRIVE CUSTOMER INSIGHTSCONNECT PRODUCTS & SERVICES (IoT) PROTECT BUSINESS


ADDRESSING THREE TRANSFORMATIVE MARKETS… …WHILE DISRUPTING AN EXISTING MARKET

$5B

$13B

$11B

$28B

2016 2021

21%CAGR

$45BRelational and

non-relational DBMS

$73BTAM+ =

2021 2021

Cognitive / AI

Advanced analytics

Dynamic data management

$10B

Large and growing market

Source: IDC

Note: Transformative markets represented $10.6B in 2016 and $27.7B in 2021, approximately broken down into $13.3B for Cognitive/AI Systems and Content Analytics Software, $9.7B for

Dynamic Data Management Systems, $4.7B for Advanced and Predictive Analytics Software

2021 2021


The challenge with traditional data applications

• Limited to

one data type

• Limited to

one analytic

function

• Difficult to

integrate

Data

Exploration

STORAGE

SECURITY

GOVERNANCE

WORKLOAD MGMT

INGEST & REPLICATION

DATA CATALOG

SQL & BI

Analytics

STORAGE

SECURITY

GOVERNANCE

WORKLOAD MGMT


DATA CATALOG

Operational

Real-Time DB

STORAGE

SECURITY

GOVERNANCE

WORKLOAD MGMT


DATA CATALOG

ETL & Data

Processing

STORAGE

SECURITY

GOVERNANCE

WORKLOAD MGMT


DATA CATALOG

Custom

Functions

STORAGE

SECURITY

GOVERNANCE

WORKLOAD MGMT


DATA CATALOG


Cloudera Enterprise

10

The modern platform for machine learning and analytics optimized for the cloud

EXTENSIBLE

SERVICES

CORE

SERVICES DATA

ENGINEERING

OPERATIONAL

DATABASE

ANALYTIC

DATABASE

DATA CATALOG

INGEST &

REPLICATIONSECURITY GOVERNANCE

WORKLOAD

MANAGEMENT

DATA

SCIENCE

Amazon S3 Microsoft ADLS HDFS KUDUSTORAGE

SERVICES


Machine Learning

Real-time database for fast analytics and ML

in IoT use cases

Fast, easy, and secure self-service data science

for the enterprise

Industry leading applied research in machine

learning and AI

Multi-cloud

Apache Kudu

6 major innovations this year

Powerful software framework making multi-

function data apps easier to develop, less

expensive to deploy and more secure –

on-premises and in the cloud

Shared Data Experience

Multi-Cloud PaaS for processing large-scale

data sets in AWS and Azure

Data warehouse cloud PaaS

(Beta)


8%of corporate workloads

are in the cloud(1)

12%of business analytics market in cloud

growing at 25% CAGR to 2020(2)

~20%of customers run

in the cloud

Enterprise grade | Scalable | Runs anywhere

1. Citi estimated that, in 2015, 8% of corporate workloads were in the cloud

2. IDC estimated that, in 2015, 12% of business analytics market was in the cloud growing at a 25% CAGR to 2020

Cloudera in the cloud era


Unified security – protects sensitive data with consistent

controls, even for transient and recurring workloads

Consistent governance – enables secure self-service access to

all relevant data and increases compliance

Easy workload management – increases user productivity and

boosts job predictability

Flexible ingest and replication – aggregates a single copy of all

data, provides disaster recovery, and eases migration

Shared catalog – defines and preserves structure and business

context of data for new applications and partner solutions

Open management services frameworkBuilt for multi-function analytics | Optimized for cloud

14© Cloudera, Inc. All rights reserved. 14© Cloudera, Inc. All rights reserved.

Multi-Cloud Multi-Function

Platform-as-a-Service

Altus Analytic DB (beta) the first data warehouse cloud service

to bring the warehouse to the data, enabling

enterprises to quickly and reliably perform self-

service BI and SQL analytics

Altus Data Engineering simplifies building and running large-scale elastic

data workloads, making it easy to incorporate

data engineering elements into more complex BI,

data science and real-time apps


Customers

Run IMPALA on Cloudera

Machine LearningPattern recognition

Anomaly detection

Prediction

Customers

Run on Cloudera

Enterprise-proven

machine learning and analytics

AnalyticsSelf-service intelligence

Real-time analytics

Secure reporting

© Cloudera, Inc. All rights reserved.


Supports multiple languages

TensorFlow, R, Python

Direct, secure access to production data

Impala & Spark

Collaborative and reproducible data

science

Accelerating machine learning and data science from exploration

to production

Cloudera

Data Science Workbench


Published research subscription service

Delivers cutting edge advances in applied

machine learning / artificial intelligence

Accelerates adoption in large enterprises

Drives demand for our platform

Applied research for machine learning and data science

Cloudera

Fast Forward Labs


Predict health outcomes

IoT sensor data analytics

Dodd-Frank (CCAR)

Customerexperience

Device analytics Datasecurity + PCI

Taxpayer360

Supply chainoptimization

Frauddetection

Open ecosystem driving industry solutions

INDUSTRY STANDARD 100+ PARTNER SOLUTIONS

DRIVE

CUSTOMER INSIGHTS

CONNECT

PRODUCTS & SERVICES (IoT)

PROTECT

BUSINESS

SI and reseller

Software and OEM

Data systems

Platform and cloud

Machine learning and analytics optimized for the cloud


Adoption driven by large enterprises

Customers across all verticals

660+ Global 8000customers

7/10 9/10 30+ 6/10 8/10Top Global Top Global Top Global Top GlobalCountries with

Government Customers

BANKING TELCO PUBLIC HEALTHCARE TECHNOLOGY

Plant the flagInternational strategy

Note: Banking excludes state-controlled firms.


Benefitting from multiple growth vectors

New use cases

Cloud

Partner leverage

Explosion of data

International growth

New logos

OSS market seedingLAND

EXPAND


Cloudera leadership team

Tom Reilly

CEO

Mike Olson

Co-Founder and CSO

Amr Awadallah

Co-Founder and CTO

Doug Cutting

Chief Architect,

Co-Creator Hadoop

Daniel Sturman

SVP Engineering

Charles Zedlewski

SVP Products

Jim Frankola

Chief Financial Officer

Mick Hollison

Chief Marketing Officer

Vishal Rao

SVP Field Operations

Britt Sellin

VP Human Resources

David Middler

Chief Legal Officer


Financial highlights

Rapid revenue growth at scale

Powerful land & expand

economics

Proven pathto profitability

Large marketopportunity


$34$38

$44

$50$56

$64$67

$73$80

$90$95

FQ1'16 FQ2'16 FQ3'16 FQ4'16 FQ1'17 FQ2'17 FQ3'17 FQ4'17 FQ1'18 FQ2'18 FQ3'18

HISTORICAL QUARTERLY REVENUE ($M) HISTORICAL ANNUAL REVENUE ($M)

41%TTM

growth

$109

$166

$261

$337

FY15 FY16 FY17 TTM at FQ3'18

Services Subscription

Rapid revenue growth

51%Subscription

Y/Y TTMgrowth


Operations in 30+ countries

Covering 90%+ of Global 8000

Targeting the Global 8000FQ3’18 FQ3’18

Differentiated solution

85% of the world’s data

29%International

Revenue split

~60%Global 8000

& Public Sector

>80%Global 8000

& Public Sector

Subscription revenue splitCustomer split


Significant expansion in every cohort

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.

135%net expansion

rate


5 PLATFORM EDITIONS 3 NEW OFFERINGS SUBSCRIPTION PRICING

Diversified revenue model

BY CONSUMPTION

BY NODE

BY USER


60%

69%73%

FY16 FY17 FQ3'18

Rapid software growth drives gross margin expansionNON-GAAP GROSS MARGIN TRENDS

• Software subscription

revenue growth• scale benefits

• positive mix shift

• Benefitting from cloud

deployment

• Machine learning powers

proactive support

OVERALL

78%82%

86%

FY16 FY17 FQ3'18

SOFTWARE

Note: Presented on a non-GAAP basis. Please see pages 30-32 for a Non-GAAP to GAAP reconciliation


NON-GAAP FY16 FY17 FQ3’18 Long-term model

Subscription Margin

Services Margin

Total Gross Margin

78%

14%

60%

82%

24%

69%

86%

12%

73%

90%+

20%+

82% - 84%

R&D / Revenue

S&M / Revenue

G&A / Revenue

46%

84%

13%

37%

75%

10%

31%

57%

11%

16% - 20%

30% - 34%

5%

Operating Income Margin

Operating Cash Flow Margin

(83%)

(55%)

(54%)

(45%)

(26%)

(3%)

30%

>30%

Progress toward long-term model

1. Presented on a non-GAAP basis. Please see pages 30-32 for a Non-GAAP to GAAP reconciliation

(1)


• Machine learning and analytics platform

• Enterprise scale, security and performance

• Cloud-native and cloud-differentiated

• Open-source innovation and efficiency

• World-class partner ecosystem


GAAP to Non-GAAP Reconciliation (Three Months Ended – Oct 31, 2017)

(in thousands)


GAAP to Non-GAAP Reconciliation (Twelve Months Ended – Jan 31, 2017)

(in thousands)


GAAP to Non-GAAP Reconciliation (Twelve Months Ended – Jan 31, 2016)

(in thousands)

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