CORPORATE OVERVIEW. June 2018

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Charity Washington
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1 CORPORATE OVERVIEW June 2018

2 SAFE HARBOR STATEMENT 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 Annual Report filed with the Securities and Exchange Commission, or the SEC, on April 4, 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 byexcluding 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 June 6, 2018, which is available on or on the Investor Relations section of our website. Unless otherwise noted, the information in this presentation is as of April 30, 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. 2 Cloudera, Inc. All rights reserved.

3 INVESTMENT HIGHLIGHTS recurring Subscription software revenue TTM revenue 44% TTM subscription revenue growth 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 Customers (1) $100K+ software annual recurring revenue net expansion Driven by data and new use cases Notes: 1. FQ1 18: 392, FQ2 18: 429, FQ3 18: 475, FQ4 18: 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) Vast and growing ecosystem of solution and service provider partners Rapid growth with powerful land and expand economics 3 Cloudera, Inc. All rights reserved.

THE DATA ECONOMY THE DATA-DRIVEN ENTERPRISE connected (1) devices more data (2) AN UNTAPPED OPPORTUNITY of structured data is actively used in making decisions (3) of unstructured data is analyzed or

4 THE DATA ECONOMY THE DATA-DRIVEN ENTERPRISE connected (1) devices more data (2) AN UNTAPPED OPPORTUNITY of structured data is actively used in making decisions (3) of unstructured data is analyzed or used at all (3) 1. IDC estimates that there will be 30B IoT and connected devices in IDC estimates that there will be 440x more data in 2020 than Harvard Business Review Cloudera, Inc. All rights reserved.

5 WE DELIVER THE MODERN 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 5 Cloudera, Inc. All rights reserved.

7 ENABLING THE DATA-DRIVEN ENTERPRISE GROW BUSINESS CONNECT PRODUCTS & SERVICES (IoT) PROTECT BUSINESS Using deeper customer insights to personalize customer solutions Reducing manufacturing costs and improving product quality with IoT analytics Uncovering zero-day attacks and stopping advanced persistent threats more quickly 7 Cloudera, Inc. All rights reserved.

8 ENABLING THE DATA-DRIVEN ENTERPRISE GROW BUSINESS CONNECT PRODUCTS & SERVICES (IoT) PROTECT BUSINESS Enhancing customer experience with network visibility and tailored offers Predicting electrical energy demand with machine learning Identifying deposit fraud with machine learning 8 Cloudera, Inc. All rights reserved.

9 LARGE AND GROWING MARKET $73B $45B $11B 21% CAGR $28B $13B Cognitive / AI $5B Advanced analytics $10B Dynamic data mgmt + = Relational and non-relational DBMSs TAM 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 9 Cloudera, Inc. All rights reserved.

10 MARKET DEVELOPMENT & PHASES OF GROWTH ML, ANALYTICS & CLOUD DIGITAL TRANSFORMATION powered by data BIG DATA TECH DATA PLATFORM IT early adopters & Developers CIO & Data Admins LOB & Data Scientists C-suite & Boards 10 Cloudera, Inc. All rights reserved.

INNOVATIONS IN ML, ANALYTICS & CLOUD Cloudera Data Science Workbench (CDSW) Secure, collaborative data science at scale to speed workflows from research to production Cloudera Fast Forward Labs

11 INNOVATIONS IN ML, ANALYTICS & CLOUD Cloudera Data Science Workbench (CDSW) 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 Apache Kudu Real-time database for fast analytics on fast changing data to support ML & IoT Recent announcement CDSW 1.4 Shared Data Experience Cloudera Altus Data Engineering Cloudera Altus Analytic DB Cloudera Altus SDX Powerful software framework for multi-function data apps on-premises and in the cloud Multi-cloud PaaS for processing large-scale data sets in AWS and Azure Multi-cloud PaaS data warehouse for self-service BI and SQL analytics PaaS that provides and retains business context for shared cloud-based data Recent announcement generally available on Azure Recent announcement available on Azure (beta) Recent announcement Cloudera Altus SDX on Azure (beta) 11 Cloudera, Inc. All rights reserved.

13 CLOUDERA ENTERPRISE DATA PLATFORM WORKLOADS DATA SCIENCE ANALYTIC DATABASE OPERATIONAL DATABASE DATA ENGINEERING 3 RD PARTY SERVICES The modern platform for machine learning & analytics optimized for the cloud COMMON SERVICES SECURITY GOVERNANCE DATA CATALOG LIFECYCLE MANAGEMENT CONTROL PLANE STORAGE Amazon S3 Microsoft ADLS HDFS KUDU 13 Cloudera, Inc. All rights reserved.

SHARED DATA CONTEXT SERVICES Built for multi-function analytics anywhere Data Catalog: a comprehensive catalog of all data sets, spanning onpremises, cloud object stores, structured, unstructured,

14 SHARED DATA CONTEXT SERVICES Built for multi-function analytics anywhere Data Catalog: a comprehensive catalog of all data sets, spanning onpremises, cloud object stores, structured, unstructured, and semistructured. Includes technical schemas from the Hive metastore, as well as business glossary definitions, classifications, and usage guidance Security: role-based access control applied consistently across the platform using Apache Sentry. Also includes full stack encryption and key management Governance: enterprise-grade auditing, lineage, and other governance capabilities applied universally 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 14 Cloudera, Inc. All rights reserved.

16 ENTERPRISE MACHINE LEARNING PLATFORM DATA APPS PRODUCTION SOLUTIONS USE CASES UX DATA SCIENCE WORKBENCH ALGORITHMS Open platform Complete lifecycle EXPLORATORY ANALYSIS DATA SCIENCE WORKBENCH OPEN SOURCE & VENDOR ECOSYSTEM Team collaboration Enterprise ready Runs anywhere COMPUTE STORAGE S3 SPARK IMPALA GPUs CPUs CLOUD ADLS ON-PREMISES HDFS KUDU 16 Cloudera, Inc. All rights reserved.

ENTERPRISE-READY PRODUCTION MACHINE LEARNING ANALYZE Workbench INGEST Data TRAIN Experiments Complete machine learning lifecycle Model governance Model lineage Model security

17 ENTERPRISE-READY PRODUCTION MACHINE LEARNING ANALYZE Workbench INGEST Data TRAIN Experiments Complete machine learning lifecycle Model governance Model lineage Model security Model access control DEPLOY Models Data Security Governance Metadata Catalog SERVE Jobs Model Security Governance Lineage Access SHARE Reports 17 Cloudera, Inc. All rights reserved.

18 HYBRID IS THE NEW NORMAL IN ML & ANALYTICS CLOUD ON-PREMESIS Elastic Transient IoT Dev / Test New locations + Data sovereignty Persistent Legacy Cost Performance Choice Economics Migration Governance Control 18 Cloudera, Inc. All rights reserved.

19 ANALYTIC DATABASE FOR DATA WAREHOUSE TARGET DELIVER DIFFERENTIATE Specific use cases for mission critical data warehousing Data warehouse optimization Operational and discovery data marts Features to expand the opportunity and enhance competitiveness Interactive Scalable Versatile Cloud-based, big data app performance service Monitor Analyze Onboard Optimize 19 Cloudera, Inc. All rights reserved.

EXTENSIVE INTEGRATION WITH PUBLIC CLOUD VENDORS CLOUDERA ALTUS Platform-as-a-Service CLOUDERA ENTERPRISE Infrastructure-as-a-Service DATA ENGINEERING beta

20 EXTENSIVE INTEGRATION WITH PUBLIC CLOUD VENDORS CLOUDERA ALTUS Platform-as-a-Service CLOUDERA ENTERPRISE Infrastructure-as-a-Service DATA ENGINEERING beta ANALYTIC DB soon DATA SCIENCE DATA SCIENCE ANALYTIC DATABASE OPERATIONAL DATABASE DATA ENGINEERING beta Bare Metal Private Cloud 20 Cloudera, Inc. All rights reserved.

21 CLOUDERA ALTUS PAAS DATA ENGINEERING ANALYTIC DB DATA SCIENCE beta soon Multi-Cloud, Multi-Function Simple Self-service Auto-elastic Role specific SECURITY Amazon S3 GOVERNANCE DATA CATALOG LIFECYCLE MANAGEMENT Microsoft ADLS beta CONTROL PLANE 21 Cloudera, Inc. All rights reserved.

22 CLOUDERA IN THE CLOUD ERA Customer usage on AWS, Azure, and GCP 27% 24% 21% 21% 21% 22% 24% 25% 26% 26% 18% 16% 17% 18% 15% 14% 12% 11% 12% 9% 6% 3% 0% 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 Cloud Customers (as % of Total) 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 22 Cloudera, Inc. All rights reserved.

PARTNER ECOSYSTEM ISVs & SOLUTIONS RESELLERS

expand reach and accelerate consumption CLOUD

ADOPTION DRIVEN BY LARGE ENTERPRISES Customers across all verticals 539 Customers with $100K+ Software ARR Plant the flag international strategy TOP

24 ADOPTION DRIVEN BY LARGE ENTERPRISES Customers across all verticals 539 Customers with $100K+ Software ARR Plant the flag international strategy TOP GLOBAL TOP GLOBAL COUNTRIES TOP GLOBAL WITH GOV CUSTOMERS TOP GLOBAL BANKING TELCO PUBLIC HEALTHCARE TECHNOLOGY 24 Cloudera, Inc. All rights reserved.

25 TOP INDUSTRY VERTICALS BANKING TECHNOLOGY TELCO HEALTHCARE MANUFACTURING USE CASES Fraud detection Anti-money laundering Spend analytics Customer analytics Threat detection Predictive support Churn analysis Customer care Network optimization Patient care (IoT) Genomics research Regulatory compliance Predictive maintenance (IoT) Supply chain optimization Remote monitoring CUSTOMERS Barclays Bank of America Citi Cisco Intel NetApp Comcast British Telecom Bharti Airtel GlaxoSmithKline Symphony Health Sharp Healthcare Navistar Faurecia Sikorsky 25 Cloudera, Inc. All rights reserved.

27 CLOUDERA LEADERSHIP TEAM MIKE OLSON CO-FOUNDER & CSO AMR AWADALLAH CO-FOUNDER & CTO DANIEL STURMAN SVP ENGINEERING HILARY MASON GM MACHINE LEARNING ANUPAM SINGH GM ANALYTICS VIKRAM MAKHIJA GM CLOUD TOM REILLY CEO CHARLES ZEDLEWSKI SVP EMERGING BUSINESSES JIM FRANKOLA CHIEF FINANCIAL OFFICER AMY O CONNOR CHIEF DATA & INFORMATION OFFICER MICK HOLLISON CHIEF MARKETING OFFICER BRITT SELLIN VP HUMAN RESOURCES DAVID MIDDLER CHIEF LEGAL OFFICER 27 Cloudera, Inc. All rights reserved.

29 RAPID REVENUE GROWTH HISTORIC QUARTERLY REVENUE ($M) HISTORIC ANNUAL REVENUE ($M) 37% Y/Y growth $90 $95 $103 $103 $367 $391 $38 $44 $50 $56 $64 $67 $73 $80 $109 $166 $261 Q2 FY16 Q3 FY16 Q4 FY16 Q1 FY17 Q2 FY17 Q3 FY17 Q4 FY17 Q1 FY18 Q2 FY18 Q3 FY18 Q4 FY18 Q1 FY19 FY15 FY16 FY17 FY18 TTM at FQ1'19 Services Subscription 29 Cloudera, Inc. All rights reserved.

SIGNIFICANT EXPANSION IN EVERY COHORT 132% net expansion rate* Note: Our quarterly net subscription revenue expansion rate equals: the subscription revenue in a given quarter from all customers that

31 SIGNIFICANT EXPANSION IN EVERY COHORT 132% net expansion rate* 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. 31 Cloudera, Inc. All rights reserved.

33 RAPID SOFTWARE GROWTH DRIVES GROSS MARGIN EXPANSION 60% 69% 73% 73% 78% NON-GAAP GROSS MARGIN TRENDS 82% 85% 85% Software subscription revenue growth Benefiting from cloud deployment Machine learning powers proactive support FY16 FY17 FY18 FQ1'19 OVERALL FY16 FY17 FY18 FQ1'19 SOFTWARE Note: Presented on a non-gaap basis. Please see appendix for a Non-GAAP to GAAP reconciliation 33 Cloudera, Inc. All rights reserved.

34 PROGRESS TOWARD LONG-TERM MODEL NON-GAAP FY16 FY17 FY18 FQ1 19 Long-term model Subscription Margin Services Margin Total Gross Margin 78% 14% 60% 82% 24% 69% 85% 17% 73% 85% 10% 73% 90%+ 20%+ 82% - 84% R&D / Revenue S&M / Revenue G&A / Revenue 46% 84% 13% 37% 75% 10% 31% 56% 12% 33% 52% 12% 16% - 20% 30% - 34% 5% Operating Income Margin Operating Cash Flow Margin (83%) (55%) (54%) (45%) (26%) (12%) (24%) 24% 30% >30% Note: Presented on a non-gaap basis. Please see appendix for a Non-GAAP to GAAP reconciliation 34 Cloudera, Inc. All rights reserved.

35 Machine learning and analytics platform Cloud-native and cloud-differentiated Enterprise scale, security and performance Open-source innovation and efficiency World-class partner ecosystem Cloudera, Inc. All rights reserved.

GAAP TO NON-GAAP RECONCILIATION Three Months Ended

GAAP TO NON-GAAP RECONCILIATION Twelve Months Ended

Taking Advantage of Cloud Elasticity and Flexibility

Taking Advantage of Cloud Elasticity and Flexibility Fred Koopmans Sr. Director of Product Management 1 Public cloud adoption is surging 2 Cloudera customers are leading the way 3 Hadoop was born for the