Hortonworks Data Platform

Sanjay Kumar General Manager, Telecom Hortonworks

Customer Momentum • 550 customers (as of August 5, 2015) • 119 customers added in Q2 2015 • Publicly traded on NASDAQ: HDP

Founded in 2011 Hortonworks Data Platform Original 24 architects, developers, • Completely open multi-tenant platform operators of Hadoop from Yahoo! for any app and any data • Consistent enterprise services for security, operations, and governance 740+ 1350+ Partner for Customer Success EMPLOYEES E C O S Y S T E M PARTNERS • Leader in open-source community, focused on innovation to meet enterprise needs • Unrivaled Hadoop support subscriptions

• De-Risk Future Architecture: 100% open source Hadoop ensure current and future alignment with marketplace (non proprietary vendor lock-ins) 100% • Accelerated Path to New Functionality: Open source community Speed of Open Source Development/Release far exceeds proprietary

• Best Path to Influence Hadoop Roadmap: Ensure Mission Critical Support and Most Committers and Greatest Contributions needed new Functionality can best be engineered in Hadoop and available in all future Releases in Apache Hadoop

• Integrates with your environment & Partner Solutions: Data Centric Architecture with Yarn allows other partner/vendor solutions to readily integrate and participate. (Not just solutions in silos) • Allows the Road to Data Centric Organization: Data Centric Architecture with Yarn to minimize the movement of data and let the applications interact directly with the data with our replication

• Best Chances of Success in your Telecom Environment: Best business value for current industry solution needs and a trusted partner to help on your Hadoop Journey for a Data Centric Transformation in Telecom

Hortonworks Data Platform provides Hadoop for the Enterprise: a centralized architecture of core enterprise services, for any application and any data.

Completely Open Hortonworks Data Platform 2.3 • HDP incorporates every element GOVERNANCE BATCH, INTERACTIVE & REAL-TIME DATA ACCESS SECURITY OPERATIONS required of an enterprise data platform: data storage, data access, Apache Falcon Apache Ranger Apache Ambari governance, security, operations Apache Apache Sqoop Apache Knox Zookeeper

• All components are developed in

Apache Hive Apache Cascading HBase Apache Solr Apache

Apache Spark Apache Apache Apache Accumulo Apache Storm Apache Apache Flume Pig Apache Apache Falcon Apache Oozie open source and then rigorously tested, certified, and delivered as an Apache Kafka YARN: Data Operating System (Cluster Resource Management) integrated open source platform that’s easy to consume and use by the 1 ° ° ° ° ° HDFS° ° ° ° ° ° ° enterprise and ecosystem. ° ° ° (Hadoop° ° Distributed° ° File° System)° ° ° ° °

“Niagara Files” software developed at NSA over 8 years became Apache NiFi in 2014

Onyara was founded in 2015 by the chief architects of Apache NiFi

Hortonworks acquired Onyara in August 2015, to further extend its Big Data management product line

Perishable Hortonworks DataFlow powered by Apache NiFi Insights

The IoAT Data Flow Store Data Enrich and Metadata Context

Hortonworks Data Platform Internet powered by Apache Hadoop Historical of Anything Hortonworks Data Platform Insights powered by Apache Hadoop Hortonworks DataFlow and the Hortonworks Data Platform deliver the industry’s most complete solution for management of Big Data

8 of the Top 9 North American Communication Service Providers have Standardized on Hortonworks

Hortonworks. We do Hadoop.

Page 9 © Hortonworks Inc. 2011 – 2014. All Rights Reserved Traditional systems under pressure 2020 40 Zettabytes 1 Challenges INDUSTRY Clickstream • Constrains data to app LEADERS • Can’t manage new data Geolocation • Costly to Scale

Web Data 2 New Data New Internet of Things Business Value

Docs, emails

Server logs

LAGGARDS

ERP CRM SCM

2012 Traditional 2.8 Zettabytes

APP-CENTRIC Limitations: • Multiple copies of data App1 App 2 App 3 App 4 App 5 App 6 • Difficult cross-system integration • Upper-limit on data volumes before harming performance App Centric will break down with x10, x100,x1000… Need to shift to Data Centric DATA-CENTRIC Advantages: • One version of the data • No need for cross-app integration • System scales linearly

Existing OSS/BSS/DWH – Driving Business Operations App 1 App 2 App 3 App 4 App 5 App 6 through a Central Data Lake • Injest all sources of data for Clickstream holistic view of customers, network, & products

Web & Social 360 IOT – Extending Value from Existing Customer Solutions Investments Geolocation Streaming: Network Awareness • Existing systems contribute Probes, Click Stream, and participate in central Sensor, Location Event Records data storage and processing Batch: Call Detail Records Analytic – New Generation of Data Call Logs On-Line: Customer Sentiment Services Centric Solutions Unstructured: Txt, • 360 Customer Household Files, emails Pictures, Video, View for enhanced Customer Voice2Text Experience Server Logs • Network Optimization & Network Journey for NFV Contextual Planning Marketing Optimization • IOT Solutions, Data monetization, and Analytics- as-a-service Page 12 © Hortonworks Inc. 2011 – 2014. All Rights Reserved How to See What the Customer Sees and Respond with Awareness

– View from The Customer (360 degree view) • Quality of Service Experience (Network details) Lifestyle & Interests • Call Center dialog (voice to text analysis) • Customer Interaction Channel (CRM, Billing) • Customer’s Sentiment (what they are saying on social media)

Call Center Social Media – Understanding Current State of the Customer Interaction Sentiment • Net Promoter Score (dynamically computed) • Churn Score • Appetite for Information & other Customer Metrics • Target Advertising Profile

– Next Best Actions Quality • Context aware promotions of • Churn risk response Service • Retail Store with State of the Customer • Omni-channel correlated actions

– Enrich the Data Lake with all available customer interaction points

– Develop and Revise the Models that best get your customer metrics: • Net Promoter Score, Customer Churn Score, Appetite for Information, Customer Target Profile, etc

– Deploy the Current State of the Customer with references and customer real-time metrics • Computed (ML) from the Data Lake into a Dynamic Customer Profile that is available across business groups and systems

– Drive Next Best Action Using Real Time Event triggers and Dynamic Customer Profile for Context awareness • Next Best Care Action • Location & Context Aware Marketing

Enabling a Modern Data Architecture . SAP offers a single unified data architecture including . SAP HANA + Hadoop = Instant access + Low Cost, Scale Out Storage . Enables applications (analytics, ERP, CRM, predictive, etc.) to interact with Hadoop

+ SAP can assure their customers they are deploying an SAP HANA + Hadoop architecture fully supported by SAP

SOURCES Analytic Predictive Web Mobile APPLICATONS Sensor

Geo Stream Accelerated Application Services Logs Processing Analytics

Text SAP HANA

Structured

Deep Analytics & Weather Low Cost Scale-Out Data Processing, Transformation, Exploration Rationalization

Data Ingestion & Provisioning & Ingestion Data Storage Social

Other HADOOP DATA LAKE

Customer Experience Management - Enhance End-to-end Experience of Customer - Become Trusted Partner to Customer - Awareness of customer’s needs when and where needed

Network Optimization New Business & Consumer Services - Move to Software Driven Networks - New Digital & Infrastructure Services - Leverage Network Data Assets Service - Data Monetization - Self optimizing and provisioning Providers - M2M, IoT, Analytics-as-a service

Challenge Solution Impact Fragmented view of the customer • Deploy a Data Lake and Analytics for “ Our Big Data solution for managing the across applications and the omni- capturing all sources of customer quality of service and customer channel causing silos of operations, interaction points across multi- interactions has helped to drive a 59% misaligned responses to customers channels (e.g. Network traffic, Social improvement in consumer experience” issues and an incomplete view of the Media, Clickstream, IVR, Geo-Spatial customers experience data.) apply to customer experience and market campaigns Victor Nelson Network data traffic growth of SVP of Big Data 50,000% within 6 year period due to • Ingesting 30 billion data points an AT&T smart phones hour correlated to optimize customer & network experience

• Tower outage and network analyzer to Page 20 © Hortonworks Inc. 2011 – 2014. All Rights Reserved prioritized the tower repairs to customer quality of service Dynamic Customer Profile Customer Stories and Targeted Marketing

Challenge Solution Impact

Modernize Audience Platform for • Created Granular customer profile “We were able to double our advertising Targeted Marketing and Advanced models from 5000+ attributes across revenue in the first year alone… most Analytics. 600+ traits of anonamized data for success project in the companies Campaign Optimization history!.”

Measure and Improve the end-to-end Customer Experience level to align • Computed Net Promoter Score “Now all Executive performances are organizational performances to (NPS) across different areas of measured against achieved Customer Satisfaction of the Customer customer touch points: Care, quality Net Promoter Scores.” of service, customer sentiment. Reflect State of the Customer through dynamic customer Profile Chris Dingle Sr. Director Customer Intelligence

Challenge Solution Impact To determine needed network • Deploy a Data Lake and Analytics for “Hortonworks Hadoop platform has helped investment, over-subscription models capturing 250 billion events per day us better understand and model our are developed from network event network demand… saving us 10s of traffic. Traditionally, the size of the data millions of dollars in network spending just • Develop network oversubscription has limited models to be based on on this one solution alone” sampling data over weeks of events not models based no complete network the months and years of data needed to event details for 13 month period to “Even after extensive churn reduction be accurate. have an accurate view on demand activities, we have been able to reduce our customer churn scores by an additional • Develop more detailed Customer To improve customer churn, data from 20% with new customer insights.” unstructured sources like social media Churn models with Hadoop to drive and voice-2-text from call centers need Next Best Action with customers Rob Smith to be added with structured data from across the CMR,Page Billing 22 and© Hortonworks Network Inc. to2011 better – 2014. All Rights Reserved Executive Director understand customer sentiment Verizon Wireless IT Operations EDW Data HDP HDP Real-time Streaming Offload Landing Zone Data Lake HDP Data Lake Business Functions

Customer 360 Customer Dynamic Location & Next Best - Customer Experience Sentiment & Household Customer Context Based Action Churn View Profile CEM

Target Context Aware Location & - Marketing Audience Target Context Based Profile Marketing Promotions

Real-Time Dynamic Threat Threat Pattern - Security Detection Analytics Detection

- Network Next Best Equipment Dynamic Customer Network Network Predictive Network Aware Network Decommissioning Investment Maintenance Provisioning Provisioning

Customer Cyber Hadoop- M2M/IoT Personal Industry Go-to-market Security as-a-service Solutions Intelligence Brokering