Cirata Plc · LSE:CRTA
Cirata — WANdisco — H1 2013 Earnings Presentation
46 slides from Cirata's earnings presentation, Sep 26, 2013
Slide 1: WANdisco plc Interim Results for the period ended 30 June 2013
WANdisco plc Interim Results for the period ended 30 June 2013 26 September 2013
Slide 2: A quick recap on our story
WANdisco A quick recap on our story WANdisco: Wide Area Network Distributed Computing Patented technology addressing a large, global market Leader in continuous availability Software Development: 300+ enterprise customers including: HP, Intel, Barclays, John Deere, Honda, Wal-Mart Big Data
Slide 3: 2013 Financial and Operational Highlights
2013 Financial and Operational Highlights Paul Harrison – CFO Executing on the strategy
Slide 4: Key financials
Key financials Summary H1 2013 H1 2013 H1 2012 FY 2012 30 JUNE $ 000’s $ 000’s $000’s Bookings 6,098 3,392 7,916 Deferred Revenue 8,961 4,940 6,368 Revenue 3,506 2,915 6,031 Adjusted EBITDA (3,323) 354 (3,002) Net Cash 5,454 21,982 14,545 29 new customers including ADP, Areva, Blue Cross Blue Shie
Slide 5: Bookings breakdown
Bookings breakdown H1 2013 key bookings metrics Number of Mix Type Bookings Value Average Deal Size Deals % New customers 29 $3,414,000 $117,700 58% Add-on deals 14 $483,000 $34,500 8% Renewals 38 $1,985,000 $52,200 34% Total install base 52 $2,468,000 $47,500 42% Deal total 81 $5,882,000 $72,600 10
Slide 6: Quarterly bookings progression
Quarterly bookings progression Cash bookings over 18 months Bookings 3.5 3 2.5 $ Millions 2 1.5 1 0.5 0 Q1 2012 Q2 2012 Q3 2012 Q4 2012 Q1 2013 Q2 2013 Period 6
Slide 7: Bookings breakdown by applications
Bookings breakdown by applications H1 2013 key bookings metrics H1 2013 H1 2012 Change Type $000 $000 % Application Lifecycle $5,941 $3,392 75% Management (ALM) Big Data $157 $0 N/A Total $6,098 $3,392 80% DConE applied to two businesses; ALM and Big Data H1 2013 predominantly ALM, with the firs
Slide 8: Cash flow bridge January 2013 to June 2013
Cash flow bridge 1 January 2013 to 30 June 2013 Cash bridge 20,000 3,900 (3,354) (2,542) 14,545 15,000 (3,746) (3,349) 10,000 5,454 $000 5,000 (5,000) Opening cash Cash receipts Investment in Enterprise Investment in Big Data Investment in ALM Other costs Closing cash sales engineers Engineers Pla
Slide 9: Operational update
Operational update Driving growth in the ALM business and establishing Big Data platform Big Data – Product launch brought forward - First product release February 2013 - First Big Data customer announced – Tier 1 UK telco - NSN signed up – June 2013 - Miaozhen (China) signed up – September 2013
Slide 10: 2013 Strategic Update
2013 Strategic Update David Richards – CEO Strong strategic progress
Slide 11: Our strategy for growth
Our strategy for growth Key focus areas 1 Market Share A significant opportunity to grow within existing markets 2 Product Development Targeting new and existing markets and customer groups 3 Big Data Expanding in to this fast growth market with new, ground-breaking products 4 Strategic Partners Acc
Slide 12: Strategic focus
Strategic focus Patented Active : Active replication technology applied to two markets… …with two approaches 12
Slide 13: ALM: Continued growth
ALM Continued growth Direct Enterprise Sales via an Expanded Sales Team Larger ‘enterprise’ size deals Entering the GIT Market Distributed version control is becoming more popular Offering dual license (both GIT & Subversion) GIT & Subversion is the Right Product Mix Different stages o
Slide 14: ALM customers commit
ALM customers commit Larger deal sizes and longer period Customers showing confidence in company and technology - Fortune 100 Heavy Equipment Manufacturer • Customer originally signed in 2011 • Deal started as $250,000 per year • 2013 deal has expanded to a 5 year term ($1,800,000) paid annually -
Slide 15: The Big Data opportunity
The Big Data opportunity A ‘killer app’ for our technology Big Data is a big problem… “Large data sets so big that commonly-used software tools are unable to capture, curate, manage, and process the data within a tolerable elapsed time.” Big Data is a big market… - $50bn by 2016 (Wikibon) - $16b
Slide 16: The Big Data opportunity: attractive market dynamics
The Big Data opportunity Attractive market dynamics Wikibon’s Big Data market forecast maps almost perfectly to technology adoption S-Curve - 2010 – 2012 much of the revenue generated was via education and services - 2012 – 2014 revenue is crossing to become product-based - Enterprise features suc
Slide 17: WANdisco's Big Data timeline
WANdisco’s Big Data timeline Achieved progress well ahead of our original expectations Strategic go-to- market partners Achieved first customer wins Built first Big Data products AltoStor Acquisition Tier 1 UK Telco Nov 2012 Sept 2013 17
Slide 18: Big Data strategy
Big Data strategy The Continuous Availability Platform Hadoop is being deployed for mission critical enterprise applications Financial trading systems Fraud detection QOS for cell towers These are real-time applications… A major US Bank told us a 1 minute outage of their trading system =
Slide 19: Major Big Data OEM secured
Major Big Data OEM secured NSN signed, validating platform approach A significant customer - Subsidiary of Nokia Corporation (formerly Nokia Siemens Networks), acquired Motorola’s wireless networks infrastructure business in 2011 - Started operations on April 1, 2007 - Net sales of approximately €
Slide 20: Miaozhen OEM WANdisco's Hadoop Products
Miaozhen OEM WANdisco’s Hadoop Products First Big Data Deal in China Miaozhen OEM’s WANdisco’s Continuous Availability Hadoop Products - Leading online advertising company - 100bn ads per day - Over 2pb of storage - Customers include P&G, Microsoft, Volkswagen, L'Oreal, Coca-Cola, YUM! OEM WANdi
Slide 21: De Facto Hadoop Continuous Availability Solution
De Facto Hadoop Continuous Availability Solution Integration / Strategic Partnering with Major Big Data Players Hortonworks (HDP 2.1) Now Supports WANdisco - Hortonworks: - Leading Hadoop vendor - Recently announced strategic deal with SAP (HANA) - Other customers include include eBay, Spotify, Xi
Slide 22: Building out the Big Data ecosystem
Building out the Big Data ecosystem Partnerships Dell - Certified Non-Stop Hadoop to run on Dell hardware - Leading provider of servers for Big Data AMP labs (UC Berkeley) - “Algorithms, Machines, People”, a five-year collaborative effort at UC Berkeley - Big Data research - Spark & Shark (in me
Slide 23: The Next Generation ALM Products
The Next Generation ALM Products Integrating ALM & Big Data A product strategy that fully utilizes skills & technology in Big Data & ALM Industry leading Big Data & ALM expertise Unification of existing technologies Massive Integrated Storage Enhance back-end database of Subversion, GIT &
Slide 24: Summary and Outlook
Summary and Outlook > WaONDISCO
Slide 25: Achievements in the first half
Achievements in the first half Strong H1 progress, with more to do Some very strong progress in H1 - Built out our offer in ALM and Big Data - Built out enterprise sales team - Management team strengthened - Strong growth momentum – bookings up 80% - Filed 3 further patents Investment and energi
Slide 26: Outlook
Outlook Capitalise on first mover advantage On track to achieve commercial and bookings targets for the current financial year Immediate need to strengthen Big Data team - Hortonworks and others require dedicated engineering resources • Continue to recruit Big Data engineers Primarily based in
Slide 27: Appendix
Appendix > WaNDISCO
Slide 28: Senior management team
Senior management team David Richards, Chairman, Chief Executive Officer & Co-Founder: 15+ years in senior management of software technology businesses in Silicon Valley, from start up companies to NASDAQ listed, including the sale of Librados to US NASDAQ listed company, NetManage, Inc. Became GM a
Slide 29: Senior management - continued
Senior management - continued Robert Budas, Vice President of Product Management has over 28 years of experience within the software industry, and has been focused on the Software Configuration Management sector for the last 17 years. Prior to joining WANdisco in 2007, Rob was Senior Systems Enginee
Slide 30: Non-executive Directors
Non-executive Directors Paul Walker served as Chief Executive Officer of The Sage Group Plc from 1994 to September 2010. Paul joined Sage Group Plc as Company Accountant in 1984 and served as its Finance Director until 1994. Paul has been a Non-Executive Director of Experian plc since June 2010 and
Slide 31: Differentiated Technology
Differentiated Technology Previously Thought Impossible 2001-2005 Dr Yeturu Aahlad left SUN Microsystems where he was the distributed systems architect to work on a maths problem: - active:active replication over a wide area network - A wide area network (WAN) is a long- distance communications ne
Slide 32: Differentiated Technology
Differentiated Technology Previously Thought Impossible The eight fallacies of distributed computing say “not possible” 32
Slide 33: Differentiated Technology
Differentiated Technology Previously Thought Impossible By 2005 he had solved the riddle… - 20 pages in the form of a mathematical proof Initially applied to the problem of distributed software engineering teams Same technology now being applied to the Big Data market 33
Slide 34: Market Approach & Competitors
Market Approach & Competitors Traditional Approach WANdisco Technology Master Slave Peer to Peer Master (single point of failure) Every server an exact replica All writes go over the WAN to the Master Slave Slave Slave Local read/write access to each server No single point of failure 34
Slide 35: Applications in Hadoop Big Data
Applications in Hadoop Big Data WANdisco Non-Stop NameNode 100% Uptime with WANdisco’s patented replication technology - Zero downtime / zero data loss - Enables maintenance without downtime Automatic recovery of any failed server without admin intervention Scales as workload increases VS HDFS
Slide 36: Distributed Development Problem
Distributed Development Problem From New York From Europe 2 hours 5 hours From China 2-3 days From India 1-2 days From Australia 8 hours Time to to read the SVN Repository 36
Slide 37: Distributed Development Solution
Distributed Development Solution SVN MultiSite Servers at every location 37
Slide 38: Customers
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Slide 39: The Big Data opportunity
The Big Data opportunity A ‘killer app’ for our technology Big Data is a big problem… “Large data sets so big that commonly-used software tools are unable to capture, curate, manage, and process the data within a tolerable elapsed time.” Big Data is a big market… - $50bn by 2016 (Wikibon) - $16b
Slide 40: The Big Data opportunity: attractive market dynamics
The Big Data opportunity Attractive market dynamics Wikibon’s Big Data market forecast maps almost perfectly to technology adoption S-Curve - 2010 – 2012 much of the revenue generated was via education & services - 2012 – 2014 revenue is crossing to become product-based - Enterprise features such
Slide 41: Unrivalled expertise in Hadoop
Unrivalled expertise in Hadoop Developing Hadoop products with Hadoop architects at the helm Dr. Konstantin Shvachko - Co-founder of AltoStor, acquired by WANdisco - Team member that invented Hadoop at Yahoo in 2006 - Principal Big Data architect at eBay - Hadoop committer and creator of Hadoop Di
Slide 42: First Big Data customer secured
First Big Data customer secured Tier 1 UK telecommunications company A significant customer - Tier 1 UK telecoms operator - Operations are globally distributed Utilising multiple WANdisco Big Data products - WANdisco WDD - WANdisco Non-Stop Hadoop Solving a significant business challenge - Lar
Slide 43: Major Big Data OEM secured
Major Big Data OEM secured NSN signed, validating platform approach A significant customer - Subsidiary of Nokia Corporation (formerly Nokia Siemens Networks), acquired Motorola’s wireless networks infrastructure business in 2011 - Started operations on April 1, 2007 - Net sales of approximately €
Slide 44: Strategic acquisitions delivered
Strategic acquisitions delivered Welcoming smartSVN and AltoStor Acquiring in ALM Acquiring in Big Data SmartSVN AltoStor Acquired in September 2012 for $1.0m Acquired in November 2012 for $4.9m of which $1.5m was paid immediately in cash Broadened the Group’s product offering for the ALM mark
Slide 45: The Wall Street Journal: Elephant in the Room to Weigh on Growth
The Wall Street Journal Elephant in the Room to Weigh on Growth for Oracle, Teradata Rolfe Winkler 19 August 2013 What do you get when you cross Google with a toy elephant? A threat to sales growth for some big technology companies, and a new breed of promising IPO candidates. In developing its powe
Slide 46: The Wall Street Journal: Elephant in the Room (cont.)
The Wall Street Journal Elephant in the Room to Weigh on Growth for Oracle, Teradata (cont.) As for the threat to database heavyweights like Oracle and Teradata, Hadoop won't cause companies to abandon the kind of relational database products they offer. These remain the standard for processing easi