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Open data 4 startups (2°edition)
 

Open data 4 startups (2°edition)

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Show the value of OpenData in creating New Business and Startups

Show the value of OpenData in creating New Business and Startups

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    Open data 4 startups (2°edition) Open data 4 startups (2°edition) Presentation Transcript

    • Open Data Startups Massimo Zaglio Christian Racca
    • Agenda Obiettivi del workshop Big Data Cosa sono gli Open Data e perchè Open Data? Quali vantaggi possono dare gli Open Data? Gli Open Data nel mondo Chi produce Open Data? Linked Open Data Alcuni Datasets disponibili Qualche esempio di Apps Altri esempi Le 10 slide20 sett 2011 Open Data Startups
    • Workshop GOALS Dare consapevolezza del valore potenziale dei dati open. Creare una versione ALPHA di start-up utilizzando uno o più datasets (suggeriti e non). Presentare in un elevator pitch di 4(?) minuti il proprio "seme" di start-up. Open Data Startups
    • WEB 2.0 WEB 2.0 is dead... Long life toWEB OF DATA Open Data Startups
    • Big Data: A growing torrent $600 to buy a disk drive that can store all the worlds music. 5 billion mobile phone in use in 2010. 30 billion pieces of content shared on Facebook every month. 40% of projected growth in global data generated per year VS 5% growth in global IT spending. 235 terabytes data collected by US Library of Congress in April 2011. 15 out of 17 sectors in the United States have more data stored per company than the US Library of Congress. * rapporto McKinsey: Big Data: The next frontier of innovation, competition and productivity. (may 2011) Open Data Startups
    • Big Data: Capturing the value $300 billion potential annual value to US health care - more than X 2 total annual health care spending in Spain. €250 billion potential annual value to Europes public sector administration - more than GDP of Greece. $600 billion potential annual consumer surplus from using personal location data globally. 60% potential increase in retailers operating margins possible with big data. 140.000-190.000 more deep analytical talent position and 1.5 million more data-savvy managers needed to take full advantage of big data in the USA. * rapporto McKinsey: Big Data: The next frontier of innovation, competition and productivity. (may 2011) Open Data Startups
    • Quanti di voi hanno preso lautobus questa mattina? Open Data Startups
    • Quanti di voi hanno preso lautobus questa mattina? Open Data Startups
    • Quanti di voi hanno preso lautobus questa mattina? Open Data Startups
    • Quanti di voi hanno preso lautobus questa mattina? Open Data Startups
    • Quanti di voi hanno preso lautobus questa mattina? Open Data Startups
    • Open Data - What are ? da Wikipedia Con Dati aperti, comunemente chiamati con il termine inglese Open Data anche nel contesto italiano, si fariferimento ad una filosofia, che è al tempo stesso una pratica. Essa implica che alcune tipologie di dati siano liberamenteaccessibili a tutti, senza restrizioni di copyright, brevetti o altre forme di controllo che ne limitino la riproduzione. Open Data Startups
    • Open Data - What are ? in pratica Open Data propone un modello di valorizzazione delpatrimonio informativo pubblico basato sulla possibilità di usare i dati aperti per creare nuovi servizi e nuovi strumenti. Open Data Startups
    • Open Data is a matter of: Prezzi I beni digitali: non rivali, costo di distribuzione/ riproduzione basso. Recupero dei costi VS distribuzione al costo marginale. Licenze OKF (Open Knowledge Foundation) CC (Creative Commons) ! possibilità di riuso a fini commerciali. Formati e Tecnologie ... Open Data Startups
    • Open Data - Formats Rendere disponibili i dati sul WEB in qualunque formato, utilizzando una licenza aperta. Rendere disponibili i dati sul WEB in formato leggibile dalle macchine (CSV, XLS...) Utilizzare formati non proprietari. Utilizzare lo standard RDF Dati in formato RDF linkati fra di loro (Linked RDF DATA) Open Data Startups
    • Open Data in the world La mia amministrazione è impegnata a creare un livello di apertura senza precedenti nella gestione del Governo. Lavoreremo insieme per accrescere la fiducia del pubblico e per creare un sistema basato sulla trasparenza, la partecipazione e la collaborazione. Questa apertura rafforzerà la nostra democrazia e promuoverà lefficenza e lefficacia nel nostro Governo. Transparency and Open Government Memorandum for the Heads of Executive Departments and Agencies (2009)"People are tempted to keep it [data]. You hug yourdatabase, you dont want to let it go until youve madea beautiful website for it. Well Id like to suggest that,yes, make a beautiful website, who am I to say dontmake a beautiful website? Make a beautiful website,but first, give us the unadulterated data, we want thedata, we want unadulterated data. We have to askfor raw data now."Tim Berners-Lee, inventore del WEB e advisordata.gov.uk Open Data Startups
    • Who produce Open Data ? Il settore pubblico possiede e gestisce grandi quantità di dati e informazioni il cui valore app. è 27 Miliardi di € (MEPSIR Report - Measuring European Public Sector Resources, 2006). La PSI può essere un primo grande fornitore di Open Data. Il settore privato potrebbe però diventare il maggior produttore di Open Data se ne percepisse il giusto valore. Open Data Startups
    • Open Data - Benefits Trasparenza Efficienza Concorrenza Innovazione Open Data Startups
    • Open Data - Challanges “Invogliare” la Pubblica Amministrazione a rendere i propri dati disponibili. LeCommunity (e start-ups) dovrebbero aggiungere business model e innovazione. Serendipity: L’innovazione è spesso generata dall’uso inaspettato di dati! Problemi Trovare nuovi dataset di dati “Fondere” e “linkare” dati e dataset (possibilmente on-the-fly). Open Data Startups
    • Data As A Service I datinon sono più "chiusi" nelle applicazioni... ... ma consumati on-demand come un qualsiasi altro tipo di servizio. RESTful: accedere ai dati come si accede ad una risorsa web: tramite URL. Open Data Startups
    • Data Marketplace Business Models: Data owner: paid to publish / revenue share. Data user: pay for data delivery/trasformation/analysis services. New Generation Marketplace Operano su dati open e non. Forniscono dati on-the-fly attraverso API (anche custom). Coinvolgono (in alcuni casi) la comunità nel mantenere (curation) i dati: crowdsourcing (e.g. Factual). Forniscono strumenti integrati (web based) per lesplorazione. Open Data Startups
    • LINKED Open Data Principi base: Le cose hanno un nome (persone, città, aziende). Ogni nome inizia con http:// Rappresentare i dati come un RDF (Resource Description Framework is a W3C standard). Linked Data spiegato da Tim Berners Lee: http://www.ted.com/talks/tim_berners_lee_on_the_next_web.html Open Data Startups
    • Data as a RDF graph Open Data Startups
    • The Vision - A global interconnected database Open Data Startups
    • The Vision - Mix data on-the-fly Open Data Startups
    • Linked Data - hands onDBPedia fornisce una gran parte delle entità di Wikipedia informato Linked Data.Firenze: http://dbpedia.org/page/Florence dbpedia-owl:leaderName Renzi Firenze Open Data Startups
    • Where are the Data ? Un archivio di open (e non open) data: http://ckan.net/ http://it.ckan.net/ Esempi: 5T: http://biennaledemocrazia.it/dataset/ Dati Piemonte: http://dati.piemonte.it Datasets originali ISTAT: http://dati.istat.it/ Enel http://data.enel.com/ Open Data Startups
    • Food Open Data Startups
    • Transportation Open Data Startups
    • Children Open Data Startups
    • Transparency Open Data Startups
    • Environment Open Data Startups
    • Other examples Open Data Startups
    • The linked Data CLOUD http://richard.cyganiak.de/2007/10/lod/lod- datasets_2010-09-22_colored.html Open Data Startups
    • The hackers WAY Quando licenze e copyright lo permettono... Web Site scraping è un possibilità. http://scraperwiki.com/ Es. http://scraperwiki.com/scrapers/aria-comune-di-torino/ Open Data Startups
    • Interesting Tools & LinksONLINE DATA VISUALIZATIONG visualization Api: http://code.google.com/intl/it-IT/apis/chart/Tableau Public: http://www.tableausoftware.com/publicOpen Heat Map: http://www.openheatmap.com/ONLINE STORAGE+VISUALIZATIONGoogle Public Data explorer: http://www.google.com/publicdata/homeIBM Many Eyes: http://www-958.ibm.com/software/data/cognos/manyeyes/Google Fusion tables: http://www.google.com/fusiontables/HomeImpure: http://www.impure.com/ è un linguaggio visuale tipo Y! Pipes per la data visualization. Moltopotente ma non facile da usare.CURATION & LINKINGGoogle RefineData Wrangler: http://vis.stanford.edu/wrangler/OFFLINE TOOLSR per dati statistici potentissimo molti plugin anche sparql: http://www.r-project.org/Jscript Library per la data visualization: http://thejit.org/Anche questa: http://vis.stanford.edu/protovis/Il miglior tool di network e graph analysis e visualization (non facilissimo ma davvero powerful, ha pluginsparql): http://gephi.org/Linguaggio turing complete per la dataviz, potentissimo, difficile (lo usano tutti i visual artist seri):http://processing.org/ Open Data Startups
    • Workshop Output 10 slides to pitch a Venture Capitalist Open Data Startups
    • How to Pitch a VCDave McClure, Founders Fund, Master of 500 Hats blogs @DaveMcClure on Twitter http://500startups.com/
    • Essential Elements of a Hot VC Pitch• Love in an Elevator (30-second quick pitch)• The Money Shot (live demo, screen shots, video)• Size Matters (market size, bottom up / top down)• Nice Package (customer$, metric$ UP & to the RIGHT)• Superheros & Rock Stars (your team) * note: the above are teaser images… they don’t really mean anything; they’re just here to capture your attention.
    • 10 Erogenous VC Zones Teaser Image Goes Here1. Elevator Pitch 6. Proprietary Tech2. The Problem 7. Competition3. Your Solution Money Shot 8. Marketing Plan 9. Team / Hires Goes Here4. Market Size5. Business Model 10. Money / Milestones AA RR R! The Money Shot: Business Demo Metrics Cu$tomer Screen Shots (NOT Revenue Testimonial$ Video Projections)
    • 1. The Elevator Pitch The 30-second quickie, for when you don’t have time for lots of VC lovin’• Short, Simple, Memorable: “What, How, Why.” – “We’re X for Y” is ok if 1) it’s true 2) X & Y are well-known• Max 3 key words / phrases, 2 sentences. – “SlideShare is the world’s largest community for sharing presentations. – “TeachStreet is a place to teach or learn anything.” – “Mint.com is the free, easy way to manage your money online.”• Logo and/or Image ok• No “Inside Baseball” lingo – make it easy for non-experts to understand.• Smile. It’s ok to have fun when you pitch !
    • 2. The Problem• What is The Problem? Make it Obvious. – “Ouch. Yeah, I have that too…”• Who has it? How Many? How do you know? – stats, examples, research, links.• “Painkiller not Vitamin” – Vitamins are great, but you NEED painkillers. BAD. (note: Viagra is not a Vitamin)
    • 3. Your SolutionDescribe why your Solution:– Makes customers very happy– Does it better, different than anyone else– Remember “NICHE to WIN” (Customer Case Study can also go here)
    • 4. Market Size no idea what this is, but it looks really F’ing impressive, doesn’t it? up & to the right.• Bigger is Better• Top Down = someone else reported it – Forrester, Gartner, Your Uncle• Bottom Up = calculate users/usage/rev$ – Avg Txn = $X – Y customers in our market – Avg customer buys Z times per year – Market Size = $X * Y * Z annually = a big friggin’ # – Market growing @ 100+% per year note: “top down” and “bottom up” have nothing to do with giving VCs hard-ons. Get your mind out of the gutter.
    • 5. Business Model (How Do You Plan to Make Money?)• Describe Top 1-3 Revenue Sources – Prioritize by Size, Growth, and/or Potential – Cite current market activity / customer behavior as proof• Show How You Get to Break-even (or Profitable) – Ideally, on the current round of funding you’re raising• Common Revenue Models – Direct: ecommerce, subscription, digital goods, brands – Indirect: advertising, lead gen, affiliate / CPA• See Andrew Chen presentation: • Revenue: The Internet Wants to Be Free, but You Need to Get Paid
    • 6. Proprietary Tech (What is your Unfair Advantage?)• VCs *really* like unfair advantage – big market lead – experienced team – ex-Google PhDs – core / “breakthrough” tech – “defensible” IP / patents – “exclusive” partnership – great sales/marketing – balls of steel
    • 7. Competition (+ why they all suck, why you’re different, yellow, better)• List all top competitors – (especially top ones; we’ll find them anyway)• Say how you’re better, or at least different – If not better or different -> “NICHE TO WIN” – position(-ing) matters• 2-axis graph is trite, but still useful – see next page for example• useful comparisons / differentiation: – simple vs complex – value vs cheap (tougher to prove tho) – cheap vs expensive (but careful you don’t race to bottom) – consumer vs enterprise – open vs proprietary (in this case, open usually better… but not always)
    • We’re Better, Different. (and You Suck.) Funny!Accepted Shocking !!! Not Funny.
    • 8. Marketing PlanOk, so your product / technology rocks, but… … how do you get customers / distribution?lots of channels, lots of decisions… choose a few: • PR • Email • Contest • SEO / SEM • Biz Dev • Blogs / Bloggers • Viral / Referral • Direct Marketing • Affiliate / CPA • Radio / TV / Print • Widgets / Apps • Dedicated Sales • LOLCats • Telemarketing 3 Things That Matter / To Measure : 1. Volume 2. Cost 3. Conversion
    • 9. TeamPeople that Get VCs all Hot & Bothered• Geeks with deep technical background• Entrepreneurs who have sold companies• Sales/Marketing who Make it RainAlso Identify:• Key Hires you Need but *Don’t* Have, and…• … you’ve got candidates lined up in those areas• ... ready to hire as soon as you close funding• … or at least job descriptions / est. salary
    • 10. Money, Milestones• How Much Money Raised / Now Raising? – Show 3 Budgets: Small, Medium, Large – Show how you’ve got “Small” already lined up – Show “Optionality”, Competitive Interest (if poss.)• How Will You Spend It? – Key Hires (Build Product) – Marketing & Sales (Drive Revenue) – CapX, Ops Infrastructure (Scale Up)• Show Achievable Milestones with Non-Linear Increase in Value – Show what will get you to next milestone (product, customers, hires) – Show how the capital you have is more than adequate
    • Additional Resources• Dave McClure: – Startup Metrics for Pirates (AARRR!) – ZapMeals Sample Pitch Presentation – Master of 500 Hats Blog: “Greatest Hats” (top blog posts)• Steve Blank: 4 Steps to Epiphany, Customer Development Methodology• Eric Ries: StartupLessonsLearned• Sean Ellis: Startup-Marketing.com• Andrew Chen: AndrewChenBlog.com• Brad Feld, Jason Mendelson: AskTheVC.com• Aydin Senkut: Felicis Ventures blog• Mark Suster: Both Sides of the Table• VentureHacks.com• StartupCompanyLawyer.com
    • Open Data Startups rks hop Wo he re!!! st arts Massimo Zaglio Christian Racca