Big Data What does it actually mean?
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- Annabella Payne
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1 Big Data What does it actually mean?
2 Introduction
3 A new world order Target knows your daughter is pregnant before you do! Identify pregnant women early to get them into the store and change shopping behavior How? Created an algorithm to identify about 25 products that, when analyzed together, assign each shopper a pregnancy prediction score Estimate her due date to within a small window
4 But what is Big Data? Big Data/bɪɡ ˈdeɪtə/plural noun Big data is an overarching theme for using multiple internal/external data sources to continuously generate new insights and knowledge to make business decisions more data-driven and fact-based How is it different? Using full data sets not subsets Utilize multiple data sources to triangulate results Continuously drive new insights analysis updated real time
5 Big data is characterized by the 3 Vs Volume Velocity Variety 6 exabytes of new data stored globally by consumers in exabytes of new data stored globally by enterprises in ,148 apps downloaded every 60 seconds 400,710 ads requested submitted every 60 seconds 5 billion mobile phone users in 2010, with 20% annual growth 30 million networked sensor nodes in 2010, with 30% annual growth 2 exabytes of new data generated by sensors in ,720 mobile banking transactions in Europe in just 1 day 30 billion pieces of content shared on Facebook every month
6 Big data is not new Big Data search on Google Tesco and Dunnhumby develop and launch Clubcard in In 2001 Begin to sell Clubcard insights Professional services and data analytics subsidiary MasterCard Advisors founded in 2001 Google creates MapReduce in 2004, a programming model for processing very large data sets IBM and City of Stockholm started in CineMatch 2007 to deploy the recommendation charging system engine to in 2000 handle - launched traffic congestion a contest in 2006 to find an algorithm that could beat CineMatch Began testing and piloting RFID with TOP 100 suppliers in 2005 Recommendation engine a key success factor since late 1990s Kaiser Permanente started building electronic medical recording system KP HealthConnect in Currently one of the largest implementations TomTom HD Traffic data service launched in partnership with Vodafone in
7 Big data companies outperform peers Big data leaders Competitors Revenue (10YR CAGR) 1,2 EBITDA (10YR CAGR) 1,2 Grocers Online retailers Big box retailers Casinos Credit cards Insurance All are figures except from Harrah s and its peer group, for which figures are used 2 Peer group for Tesco: Carrefour, Metro AG, Ahold, Sainsbury, Safeway, Krogers; Amazon: Barnes & Nobel, Borders Group, overstock.com, Sears, JC Penny; Walmart: Target, Krogers, Sears; Harrah s: MGM, Boyd, Pennacle, Trump Entertainment; Capital One: JP Morgan Chase, Bank of America, Citigroup, American Express, Wells Fargo, US Bancorp; Progressive: Allstate, Travelers, Hartford Insurance SOURCE: Bloomberg and Datastream; annual reports; McKinsey CMAC
8 The relative value potential and ease of capture will vary among sectors Big data ease of capture and value potential index Bubble sizes denote relative sizes of GDP SOURCE: McKinsey Global Institute analysis
9 But the potential is enormous Estimated value of Big Data for Telco operators $ Bn, 2011 prices Value from improving core Revenue from new businesses ~20 times current revenues of Facebook ~EUR1.3 monthly increase in revenue per mobile subscriber in the world < more than current global spend on roaming calls
10 We are all the providers of Big Data
11 A couple of example of what we have seen so far Health care and decease prevention Dynamic marketing and sales New service inventions Big Data Cross business Operations Socio and economic analysis Government, urbanization, and social good
12 How to get started Wave 1: Data & analytics infrastructure Achieve data transparency through Standardization of Measurement Storage Gathering Improving accessibility for inhouse operations/business units Wave 2: Improving in-house operations Improve core business through Increasing revenues Data driven up-sell and cross-selling Optimizing customer lifecycle management Managing product lifecycles Decreasing costs Data driven operations improvements Wave 3: Exploiting new business opportunities Exploit new businesses through Selling unique, consolidated data as wholesalers Developing proprietary tools/services in new business areas that utilize data advantage Enabler
13 Only your imagination is the limit Big data will make the world a better place by preventing disease fighting crime and boosting earnings
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