LEADER 02059nam 2200409Ia 450 001 996393898703316 005 20200824121839.0 035 $a(CKB)4940000000115452 035 $a(EEBO)2248521463 035 $a(UnM)99898929e 035 $a(UnM)99898929 035 $a(EXLCZ)994940000000115452 100 $a19981030d1558 uy | 101 0 $aeng 135 $aurbn||||a|bb| 200 14$aThe rules and ryghte ample documentes, touchinge the vse and practise of the common almanackes which are named ephemerides$b[electronic resource] $eA bryefe and shorte introduction vpon the iudicial astrologie, for to prognosticate of thinges to come, by the helpe of the sayd ephemerides. With a treatise added hereunto touchinge the coniunction of the planets, in euery one of the. 12. signes and of their prognostications and reuolutions of yeres. The hole faithfully, and clerely translated into Englyshe by Humfrey Baker 210 $a[Imprynted at London $cin Fletestrete nere to S. Dunstons church by Thomas Marshe$d[1558?]] 215 $a[112] p. $cill., tables, diagrams 300 $aBy Fine, Oronce--STC. 300 $aA translation of: Fine, Oronce. Les canons & documents tresamples, touchant l'usage & practique des communs almanachz, que l'on nomme ephemerides. 300 $aPrinter's name and address from colophon; entered in Stationer's Register 1557-58--STC. 300 $aSignatures: A-G. 300 $aReproduction of original in the Bodleian Library, Oxford, England. 330 $aeebo-0014 606 $aAstrology$vEarly works to 1800 606 $aEphemerides$vEarly works to 1800 615 0$aAstrology 615 0$aEphemerides 700 $aFine$b Oronce$f1494-1555.$0330004 701 $aBaker$b Humfrey$ffl. 1557-1587.$01001627 801 0$bCu-RivES 801 1$bCu-RivES 801 2$bWaOLN 906 $aBOOK 912 $a996393898703316 996 $aThe rules and ryghte ample documentes, touchinge the vse and practise of the common almanackes which are named ephemerides$92307758 997 $aUNISA LEADER 05582cam a2200289 i 4500 001 991000349779707536 008 220531s2016 nju b 001 0 eng 020 $a9781119231387 035 $ab14458287-39ule_inst 040 $aBibl. Dip.le Aggr. Ingegneria Innovazione - Sez. Ingegneria Innovazione$beng 082 00$a658.0557$223 100 1 $aMarr, Bernard$0599713 245 10$aBig data in practice :$bhow 45 successful companies used big data analytics to deliver extraordinary results /$cBernard Marr 264 1$aChichester, West Sussex :$bWiley,$c2016 300 $axi, 308 p. ;$c22 cm 504 $aIncludes bibliographical references and index 505 8 $aMachine generated contents note: Introduction 1 Walmart: How Big Data Is Used To Drive Supermarket Performance 2 CERN: Unravelling the Secrets of the Universe with Big Data 3 Netflix: How Netflix Used Big Data to Give Us the Programmes We Want 4 Rolls-Royce: How Big Data Is Used To Drive Success In Manufacturing 5 Shell: How Big Oil Uses Big Data 6 Apixio: How Big Data Is Transforming Healthcare 7 Lotus F1 Team: How Big Data Is Essential To The Success Of Motorsport Teams 8 Pendleton & Son Butchers: Big Data for Small Business 9 US Olympic Women's Cycling Team: How Big Data Analytics Is Used To Optimize Athletes' Performance 10 ZSL: Big Data In The Zoo And To Protect Animals 11 Facebook: How Facebook Use Big Data to Understand Customers 12 John Deere: How Big Data Can Be Applied On Farms 13 Royal Bank of Scotland: Using Big Data to Make Customer Service More Personal 14 LinkedIn: How Big Data Is Used To Fuel Social Media Success 15 Microsoft: Bringing Big Data To The Masses 16 Acxiom: Fuelling Marketing With Big Data 17 US Immigration and Customs: How Big Data Is Used To Keep Passengers Safe and Prevent Terrorism 18 Nest: Bringing the Internet of Things into The Home 19 GE: How Big Data Is Fuelling the Industrial Internet 20 Etsy: How Big Data Is Used In A Crafty Way 21 Narrative Science: How Big Data Is Used To Tell Stories 22 BBC: How Big Data Is Used In The Media 23 Milton Keynes: How Big Data Is Used To Create Smarter Cities 24 Palantir: How Big Data Is Used To Help The CIA And To Detect Bombs In Afghanistan 25 Airbnb: How Big Data Is Used To Disrupt the Hospitality Industry 26 Sprint: Profiling Audiences Using Mobile Network Data 27 Dickey's Barbecue Pit: How Big Data Is Used to Gain Performance Insights Into One Of America's Most Successful Restaurant Chains 28 Caesars: Big Data At The Casino 29 Fitbit: Big Data In The Personal Fitness Arena 30 Ralph Lauren: Big Data In The Fashion Industry 31 Zynga: Big Data In The Gaming Industry 32 Autodesk: How Big Data Is Transforming The Software Industry 33 Walt Disney Parks and Resorts: How Big Data Is Transforming Our Family Holidays 34 Experian: Using Big Data To Make Lending Decisions And To Crack Down On Identity Fraud 35 Transport for London: How Big Data Is Used To Improve And Manage Public Transport In London 36 The US Government: Using Big Data To Run A Country 37 IBM Watson: Teaching Computers To Understand And Learn 38 Google: How Big Data Is At The Heart Of Google's Business Model 39 Terra Seismic: Using Big Data To Predict Earthquakes 40 Apple: How Big Data Is At The Centre Of Their Business 41 Twitter: How Twitter And IBM Deliver Customer Insights From Big Data 42 Uber: How Big Data Is At The Centre Of Uber's Transportation Business 43 Electronic Arts: Big Data In Video Gaming 44 Kaggle: Crowdsourcing Your Data Scientist 45 Amazon: How Predictive Analytics Are Used To Get A 360-Degree View Of Consumers Final Thoughts About the Author Acknowledgements Index . 520 $a"The best-selling author of Big Data is back, this time with a unique and in-depth insight into how specific companies use big data. Big data is on the tip of everyone's tongue. Everyone understands its power and importance, but many fail to grasp the actionable steps and resources required to utilise it effectively. This book fills the knowledge gap by showing how major companies are using big data every day, from an up-close, on-the-ground perspective. From technology, media and retail, to sport teams, government agencies and financial institutions, learn the actual strategies and processes being used to learn about customers, improve manufacturing, spur innovation, improve safety and so much more. Organised for easy dip-in navigation, each chapter follows the same structure to give you the information you need quickly. For each company profiled, learn what data was used, what problem it solved and the processes put it place to make it practical, as well as the technical details, challenges and lessons learned from each unique scenario. Learn how predictive analytics helps Amazon, Target, John Deere and Apple understand their customers Discover how big data is behind the success of Walmart, LinkedIn, Microsoft and more Learn how big data is changing medicine, law enforcement, hospitality, fashion, science and banking Develop your own big data strategy by accessing additional reading materials at the end of each chapter "--$cProvided by publisher 650 0$aConsumer behavior 650 0$aStrategic planning 650 0$aBig data 907 $a.b14458287$b31-05-22$c31-05-22 912 $a991000349779707536 945 $aLE026 658.0557 MAR 01.01 2016$g1$i2026000135793$lle026$nProf. Elia G. / Progetto$op$pE43.08$q-$rl$s- $t4$u0$v0$w0$x0$y.i16031581$z31-05-22 996 $aBig data in practice$91994359 997 $aUNISALENTO 998 $ale026$b31-05-22$cm$da $e $feng$gnju$h0$i0 LEADER 01101nam0-22002771i-450 001 990007534180403321 005 20250430124540.0 035 $a000753418 100 $a20030814d1988----km-y0itay50------ba 101 0 $aita 102 $aIT 105 $ay-------001yy 200 1 $aRisultati di un'indagine su alcuni aspetti socio - strutturali delle collettivitą italiane di Toronto e di Montreal$fdi Franca Farnocchia Petri 210 $aMilano$cFranco Angeli$d1988 215 $ap. 204 - 228 225 1 $v23 cm 300 $aEstr. da: Atti del Convegno Le societą in transizione : italiani ed italo - canadesi negli anni ottanta (Montreal, 9 - 11 giugno 1988) / a cura di Raimondo Cagiano de Azevedo 610 0 $aCanada$aImmigrati italiani 700 1$aFarnocchia Petri,$bFranca$0129687 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aLG 912 $a990007534180403321 952 $aMISC.F 0083$bIst. s.i.$fILFGE 959 $aILFGE 996 $aRisultati di un'indagine su alcuni aspetti socio - strutturali delle collettivitą italiane di Toronto e di Montreal$9684995 997 $aUNINA