Leveraging Big Data Opportunities for Growth


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Mr Krishna Tewari spoke on the Publisher´s Forum 2013 in Berlin about Big Data...

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Leveraging Big Data Opportunities for Growth

  1. 1. Krishna TewariGlobal HeadDigital Publishing & Retail solutionsDatamatics Global Services LtdLeveraging Big Data Opportunities for Growth
  2. 2. Challenges for publishersBig Data in publishing industryThe technology landscapeUse cases for publishingPlanning for Big Data12345Agenda
  3. 3. This is ‘The Library of Alexandria’Here the Egyptians once collected and managed every scroll of informationthen available in the worldThe classical contentArtist: O. Von Corven, Source: Wikipedia
  4. 4. Newsroom www.telegraph.co.uk
  5. 5. The Publisher’s tilt
  6. 6. challenge is to bridgethe chasm ahead….
  7. 7. Challenges for publishersBig Data in publishing industryThe technology landscapeUse cases for publishingPlanning for Big Data12345Agenda
  8. 8. Data & content in the publishing worldStructured Semi structured UnstructuredContentDatabasesXML FilesPDFsHeadersMetadataImage BanksApplication FilesAdvertsFeedsInfo GraphicsAudioVideoContent sharingRatingsReaders / ContentConsumersSubscriptionsCustomer InformationCRM DataPurchase HistoryDemographicsService LogsReading ModesInterest AreasBuying PatternsSearches,eMailsSpend AnalysisLikesTweetsSharesRatingsReading ,ChatsSalesChannelsGeo SpreadPublication type PerformanceGeographical Performance Campaign DataDiscountsBundled offersGeo preferencesChannel dataHit countsEventsSurveysMarketing copiesTest runsAuthors/ DataprovidersAuthor Databases ContractsPermissionsRightsMarket performancesSubject expertiseQualificationsAffiliationsEmails, PaymentsTweetsSharesPeer Reviews80 % data existing in any enterprise today is unstructured
  9. 9. What Consists of Big Data?Big DataIntegrationBig Transaction Data Big Interaction DataTransactional Data:Orders, Invoices,Payments, Plans,Deliverables, TravelrecordsOther InteractionDataBig Data ProcessingAnalytical Data:Historical Data, MachineStreams, Clickstreamdata, Log filesVolumeVelocityVarietyComplexityBig Data is the confluence of the three trends consisting of BigTransaction Data, Big Interaction Data, and Big Data Processing
  10. 10. Challenges for publishersBig Data in publishing industryThe technology landscapeUse cases for publishingPlanning for Big Data12345Agenda
  11. 11. Big Data Technology Landscape
  12. 12. Challenges for publishersBig Data in publishing industryThe technology landscapeUse cases for publishingPlanning for Big Data12345Agenda
  13. 13. Use Case: Large Scale Data ArchivalData segregated in disparate platforms in different fileformats can be acquired & organized easily using Big DataTransactional DataPublishing HouseHistorical Data• Millions of Images• Millions of Data Files• Thousands of articlesfrom hundreds of authorsContractsBoardCommentsMails &TweetsIntegratedData Repository(Powered byBig Data) Automatically indexed andtagged and made availablefor end users through a portal
  14. 14. Case Study : Archiving at RSC• About Royal Society of Chemistry– Europe’s largest society in advances of chemical science• Business Challenge– To organize assets accumulated since 1840s– Content Summary:• 1 million images• Millions of Scientific data files• Hundreds of thousands of articles from 200,000 authors• Recent Captures – Social Media, Video and Digital Assets• Solution– MarkLogic (NoSQL solution) was used to create a repository accessible for RSC’s onlineusers, entrepreneurs, researchers and educators– Content stored as XML documents (using document centric model)• Benefits– Allows RSC to publish 3x times as journals and 4x times as many articlesSource: http://is.gd/oyEu01
  15. 15. Case Study: Converting Large Scale Images in NYT• About New York Times– American daily newspaper, published in New York city since 1851• Business Challenge– NYT decided to make all public domain articles dated 1851-1922 available to the readersfree of charge– 11 million articles available in images were to be converted to PDF format– Previously PDF were generated dynamically. But as traffic scaled this approach ran out offeasibility• Solution– Pre-generating articles & serving them as static files to readers• Amazon S3 as File System• Amazon EC2 for Web Services• Hadoop to convert articles into PDF files• Benefits– NYT were able to save tremendous IT investments and were able to deliver over 1.5 TBof data to users instantaneouslySource: http://is.gd/kMqKSe
  16. 16. Use Case: Leveraging Value in Social MediaGoodReads ReviewsFacebook Page Likesand CommentsNo of Tweets withhashtag of booknameSource: Twitter, Facebook, Goodreads pages of RailSea [Author: Chine Mieville, Publishers: Random House]Publishing Companies can leverage Big Data toaggregate and track social data in real time
  17. 17. Case Study: Personalizing Interactions at DePersgroep• About De Persgroep– Leading Publishing and Broadcasting network in Belgium and Netherlands• Business Challenge– Millions of readers, viewers tune into De Persgroep’s print and digital, TV and radiochannels– With users accessing content through multiple devices (iPad, Kindle, iPhone) consumerdata outgrew the bounds of siloed solutions• Solution– Customer used Lily 2.0 (with help from NGData – customer intelligence managementcompany) to get an intelligent view on how customers are leveraging the contentgenerated by the group• Creating personalized interactions, messages, and offers based on user preferences andpurchase history• They realized an increase in Customer Lifetime Value• Benefits– The adoption enabled De Persgroep to understand viewing and content preference ofcustomers, and to create and share timely and relevant content on those linesSource: http://is.gd/M7lVWw
  18. 18. Challenges for publishersBig Data in publishing industryThe technology landscapeUse cases for publishingPlanning for Big Data12345Agenda
  19. 19. insights for growing the businessReader / ContentConsumerPast Searches67% - LIFE SCIENCES Entomology Coleoptera - 56%Lady bird beetle (72%)Beetles (28%)ad banners in the websiteDisplay Lady bird research articlesDiscount coupons for subject booksCustomize bundled offersDemographicsProf in Humboldt Universität, BerlinDept of Agricultural entomologyEditor in Chief – Life sciences journalCustomized bills with focused adsUpcoming publicationsDiscountsTime of readingSubject related searches 10 AM – 4 pmdevice read 8 pm – 10 pmDevice content share – 9 - 9.30 pm80% tweets – 6PM – 7 PMCustomized ad release timingsAd release in devicesDo not disturb timingsTailored call center actionSpend AnalysisTotal monthly spend – euro 350Research articles - euro 250Books -euro 45Journal subscription -euro 55Ads of publications in price rangeBundled savingsSpend trend and alerts to salesSocial MediaActivityVery active social mediaFB shares – 27% XYZ | 80% ABCTweets – 18% XYZ | 82% ABCLow share of walletWatch customer surveysAlert customer Account ManagerReading Device24% online searches – desktop76% Book reading - iPadMore focus on ipad alerts forbooksOffers on ebook versionsDATA ANALYTICS ACTIONS
  20. 20. Big data innovation trendsSource :http://www.constellationrg.com
  21. 21. Recommended Steps to consider Big Data• Identify the business problem that you are trying to solve• Identify the relevant technology that will be able to address the problem• Break organization silos and form cross functional teams• Assign responsibility to a mix of ‘left brain’ analytical and ‘right brain’depicter type of people• Start small, with proof of concepts playing around with existing commodityhardware and free solutions• Striking a balance between the existing technology infrastructure andintroduction of Big Data technologies
  22. 22. There is new hope with big data…
  23. 23. Leveraging Big Data Opportunities for GrowthKrishna TewariGlobal HeadDigital Publishing & Retail solutionsDatamatics Global Services LtdKrishna.tewari@datamatics.com