Krishna Tewari Global Head

Digital Publishing & Retail solutionsDatamatics Global Services Ltd

Leveraging Big Data Opportunities for Growth

Challenges for publishers

Big Data in publishing industry

The technology landscape

Use cases for publishing

Planning for Big Data

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Thisis‘TheLibraryofAlexandria’HeretheEgyptiansoncecollectedandmanagedeveryscrollofinformation

thenavailableintheworld

The classical content

Artist:O.VonCorven,Source:Wikipedia

Newsroom www.telegraph.co.uk

The Publisher’s tilt

challenge is to bridge the chasm ahead….

Challenges for publishers

Big Data in publishing industry

The technology landscape

Use cases for publishing

Planning for Big Data

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Data & content in the publishing worldStructured Semi structured Unstructured

Content

DatabasesXMLFilesPDFsHeadersMetadata

ImageBanksApplicationFilesAdvertsFeeds

InfoGraphicsAudioVideoContentsharingRatings

Readers/ContentConsumers

SubscriptionsCustomerInformationCRMData

PurchaseHistoryDemographicsServiceLogs

ReadingModesInterestAreasBuyingPatternsSearches,eMailsSpendAnalysis

LikesTweetsSharesRatingsReading,Chats

SalesChannels

GeoSpreadPublicationtypePerformance

GeographicalPerformance CampaignDataDiscountsBundledoffersGeopreferencesChanneldata

HitcountsEventsSurveysMarketingcopiesTestruns

Authors/Dataproviders

AuthorDatabases ContractsPermissionsRights

MarketperformancesSubjectexpertiseQualificationsAffiliationsEmails,Payments

TweetsSharesPeerReviews

80 % data existing in any enterprise today is unstructured

What Consists of Big Data?

Big DataIntegration

Big Transaction Data Big Interaction DataT i l D

records

Transactional Data:Orders, Invoices, Payments, Plans, 

Deliverables, Travel records

Other Interaction Data

Big Data Processing

Analytical Data:Historical Data, Machine Streams, Clickstream 

data, Log files

Volume

Velocity

Variety

Complexity

Big Data is the confluence of the three trends consisting of Big Transaction Data, Big Interaction Data, and Big Data Processing

Challenges for publishers

Big Data in publishing industry

The technology landscape

Use cases for publishing

Planning for Big Data

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Agenda

Big Data Technology Landscape

Challenges for publishers

Big Data in publishing industry

The technology landscape

Use cases for publishing

Planning for Big Data

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Use Case: Large Scale Data Archival

Data segregated in disparate platforms in different fileformats can be acquired & organized easily using Big Data

TransactionalData

PublishingHouseHistoricalData• MillionsofImages• MillionsofDataFiles• Thousandsofarticles

fromhundredsofauthors

ContractsBoard

CommentsMails&Tweets

IntegratedDataRepository

(PoweredbyBigData) Automaticallyindexedand

taggedandmadeavailableforendusersthroughaportal

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 online 

users, 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 articles

Source: http://is.gd/oyEu01

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 readers 

free 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 of 

feasibility• 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 TB 

of data to users instantaneously

Source: http://is.gd/kMqKSe

Use Case: Leveraging Value in Social Media

GoodReads Reviews

FacebookPageLikesandComments

NoofTweetswithhashtagofbookname

Source:Twitter,Facebook,GoodreadspagesofRailSea[Author:ChineMieville,Publishers:RandomHouse]

Publishing Companies can leverage Big Data to aggregate and track social data in real time

Case Study: Personalizing Interactions at De Persgroep

• 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 radio 

channels– With users accessing content through multiple devices (iPad, Kindle, iPhone) consumer 

data outgrew the bounds of siloed solutions• Solution

– Customer used Lily 2.0 (with help from NGData – customer intelligence management company) to get an intelligent view on how customers are leveraging the content generated by the group

• Creating personalized interactions, messages, and offers based on user preferences and purchase history

• They realized an increase in Customer Lifetime Value

• Benefits– The adoption enabled De Persgroep to understand viewing and content preference of 

customers, and to create and share timely and relevant content on those lines

Source: http://is.gd/M7lVWw

Challenges for publishers

Big Data in publishing industry

The technology landscape

Use cases for publishing

Planning for Big Data

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Agenda

insights for growing the business

Reader/ContentConsumer

Past Searches

67% - 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 offers

DemographicsProf in Humboldt Universität, BerlinDept of Agricultural entomologyEditor in Chief – Life sciences journal

Customized bills with focused adsUpcoming publicationsDiscounts

Time of readingSubject related searches 10 AM – 4 pmdevice read 8 pm – 10 pmDevice content share – 9 - 9.30 pm80% tweets – 6PM – 7 PM

Customized ad release timingsAd release in devicesDo not disturb timingsTailored call center action

Spend AnalysisTotal monthly spend – euro 350Research articles - euro 250Books -euro 45Journal subscription -euro 55

Ads of publications in price rangeBundled savingsSpend trend and alerts to sales

S i l M diActivity

Social Media Activity

Very active social mediaFB shares – 27% XYZ | 80% ABCTweets – 18% XYZ | 82% ABC

Low share of walletWatch customer surveysAlert customer Account Manager

Reading Device 24% online searches – desktop76% Book reading - iPad

More focus on ipad alerts for booksOffers on ebook versions

DATA ANALYTICS ACTIONS

Big data innovation trends

Source :http://www.constellationrg.com

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 commodity hardware and free solutions

• Striking a balance between the existing technology infrastructure and introduction of Big Data technologies

There is new hope with big data…

Leveraging Big Data Opportunities for Growth

Krishna Tewari Global Head

Digital Publishing & Retail solutionsDatamatics Global Services Ltd

Krishna.tewari@datamatics.com