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Big Data: Where is the beef?

Big Data: Where is the beef?. Drill Through the Hype to get Business Value. Hans-Josef Jeanrond VP Marketing, Sinequa. Where is the Beef. A Mighty Question. increase in revenue for Wendy’s in 1984 the year of the “Where is the Beef” commercial with Clara Peller. 31 %.

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Big Data: Where is the beef?

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  1. Big Data: Where is the beef? Drill Through the Hype to getBusiness Value Hans-Josef Jeanrond VP Marketing, Sinequa

  2. Whereis the Beef

  3. A Mighty Question increase in revenue for Wendy’s in 1984 the year of the “Where is the Beef” commercial with Clara Peller 31% Anticipate this questionin your Big Data plans! Gary Hart loses the Democratic primaries against Walter Mondale who asks “Where is the Beef” looking at Harts enormous case files

  4. Where is the Beef in the Big Data Hype ? Where the Beef ? is

  5. Big Data - Hype and Useless Disputes • Useless: “What is Big Data” If it’s big and varied enough to cause you problems in dealing with it and if it may be relevant for your business: take it as Big Data • False promises: “You will be Rich” The story of the nappies and the beer • The Eternal Promise: “Structure the World to Possess it” • An urban legend! Invented from A to Z • This is the Mediaeval Solution: • The Grail

  6. Big Data - Hype and Useless Disputes Beware: your Grail-quest companions may bethe wrong company for the new Big Data world! Peut-être peut-on illustrer l'idée que les anciens compagnons de route ne sont plus les bons, par un chevalier face à qq équipé d'un smart-phone / d'un GPS / d'une voiture / d'une fusée, ou qq chose dans le genre.

  7. Big Data – One Certainty Big Data ain’t Structured! 80% of enterprise data is text = unstructured = outsidethe grasp of enterprise applications (ERP, CRM, BI, etc...) = inside documents, emails, social Networks, etc. For the Brave who dare to confront many different languages and know how to analyze them And who don’t just look at the meta data of documents!

  8. Where is the Beef in Big Data? Look at just 2 Use Cases: • Creating 360° views • Mapping Implicit Social Networks of Experts What has Big Data got to do with this?

  9. 360° Viewof a Customer Portfolio Contracts Credits Insurances Operations Credit ratings Credit cards Offers (product datasheet) Shares management Info Dunn Emails Contract models Interactions with Call Centers Letters

  10. 360° View: Why Big Data? • Volume: Index billions of transactions and hundreds of millions of documents • Variety: Index transactions, ERP and CRM data, contracts, product brochures, emails, etc. • Velocity: Get it all done fast enough to present an up-to-date view of the customer walking up to you or calling you Real-time is key! Hadoop batch processing is not good enough

  11. Implicit Social Networks? Reveal Implicit Social Networks of Experts • Why? • Find the key experts in a given domain to build successful project teams. • Key experts can help capitalize on existing skills, technology, and developments optimizing R&D organizations, and shortening time to market. • Enterprise Social Networks don’t work: Self-declared expertise in user profiles of Enterprise Social Network is too often out of date, incomplete or exaggerated • How? • Finding the true experts requires looking at their work: • Analyzing publications, project reports, patent filings, HR data and schedules, Enterprise Social Media content, emails, etc. • This analysis requires Natural Language Processing (NLP) capacities to “understand” what topics people have written about.

  12. Implicit Social Networks: Why Big Data? • Analyze up to 500 M documents in different languages • Research and project reports • Patents • Articles in specialized journals • Emails • Etc. • Go though Internal and external databases • Etc.

  13. Automatically link Skills to People -> Expert discovery in Pharma Drugs Diseases Genes Brands MOA Index of tens of thousands of People With Skills = Experts Hundreds of millions of internal and external documents With Skills

  14. Expert Discovery in Manufacturing Components Supply Chain Master Data CompetitorProducts Tools Index of tens of thousands of People With Skills = Experts Hundreds of millions of internal and external documents With Skills

  15. Expert Discovery in Finance Loans CreditCards CreditRisk Central Bank Real Estate Index of tens of thousands of People With Skills = Experts Hundreds of millions of internal and external documents With Skills

  16. Now for the Beef • 360° Customer View • Call Center: 60 M€ / year • Customer facing agents and managers in branch offices: >11,6 M€ in year 2; >13 M€ in year 3 • Revealing Implicit Social Networks • Siemens: “one successful Search can save tens and even hundreds of thousands of Euros” • Atos: “The benefit is ‘beyond ROI’ – we can’t do without it.” • AstraZeneca: “Ask Nick” (Nick Brown)

  17. How do you get at the beef?

  18. A unique positioning in the Big Data ecosystem REAL TIME • Unlike Hadoop Big Data • High Performance, • Extreme Scalability • Search, Discovery &Visualize • Structured and unstructured data • 120 Connectors • Unlike NOSQL Search • Deep content analytics • Unique Semantic & Natural Language • ProcessingEngine Analytics

  19. Sinequa- More Beef and more Fun REAL TIME AND Big Data Sinequa - the ANDCompany AND Search AND Analytics More fun to work with AND

  20. Sinequa - the ANDCompany Don’t buy a comb with missing teeth All the ANDs are necessary!

  21. MERCI Hans-Josef Jeanrond VP Marketing, Sinequa

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