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sones company presentation

  1. 1. Create and Uncover Relationships.
  2. 2. About sonessones GraphDBis the first database forcloud computing thatmakes associationsbetween complex data justlike the human brain. (*)e.g.:  Seman-c  Web  data,  workflows,  pictures,  personal  documents,  loca-on,  sensor  data,  eCommerce  items,  Facebook,  TwiAer,  blogs,   mobile  apps,  configura-on  data,  your  email  inbox,  CRM  data  
  3. 3. Company history Series A financing GraphDB as an round with TGFS GraphDB 1.0 open source version Talend data T-Venture Initial proof of à OSE 1.1 – integrationsones GmbHfounded invests concept 5,000 downloads Customer saves during the first Enterprise Edition First on 100 servers month license for telcos,The basicconcept of the customer: T- with version 1.0 web, data analysisDB structure is Online GraphDB Clouddeveloped (prototypes) Start of OEM and Edition on Azure New CEO and partner sales expanded strategy managementFinancing withseed capital3 employees
  4. 4. Information - the capital of today and tomorrow§  How people access information today: •  using the Web (no boundaries, unstructured) or •  using databases (structured, boundaries)§  How people will access information in the future: Sones GraphDB •  using the Semantic Web, ontologies (no boundaries, structured, automated)
  5. 5. The current market 90% of data traffic today is unstructured (worldwide) In 2011, this digital universe will be 10 Videos, photos, times bigger than it articles, user profiles, was in 2006 (IDC news, groups, prediction) events...§  Cloud  compu-ng  data  management’s  unsolved  issues  (Cloud  Compu-ng,  Hype  Cycle,  Gartner):   §  Data  security,  data  portability,  user  controls,  reliability,  concurrency  and  dynamic  connec4ons   between  data  records  (#)  (data  has  to  be  shi:ed  from  one  data  center  to  another  to  process  the   informa4on)  
  6. 6. Database EvolutionGraph-based concepts - latest innovation Olap - and other concepts for real time analytics Graph based Content / Application / Analytics / Search Object. Joe Person Lives in Palo Alto IBM Web Site City Company Relational Database Database Publisher of Subscriber to Fan of Lives in Employee of Sue Niche-products, Jane Person ERP, CRM, … RSS Feed Coldplay Band Fan of Design Person Friend of Dominating the Developers Source of Team Group Member of Married to Bob Depiction of 123.JPG Photo Weblog Person market Author of Dave Member of Person Stanford AlumnaeMember of Depiction of Group Member ofHierarch. Database Nearly “died out” Key value based concepts for search and Web 60s 70s 80s 90s Since 2000 Today Search, Cloud Computing
  7. 7. The database worldThe innovation: Joe Website Person Lives in Palo Alto IBM City Company Publisher of Fan of Subscriber to Lives in Employee of Sue Jane Person Fan of Coldplay Person RSS feed Friend of Band Member of Design Depiction of Married to Source of Team Member Group 123.JPG of Bob Photo Web log Person Depiction of Member of Stanford Member of Dave Author of Alumnae Person Group Member of
  8. 8. What is sones GraphDB?sones GraphDB:§ A new type of object-oriented, graph-based database managementsystem§ Enables efficient storage, management and evaluation of complex,highly connected data records§ Combines the advantages of file storage with the possibilities of adatabase management system§ Unstructured data and information (e.g., video files), semi-structureddata (metadata, e.g., log files) and structured data (similar to SQL) canbe linked to each other, which makes it possible for users to managethis data themselves and evaluate when necessary
  9. 9. What makes us different?Persistence: Flexible dataStorage on a modelingnon-volatile while thestorage system ismedium running
  10. 10. We do it differently§  Information and data are saved in object networks instead of tables.§  The original data structure is maintained.§  New paradigm:§  Linking logic and data. Improved efficiency-real-time.§  New functions for large numbers of queries on highly complex, distributed, dynamic data. •Fewer processing steps required. •Cost advantages, competitive advantages
  11. 11. Universal data access Personalized recommendations Social CRM New database applications Scaling at the push of a button Targeting GraphDB SOAP Web Universal data access REST DAV Automatically generates metadata from Consolidation and links to other Links to your images, videos, music and documents information corporate data Metadata Image data Public profile data … Type Compression Can be linked with Dimensions Camera corporate data on Width Photographer Facebook Relational Height Price Increased data silos Resolution Bit depth … information density Universal access Your data remains Develop your ownno matter where your data consistent even when solutions using a is stored modeled while the flexible system running data structure
  12. 12. Easy to manage Easy-to-learn GQL query language MySQL query SELECT w.word AS wort, k.sig AS sig FROM co_s k, words w WHERE k.w1_id=(SELECT w_id FROM words w WHERE word = “Laptop”) AND k.w2_id=w.w_id ORDER BY k.sig DESC LIMIT 10; Index-based storage, simplifies GQL query storage and search processes FROM Word SELECT Cooccurrences.TOP(10) WHERE Content = ‘Laptop’; Index Can be scaled as No. Subject you like – our … … BeAer   solution easily grows … … … … Performance   with your demands … … =   … … Cost  savings   Rela-onal   Database  SEARCH Increasing  amount  of   connected  data  
  13. 13. Real-time analytics Recognizing and evaluating multidimensional relationshipsUniversal analytics Analysis and prioritization Relevant information
  14. 14. Low TCOHighly scalable Complex queries as in-depth as desired on the GraphDB call for less processing power due to their graph structure Optimized processing power, up to No double data 300% greater performance when storage for data handling processing and semi-structured data evaluationJPEG … $ €
  15. 15. Solution approaches Cross-system duplicate recognition Point of saleReal-time recommendations Analyses of customer behavior e.g.: churn detection 15
  16. 16. Locationssones GmbH sones GmbHHeadquarters RD LabSchillerstraße 5 Eugen-Richter-Straße 4404109 Leipzig 99085 ErfurtGermany GermanyMail: Mail: info@sones.deTel.: +49 (0) 341/ 3929 680 Tel.: +49 (0)361/ 3026 250Fax: +49 (0) 361/ 2445 008 Fax: +49 (0)361/ 2445 008
  17. 17. AppendixApplication examples 17
  18. 18. Web§  Image portal - Increases sales of images since the right image can be found much more quickly or is automatically recommended§  AB testing - Fast and easy evaluation of marketing campaigns Real-time analysis also possible during implementation§  Click-path analysis - e.g., via which paths do customers access the portal 18
  19. 19. Web / content§  Link building – Automatically links relevant pages/ content, checks completeness of references, makes automatic recommendations of links to appropriate pages (according to topic or other criteria).§  SEO – Optimized search results (e.g., with Google). The system does not directly link pages but generates “link chains” that provide the desired depth (e.g., 4 plus x).§  Content management - Providing the right content to the right user in the right context at the right time 19
  20. 20. Universal data access§  Enterprise Search/Enterprise Storage - Access to all data present internally regardless of their data silo. With the option of saving changes in that same location. Supplements internal data with external information from the Web (e.g. blogs/web portals/ social networks).§  Central metadata repository - Universal data access layer, centrally manage corporate data. Link data from diverse editorial sources (images, articles, etc.) 20
  21. 21. Social graph§  Analysis of user behavior - How do visitors/customers behave on the corporate website?§  Customer/user group evaluation§  SRM (social CRM) – Supplementing existing customer data with customer data from sources such as social networks, e.g., Facebook. Intention: to develop a holistic picture of the customer. When customer X calls, sales agents/customer agents can access both the internal customer status as well as information on the customer that they have posted on blogs, social networks, etc. 21
  22. 22. Social net§  Campaign management - Addressing campaigns to the right customers at the right time.§  Automatic categorization (e.g., job profiles for job portals) - Semantic categorization in order to increase the quality of job ads, etc., on the portal.§  Social networks - Real-time friend-of-a-friend calculation. Who do I know through WHOM? Customizable path query with desired depth possible ad-hoc. 22
  23. 23. eCommerce§  eCommerce - Recommendations regarding the right products made to the right customers at the right time (customer-specific advertising), regional targeting. Goal: To increase the number of items sold.§  eCommerce - Optimizing costs by reducing the number of items returned – Automatic recognition of “safe” returns, conducting pre-defined processes, e.g., recommending suitable products, increasing costs for shipping, etc. 23
  24. 24. Social commerce§  Adding social commerce, i.e., recommendations from/to friends in the friendship graph (i.e., also multi- hop!) or§  product graphs (shared shopping possible)§  for members of a group or similar shopping behaviors §  e.g., same brand regarding individual products §  e.g., same interests/groups/rated products 24
  25. 25. Visualization§  Affiliation management – Who is affiliated with which companies? Direct storage of related information such as minutes of meetings, company agreements, etc.§  Visualization – Simple, interactive depiction of relationship networks/connections/relationships. Intuitive use (e.g.,. via Silverlight)§  Geomapping - Linking the data mentioned above with geoinformation Where are customers/subscribers located? (and why?) 25
  26. 26. Miscellaneous§  Recalls, e.g., for cars: Ad-hoc report of all the people who purchased a car in which the defective part is installed.§  Parts tracking – Who installed which part when? Which supplier can deliver a specific product at a certain time for the lowest price?§  Semantic Web – social tagging, processing user generated content, crowd sourcing, social media monitoring 26
  27. 27. CMDB§  Configuration management database •  Definition according to Wikipedia In the IT Infrastructure Library (ITIL) context, a CMDB is a database that is used to access and manage configuration items. All IT resources are classified as configuration items (CI) in the context of IT management. […] In this context, this refers to the existing pool and the interdependencies of the objects being managed. •  Specification: federation (metadata management) / reconciliation (target/ current state comparisons) / mapping visualization / synchronizationsones graphDB can be described as the only real CMDB 27
  28. 28. DisclaimerGeneral DisclaimerThis document is not to be construed as a promise by any participating company to develop, deliver,or market a product. It is not a commitment to deliver any material, code, or functionality, and shouldnot be relied upon in making purchasing decisions. sones GmbH makes no representations orwarranties with respect to the contents of this document, and specifically disclaims any express orimplied warranties of merchantability or fitness for any particular purpose. The development, release,and timing of features or functionality described for sones products remains at the sole discretion ofsones. Further, sones GmbH reserves the right to revise this document and to make changes to itscontent, at any time, without obligation to notify any person or entity of such revisions or changes. Allsones marks referenced in this presentation are trademarks or registered trademarks of sones GmbHand other countries. All third-party trademarks are the property of their respective owners. 28