How to Implement Semantic Solutions Without Blowing Up Your Company Paul Bradley - SVP, Account Management 1 2 DARPA Milestones u  Communications ARPAnet (TCP/IP) u  Storage : Relational Databases u  Describing DAML-OIL Ontology Web Language Resource Description Framework 3 Data Management u  Create, Store, & Change u  Find u  Integrate u  Analyze 4 Business vs. Development Functional Requirements Technical Requirements Coding & System Test UAT Bug Fixes & Enhancements 5 Big Data Paradigm Shift 6 Rules For The Next 40 Years u  Use - understood by machines u  Locate - descriptions are local u  Standards – interoperability u  Query - access distributed data 7 The Problem Business people require access to data they don't own 8 Why Are Semantic Solutions The Answer? Semantic-based technologies describe enterprise things with precision 9 Why Semantics? u  Relate disparate data - Same thing; different name - Same name; different definition u  Uses abstraction to relate things u  Multiple layers of abstraction are needed 10 Thinking About Your Solution u  Use W3C open standards; no black boxes u  Deploy incrementally, no Big Bang u  Narrow your focus to show an early ROI u  Solve someone’s biggest riddle u  Be sure your solution is extensible 11 Pitfalls and Blind Alleys Turns u  Believing ontologies are hard to build u  Minimizing the need for SME input u  Managing metadata with multiple tools u  Pushing existing BI solutions aside u  Attempting to replace data warehouses 12 Keep in Mind... u  u  Data owners may build brick walls Ontologies describe data in terms understood by business people u  Minimal (or no) hardware requests u  Emphasize data stays where it is 13 And Above All.... Pick an Experienced Partner 14 Revelytix was founded in 2005 to provide enterprises with a robust analytical capability Emergent Analytics u  Non-invasive u  Agile u  Low impact 15 How We Do It u  W3C standards for defining and describing things u  Tools to author / relate definitions and query data u  Create an “Enterprise Information Web” u  u  Allow additional data elements / sources can be added and new relationships defined at any time Use a web-based collaboration tool allowing SMEs and data modelers to work together in real time 16 We have a suite of products enabling you to build an Enterprise Information Web u  Knoodl - web-based ontology development and management u  Spyder - exposes any data structure as RDF u  Spinner - federated, parallel query optimization engine u  Rex - rules validation engine 17 What We Can Do Now SPARQL Queries & Results RDF Data Store LOD Cloud Planner Indexes Planner Data Sources Indexes Optimizer Cache 18 R2RML Mapping Optimizer Cache Exposes any data structure as RDF, accessible using the SPARQL query language u  u  Uses ontologies to map data schemas to standardized RDF descriptions Interacts with Spinner to federate data and optimize query performance u  Exposes full power of SQL u  Reusable by reference 19 Federates a single query across multiple SPARQL endpoints Optimized description-driven, easily incorporated within your existing IT infrastructure u  Supports complex analytics without a complicated infrastructure u  Works with enterprise data where it is stored u  Delegates processing as close to the source database as possible u  20 Rules Engine, executing rules written in Rules Interchange Format u  Essential validation capabilities for results or data sets exposed by Spinner u  Assures policy compliance u  Allows inferencing across data stores 21 Collaborative development tool and EIW registry Most widely used web-based ontology tool u  u  u  Development and visualization: u  Ontologies u  Queries u  Dashboards Repository: u  EIW ontologies u  Enterprise semantic metadata 22 Our Approach u  Determine gaps u  Identify quick hits u  Professional Services u  Organize communities of interest u  Software installation & configuration 23 Why Our Solution? u  Guarantees an immediate ROI u  Adds value to existing IT infrastructure u  Retains benefits from BI investments u  Easily implemented; no data is duplicated u  Quantifiable benefits 24 We Did It In New York 23 25 We re Doing It at the Pentagon 26 We Can Do It for You u  u  Work with your data experts to create ontologies Configure our products to incorporate your company’s data u  Deliver Emergent Analytics for you u  You see results in weeks, not years u  This stuff is real and we can prove it 27 Paul Bradley September 27, 2011 [email protected] 28 29