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Enterprise Information Management

Enterprise Information Management. SOA Brown Bag #2. Sam Ceccola – SOA Architect. November 17, 2010. Agenda. What is EIM? EIM, SOA and SOE? EIM Key Characteristics Enterprise Information Model EIM Concepts Layered Architecture Data Virtualization Information Understanding

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Enterprise Information Management

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  1. Enterprise Information Management SOA Brown Bag #2 Sam Ceccola – SOA Architect November 17, 2010

  2. Agenda • What is EIM? • EIM, SOA and SOE? • EIM Key Characteristics • Enterprise Information Model • EIM Concepts • Layered Architecture • Data Virtualization • Information Understanding • Information Analytics • Dissemination • Information Governance • Challenges of implementing EIM

  3. Data, Data Everywhere Over the past 5 years, the amount of data we have has grown 10x…

  4. What is Enterprise Information Management? • EIM is a combination of Real-Time Business Intelligence, Traditional Business Intelligence and Enterprise Content Management • Business Intelligence is computer based techniques for turning data into wisdom • EIM provides virtualization and integration of Enterprise Data, utilizing both structured and non-structured data • EIM provides an Enterprise environment for a user to Discover, Manage, Understand, Analyze and Disseminate the information created by the Enterprise

  5. What is the relationship with EIM and SOE? A Service Oriented Enterprise (SOE) is an organization whose business processes and IT infrastructure are integrated across the entire enterprise to deliver on-demand services to customers, partners and suppliers • Enterprise Information Management leverages a SOE environment by utilizing the following characteristics and technologies: • Data Virtualization • Real time and non real-time business intelligence • Model-driven • Enable architectural transparency (e.g., what, where, why, cost, relationships, etc.) • Treat rules, policies and processes as “first class citizens” • Automate Service Governance

  6. EIM Key Characteristics • Enterprise Information Model • Standards Based • Data Virtualization • Event Driven • Decision Support • Trend Analysis • Advanced analytics techniques • Link Analysis • Multi-Dimensional Analysis • Application of real and near real time collection techniques • Application of a common model & structure (Bottom up Modeling

  7. Enterprise Information Model Is a representation of concepts, relationships, constraints, rules and operations to specify information Semantics for an enterprise. Representation in today’s technology utilizes a model known as an ontology

  8. What is in an Ontology? • Individuals: instances or objects (the basic or "ground level" objects) • Classes: sets, collections, concepts • Attributes: aspects, properties, features, characteristics • Relations: ways in which classes and individuals, can be related to one another] • Function terms: complex structures formed from certain relations that can be used in place of an individual term in a statement • Restrictions: formally stated descriptions of what must be true in order for some assertion to be accepted as input • Rules: statements in the form of an if-then (antecedent-consequent) sentence that describe the logical inferences that can be drawn from an assertion in a particular form • Axioms: assertions (including rules) in a logical form that together comprise the overall theory that the ontology describes in its domain of application • Events: the changing of attributes or relations

  9. EIM and Information Modeling • EIM allows for two types of Information Modeling • Top Down – a model is created from an analysis effort • Bottom Up – the system implies a model based on word meanings

  10. EIM Concepts • Layered Architecture • Data Virtualization • Information Understanding • Information Analytics • Dissemination

  11. EIM Concepts: Layered Architecture Access Controls Services Infrastructure Visualization Context / Time Static / Dynamic Smart Phone Annotation Browsers Client UI Cell Information Analytics DData Virtualization (No data duplication necessary) Publish \ Subscribe EIM Metadata Business Data

  12. EIM Concepts: Data Virtualization • Concept for the ability to create a virtual data warehouse that can: • Consume and publish data from the stove pipes in near real time, hence solving the latency issue • Never permanently store the data to disk. Data is in flight, not at rest, which solves the multiple location issue • Provide a multi dimensional model to bring the data together, therefore solving the relationship issue

  13. EIM Concepts: Information Understanding The ability to apply the information consumed from the enterprise to be applied to the model and domain in order to gain an understanding of information contextual meaning.

  14. EIM Concepts: Information Analytics or Once we understand information…How do we turn it into information? EIM allows us to apply context such as relationships, time, space, geography, dollars etc.

  15. EIM Concepts: Dissemination • The ability to disseminate information and analysis of information in a timely fashion to a prescribed set of users • Dissemination can occur in many forms, portal, alerts, RSS, SMS etc.

  16. EIM Concepts: Information Governance The need for information governance is driven by: • Security • PII • Other information privacy policies, perceptions and standards Collect Discover Manage Understand Analyze Disseminate

  17. Challenges of Implementing EIM • Lack of Transparency • Lack of control • Security • Service level

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