Research Topics in Computing Data Modelling for Data Schema Integration 1 March 2005 David George

Data Integration2 Modelling & Data Integration Key Elements of today’s Presentation Key Drivers for Data Integration Dimensions and Issues in Integration Three Integration Approaches David George

Data Integration3 Drivers for Data Integration David George

Data Integration4 Drivers for Data Integration (1) Organisations evolving as global entities with distributed data. Systems characterised by mix of legacy and new databases and applications. Organisational change : Organic growth – size and diversity. Business re-engineering. Corporate mergers and acquisitions. David George

Data Integration5 Drivers for Data Integration (2) Organisations evolved as collections of distinct, autonomous departments with disconnected systems e.g. in financial services. Trends in Business Intelligence initiatives: Decision-making support. Customer segmentation. Marketing strategies. Development of distributed or multidatabase systems. David George

Data Integration6 Dimensions and Issues in Integration David George

Data Integration7 Architecture & Design Issues Multidatabase systems can be classified in two ways: Homogeneous systems – local databases having same techniques and language. Heterogeneous systems – local databases demonstrating diverse data models and language. Key Dimensions in systems heterogeneity System heterogeneity – hardware, OS, DBMS Semantic heterogeneity - models and data David George

Data Integration8 <<<< << Check Design >> >>>> Why Heterogeneity/Conflict? Translating conceptualisations of the real world into database world representations David George

Data Integration9 Research Work Conceptualised Books Model (a) The data of interest is about Books, their Publishers and adopting Universities. Publications Model (b) The data of interest is about Publications and their Types David George

Data Integration10 Publisher Topics BookUniversity Keywords Publication Published by Adopted by contains Refer to Title Word Title Name Code Name Address City Code Research Area Publisher David George Books Publications

Data Integration11 Keywords Word Publisher Topics BookUniversity Topics Publication Published by Adopted by contains Refer to Title Name Title Name Code Name Address City Code Research Area Name Publisher Published by David George A B

Data Integration12 Publisher Topics BookUniversity Publication Published by Adopted by Refer to Title Name Code Name Address City Code Research Area Published by David George Books and Publications Integrated contains

Data Integration13 Semantic Heterogeneity/Conflict Structural Conflicts Generalisation versus Specialisation Conflicts. Entity versus attributes. Naming conflicts. Attribute (Domain) Conflicts Data Type conflicts. Measure and Scale conflicts. Integrity, Presence & Absence. Data Values David George

Data Integration14 Semantic Heterogeneity/Conflict Generalisation/Specialisation Conflicts. (i.e. Structural) Naming conflicts. Synonyms e.g. vs Homonyms e.g. vs CustomerClient Market (Products) Market (Customers)

Data Integration15 Semantic Heterogeneity/Conflict Data Type (representation) conflicts. Student (integer or string) Student -No vs Name (integer or string) Measure and Scale etc conflicts. Dimension -volume vs weight Measure -light years vs miles Scale -miles vs kilometres Precision -1:100 versus A:E Date -dd/mm/yyyy vs mm-dd-yy ??? David George

Data Integration16 Semantic Heterogeneity/Conflict Integrity Constraints e.g. Age Range 18 Referential conflict 1:1 vs 1:M (e.g. 1 invoice for 1/ M orders) Presence/Absence. No null, nulls – e.g. optional No corresponding attribute Data Values Same items different values David George

Data Integration17 Integration Approaches David George

Data Integration18 Integration Approaches Federated Database (Multidatabase) Systems. Data Warehouse (Materialised in house) Systems. Mediators (Virtual integration) Systems. David George

Data Integration19 Federated Database Systems David George

Data Integration20 Federated Databases (1) David George

Data Integration21 Federated Databases (2) A Class of heterogeneous databases that: Consist of both new and old systems. Previously existed in their own stand-alone (autonomous) environments. Integration is a consequence of distribution. Organisation can adopt different architectures i.e. the way databases are mapped together: Loosely Coupled integrations. Tightly Coupled integrations. David George

Data Integration22 Federated Databases (3) Tightly Coupled Federations Federation administrator determines schema view for all component systems in the federation. Negotiates export schemas (tables and attributes) from federation participants who control exports of local schemas. Local schema exports integrated as a federated schema. Less autonomy at federation user level for view creation. David George

Data Integration23 Federated Databases (4) Loosely Coupled Federations The federated component databases have a greater degree of autonomy. No central schema view is imposed on users. Federated user is effectively an administrator creating views. User employs a MDB Query Language (v TC schema integration). David George

Data Integration24 Federated Databases (5) Sharing is made explicit by allowing export schemas from the local or component database. The export schemas are imported to the federation to represent the shareable federated database. Each source can call on others for information. FDBMSs differ from homogeneous Distributed DBMSs – they use the same data model and DBMS. DDBMSs sharing is therefore implicit. David George

Data Integration25 Data Warehousing Systems David George

Data Integration26 Data Warehousing (1) Local Operational Warehouse Decision Support & Mining NetworkInternet Integration & Storage David George R3R2

Data Integration27 Data Warehousing (2) Represents the physical separation of operational and decision support environments. Operational data provides the raw material for: Decision support systems. Data-mining (DM). E.g. identifying trends or characteristics. DM = process of “non-trivial extraction of implicit, previously unknown, and potentially useful information”. David George

Data Integration28 Data Warehousing (3) Warehouse integrates multiple, heterogeneous data sources - e.g. Relational DBs, flat files. Data is pre-fetched into a central or intermediate warehouse repository by mediation process. Data is “cleaned” and data integration techniques applied e.g. filtered, joined or aggregated. Data may be transformed to conform to the warehouse schema. Provides consistency in naming conventions, data structures, attributes, etc. David George

Data Integration29 Data Warehousing (4) Data then stored (materialised) in warehouse repository – possibly in separate data marts. Result is a repository of synthesised data for management decision-making. Queries are made over the repository’s global schema. Information is independent from the source data. Data extraction tends to be periodically. David George

Data Integration30 Mediator (+Wrapper) Systems David George

Data Integration31 Mediator Systems (1) Mediator NetworkInternet David George Query Translation

Data Integration32 Mediator Systems (2) Global schema created and mapped to the source schemas. User makes queries over global, mediated schema. Mappings can be either: Global-as-view (GAV). Local-as-view (LAV). Mediator translates global schema query and reformulates it into sub-queries of local schemas. Wrappers execute and return. David George

Data Integration33 Mediator Systems (3) Wrappers standardise how source information is described and accessed (i.e. they translate or adapt). Query answers are returned to the user on demand – after sources are interrogated. Thus data is always up-to-date (v. Warehousing). Mediators integrate information view, without integrating the source data. David George

Data Integration34 Mediator Systems (4) Results in a homogeneous information source using views - based on the mediated (global) schema. Integration is virtual i.e. retrieved by the mediator but not stored in any central repository. Differs from Warehousing Queries – where made to materialised data. In short – provides virtual source schema integration via schema mapping and integrated view. David George

Data Integration35 Comparisons David George

Data Integration36 Federation versus Warehousing & Mediation Federation represents a more “static” approach – using agreed couplings to allow view creation. Warehousing and Mediation addresses integration in a more “dynamic” way – using extraction, transformation and integration processes. David George

Data Integration37 Warehousing vs. Mediation Warehouse: Update-driven: i.e. in warehouse repository Heterogeneous data is integrated in advance and stored in- house for direct query and analysis. Mediation: Wrapper and Mediator layer on top of source DBs. Query-driven: Query to mediated schema then translated into queries appropriate to sources. Results integrated into a global answer set. David George

Data Integration38 Summary David George

Data Integration39 Summary Drivers for Data Integration Organisational change. Business Intelligence and Strategies. Integration Issues Different Conceptual Model representations. Resulting Semantic Heterogeneities. Integration Approaches Federated Systems. Data Warehousing and Mediator Systems. David George

Data Integration40 Next step …… David George

Data Integration41 Research Resources Reference Material Journals Books Presentation slides UCLAN Website Internal: External: David George