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BI architecture presentation and involved models (short)

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BI architecture presentation and involved models; doesn't include Big Data vision but can be easily extended

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BI architecture presentation and involved models (short)

  1. 1. BI ARCHITECTUREWhat is asserted without proof can be denied without proof.(Euclide)BI Architecture – March 2013 - Author: Thierry de Spirlet1
  2. 2.  Why Architecture Architecture will permit to organize systems and information Incorporate Best Practices Defines Hardware, Software and Environmental components that areneeded to build end-to-end solutions to help meet specific businessneeds Identify Building blocks Spans all industries and all solution Areas Provides a common language and facilitates collaboration BI Reference Architecture is a framework for developing BI solutions. BI solutions will not exist if there are no business interrogations.BI Architecture – March 2013 - Author: Thierry de Spirlet2
  3. 3.  BI Architecture components Models Processes Scheduling Monitoring Project organizationBI Architecture – March 2013 - Author: Thierry de Spirlet3
  4. 4.  Models A model is an abstraction and reflection of the real world. Modeling gives us the ability to visualize what we cannot yet realize. Several forms of models exist: Data Model to organize data Business models to organize business activities Process models to organize interactions The primary aim of a data model is to make sure that all dataobjects required by the business are accurately and fullyrepresented.BI Architecture – March 2013 - Author: Thierry de Spirlet4
  5. 5.  Models used in BI solutions OLTP Models: Model optimized to support OLTP Application using in production area; these models mustsupport operations and describes the tables, columns, and keys of a database that storesoperational data. E/R model: this is an Entity - Relation diagram; this diagram will represent real entities with all of their relations;this diagram should be 3NF Dimensional Diagram: this model will represent information by using facts and dimensions with the lowest level ofgranularity Datamart modeling: this model is a model permitting data access optimization and presentation from dimensionalmodels Data Vault model: Data Vault model is a particular approach to structure an EDWBI Architecture – March 2013 - Author: Thierry de Spirlet5
  6. 6.  BI Layers BI Layers are present to organize data in the best way for aparticular usage; these presentations will also prepare data in thebest way and prepare information for the next layerBI Architecture – March 2013 - Author: Thierry de Spirlet6
  7. 7.  BI Processes Bi processes are all of these processes used to load, transform andload data; This will include also a complete process premitting: Data Optimization Data Correction Business Process permitting to data process models such as: Costing models Pricing models Operational modelsBI Architecture – March 2013 - Author: Thierry de Spirlet7
  8. 8. SourceSystems•Databases•Flat Files•Web Services•… VariousmodelsExtract AreaConceptualisationArea•Integrate concepts• ERD ModelDataWarehouse•Organize facts &dimensions• DimensionalModel or DVModelDatamarts•Optimize dataAccesses• Dimensionalmodel withAggregationAbstractionLayer•presentationmodelExploitationareaCleasing areaLT CorporateStorage AreaBusiness BusinessBusiness Enrichment ProcessesLayer:•Large Enterprises•Medium Enterprises•Small EnterprisesLayer:•Large Enterprises•Medium Enterprises•Small EnterprisesLayer:•Large Enterprise•Medium Enterprises•Small EnterprisesaLayer:•Large Enterprises•Medium Enterprises•Small EnterpriesLayer:•Large Enterprise•Medium Enterpries•Small EnterpriesLayer:•Large Enterprise•Medium Enterprises•Small EnterprisesBI Architecture – March 2013 - Author: Thierry de SpirletLayer:•Large Enterprises•Medium Enterprises•Small Enterprises= OptionalBI Processes8
  9. 9. Extract Area ConceptualisationAreaData Warehouse DatamartsBI Architecture – March 2013 - Author: Thierry de Spirlet• Pure extraction• BasicTransformation• Output area•Working Areas•Cleasing &DQ•Output area•Working Areas•Cleasing &DQ•Output area•Working Areas•Cleasing &DQ•Output area9
  10. 10.  Explaining Model content OLTP Models: Data is organized to optimize transactions; various models exists ERD Models: Data is organized around conceptual entities; achieve processing and data storage efficiency by reducing data redundancy (storing data elements once) provide flexibility and ease of maintenance protect the integrity of data by storing it once If existing, must Integrate natural key substitution; 3FN; default/dummy values Dimensional models: Data are organized around concept of facts and dimensions; if not yet done, must integrate natural key substitution; 3FN; default/dummy values; surrogatingdimensions (never surrogating in an ERD Model) Presentation models: Data are organized to optimize exploitation of organized dataBI Architecture – March 2013 - Author: Thierry de Spirlet10
  11. 11.  Explaining Layers Extract area: place where all data will be initially loaded; permit to reduce stress on source systems Conceptualisation Area: Place where data is organized around conceptual entities and their relations; achieve processing and data storage efficiency by reducing data redundancy (storing data elementsonce) provide flexibility and ease of maintenance protect the integrity of data by storing it once Implement basic data rules on data (Caps, Trim, …) Implement business rules rules on data Datawarehouse: Place where data are organized around concept of facts and dimensions for theenterprise, calculations and transformations are done at the lowest granularity level (if multi-dimensionmodel) Implement basic data rules on data (Caps, Trim, …) if no conceptual level Implement business rules rules on data if no conceptual level Implement classical datawarehouse concepts: facts & dimensions Datamarts: Place where data are stored to optimize their final processing; can limit set of data usedBI Architecture – March 2013 - Author: Thierry de Spirlet11
  12. 12.  Risks associated to ERD Models End users cannot understand or remember an ERD model. End users cannot navigate an ERD model. There is no graphical user interface (GUI) that takes a general ER model andmakes it usable by end users. Software cannot usefully query a general ERD model: Cost-based optimizers that attempt to do this are notorious for making the wrongchoices, with disastrous consequences for performance. Use of the ERD modeling technique defeats the basic allure of data warehousing,namely intuitive and high-performance retrieval of data. ERD Models are time-consuming while building this level correspond to a conceptual reverse-engineering of sourceapplications and highly coupled with business concepts.BI Architecture – March 2013 - Author: Thierry de Spirlet12
  13. 13.  Risks associated to Data Vault Models Not appropriate to End users End users cannot navigate a Data Vault model. Software cannot usefully query a general Data Vault model due tothe numerous present tables Data Vault Models may be time-consumingBI Architecture – March 2013 - Author: Thierry de Spirlet13
  14. 14.  Techniques used for Models OLTP Models: Denormalization ERD Models: Normalization; natural key substitution; 3NF; historization without updatepropagation (see later) Dimensional models: Facts with business logic (e.g. distribution, ventilation, aggregation, …),dimensions (with associated techniques such as SCDx, surrogatingdimensions); mini dimensions;… Presentation models: Data are organized to optimize exploitation of organized dataBI Architecture – March 2013 - Author: Thierry de SpirletIt is essential to associate the right model to the right layer14
  15. 15.  In summary, choosing the right BI landscape is essential since thebeginning Implementing the right model at the right place is mandatory Revamping an existing BI landscape is extremely cost and timeconsuming, it is fundamental to well design it from the beginning. Architecture will define how to do things and should becustomisable for different situations.BI Architecture – March 2013 - Author: Thierry de SpirletIN CONCLUSION15

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