Organisaties groot en klein, beginnen zich meer en meer te realiseren dat inzicht in (real-time) data helpt

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1 Data Virtualization, power to innovate with Agile data Drs. Patrick Berkhout, Enterprise en Software Architect, Trivento Organisaties groot en klein, beginnen zich meer en meer te realiseren dat inzicht in (real-time) data helpt om behoefte aan bijvoorbeeld grondstoffen te voorspellen, klanten beter te begrijpen en de klanttevredenheid te verhogen. Helaas is in veel gevallen de (real-time) data nog te veel verspreid of bevindt zich in zogenaamde silo s. Hierdoor is de analyse en het gebruik van de data, niet of beperkt mogelijk.

2 Data virtualization Data virtualization, power to innovate with Agile data

3 Agenda Introduction video The data management challenge New paradigm: Data virtualization Example (1) - Customer 360 degrees Example (2) - Enhanced business reporting JBoss Data Virtualization Explore your opportunities Questions and answers

4 Introduction video

5

6

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8 The data management challenge Application dedicated data SQL/NoSQL Database Flat file (xml,csv,xls) On premise/cloud based Big data Distributed data infrastructure Query engines API based Datawarehouse ETL (extract-transform-load) Business ruling Batch driven Many systems sizes structures

9 Common practice(1): application integration/service oriented architecture consumer consumer consumer Service bus manageable message based aggregation done by consumer or service bus

10 Common practice(2): extract-transform-load/datawarehouse consumer reporting query and reporting how to copy big/cloud data? batch, not real time

11 We need a solution to aggregate ALL our data...

12 New paradigm: Data virtualization consumer consumer consumer Consume Compose Connect

13 Example (1): 360 Degrees customer view Single user interface aggregating: ERP instances Cloud application Big data cluster Get all relevant data including statistics Consume Compose Improve handling time, avoid manual data entry Add additional data resources without changing your application Connect Data compositions are reusable ERP - US ERP - EU

14 Example (2): Enhanced business reporting Reporting tools accessing an aggregation of: Datawarehouse ERP Big data Social media Realtime operational data combined with existing Datawarehouse Accessing Big Data silos with recorded business activity Consume Compose Various consumer applications reusing the same Data composition Specific Data compositions on demand Connect DWH ERP BIG DATA recordings

15 JBoss Data Virtualization Connects to all types of datasources and protocols Out of the box: Webservice REST API Webservice SOAP/XML JDBC virtual databases Data modelling using SQL Enterprise open source Open source projects Global community Innovation power Stable releases support

16 Explore your possibilities Business opportunities customer experience operational excellence competitive advantage new business models Capabilities Keep in mind (real time) access to all your data performance underlying resources short feed back loops during development availability underlying resources full range management information lazy or eager transferring of data

17 Data virtualization, power to innovate with Agile data Questions and answers

18 Backup slides

19 Demo 360 degree view Demo steps 1. View EU customers and US customers 2. Modify Data Virtualization Query ERP - US ERP - EU 3. View all customers including salesforce

20 Example (3): Enabling regulatory compliance Data firewall functionality. Improves data quality via centralized access control, robust security infrastructure Consume Reduction in physical copies of data thus reducing risk. Central repository enables transparency and visibility of: enterprise data locations the relationships between the data in various data stores Compose Connect ERP - US ERP - EU

21 Example (4): Fast and unified development of lightweight webservices Webservice Webservice Webservice JBoss Data Virtualization increases agility and loose coupling Act as virtual data stores Multiple business service to acquire data from centralized data layer. Prevents duplication of data access logic: data access logic is maintained in one place Semantic Data Model Centralized and reusable: Data Security Policy Data Transformation Logic Data Integration Logic Consume Compose Connect ERP - US ERP - EU

22 JBoss Data Virtualization: supported Data Sources Enterprise RDBMS: Oracle IBM DB2 Microsoft SQL Server Sybase ASE MySQL PostgreSQL Ingres Enterprise EDW: Teradata Netezza Greenplum Hadoop: Apache HortonWorks Cloudera More coming Office Productivity: Microsoft Excel Microsoft Access Google Spreadsheets Specialty Data Sources: ModeShape Repository Mondrian MetaMatrix LDAP NoSQL: JBoss Data Grid MongoDB More coming Enterprise & Cloud Applications: Salesforce.com SAP Technology Connectors: Flat Files, XML Files, XML over HTTP SOAP Web Services REST Web Services OData Services RED HAT JBOSS MIDDLEWARE

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