Ciara-tech Discovery Manuel d'utilisateur

1 An Oracle White Paper January 2014 Oracle Endeca Information Discovery: A Technical Overview

10 Attribute models are mapped into virtual memory. To take advantage of the different sort orders, each attribute index is prefixed with a B-tree-l

11 contain a certain word or phrase—it allows it to return results with all the context that makes them intelligible to users, including matched term

12 A forthcoming Oracle Endeca Information Discovery Performance Whitepaper describes EID’s performance as it scales up to 300M Endeca records on a s

13 relevance strategies based on factors like proximity, position, number of terms matched, number of matched terms, and number of attributes contain

14 Data enrichment is a natural fit for Endeca Server, dovetailing with its strengths in managing jagged and unpredictable data, efficient updates, a

15 their navigation directly from visualization components. Users can employ the Studio application to explore the details behind any aggregates. 

16 Oracle Endeca Information Discovery Integrator: Easily Manage Diverse Data EID provides numerous options for loading diverse and rapidly changing

17 Key benefits of Integrator ETL include:  Reduced manual workload and time  Communication among incompatible systems  Optimized process fo

18 Oracle Endeca Information Discovery Studio: The Art of Visual Discovery Self-Service Data Management Studio builds on the robust data integration

19 Figure 4. A pre-populated app with search box, faceted navigation, chart, and results table. There has been no manual configuration. Figu

2 Contents Introduction ...

20  No modeling required. The provisioning service ingests both spreadsheets and irregular JSON files with nested structures with no demands on th

21 Integrated Discovery Figure 5. This sample analytic application built with Oracle Endeca Information Discovery illustrates how advanced search,

22  Maps. Automatically plots data by geocodes and allows visualization of several layers, including aggregate and heat layers.  Summarization b

23 First, a geographical lasso filter lets users select an area on the map. Second, a search bar lets a user who wants to focus on a certain

24 Third, each dot on the map presents a list of record details when clicked on; values within this popup can be chosen to refine upon. Every com

25  Secure self-service. IT-provisioned data sources like enterprise data warehouses and Oracle BI Server subject areas retain their underlying se

26 security restrictions). Oracle Endeca’s navigation differs from other methods of data navigation in that it assists users in navigating the data w

27 Appendix A: EID Success Stories Many Oracle customers have successfully complemented their existing business analytics investments with Oracle En

28 They built a discovery application for the demand planners that combined the forecasts out of SAS with the actuals from the distribution transacti

3 Appendix A: EID Success Stories ...

4 Introduction The last decade has seen an exponential increase in data volume and complexity, and technologies to help business make sense of this

5 Composable Applications, Purposeful Views Data discovery is a cycle of adding new data, asking new questions, and seeing new patterns. Thus, in da

6  High-dimensional analysis. Oracle Endeca Information Discovery affords superior insight by allowing organizations to unify diverse data from ins

7 Figure 1. Oracle Endeca Information Discovery, an integrated information discovery platform. These components combine to provide a powerful discov

8 Endeca Server organizes data into records. Each record is a sequence of attribute-value pairs. For example, a record with three attribute-value pa

9 schema before they can see the data, Endeca Server builds up a schema as it ingests data, then surfaces that schema with the data for the user to r