oracle endeca

7/27/2019 Oracle Endeca

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1 | 2012 Oracle Corporation

Explore All Relevant Data

Introducing Oracle Endeca Information Discovery


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Data Volume, Variety Growth Presents New Challenges

More and

Different Data

Rapid growth instructured and unstructured,

internal and external data

More

Unanticipated

Questions

Self-service ability to exploredata, add new data, and construct

analysis as required

More Change andUncertainty

Unanticipated business needscant be addressed by predefined

models, dashboards, and reports


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Challenge

Challenges To Getting Value From More Variety, Volume

Data variety makes conformingsources to a single modelmore difficult, increasingproject labor costs

Time And Cost Of Modeling

= $Uncertainty And Change

Non-Technical Users

!

!

Changes in integration and

visualization requirementsforce trade-offs between delayand rapid user adoption

Business people with domainknowledge to ask the rightquestions cant write thequeries to express them


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SolutionChallenge

Information Discovery Overcomes These Obstacles

Data variety makes conformingsources to a single modelmore difficult, increasing laborcosts

Time And Cost Of Modeling

= Uncertainty And Change

Non-Technical Users

Changes in integration and

visualization requirementsforce trade-offs between delayand rapid user adoption

Business people with domainknowledge to ask the rightquestions cant write thequeries to express them

Technology that derives itsmodel from the data itself,doing much of the modelingwork on its own

Rapid prototyping in

collaboration with thebusiness to uncover andfulfill latent requirements

Zero-training interfaces thatbring consumer userexperience innovations toenterprise software

!

!


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Interactive Exploration and Discovery

User experience optimized to foster discovery

Advanced Search Search look-ahead Spell-correction Data-driven filtering

Visual Analysis Charting & crosstabs Geographic visualization Tag clouds

Faceted Navigation Select attributes, like a web site+ +


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Simplicity of Search, Power of Analytics

Walk-up ease of use Derived from 10 years of e-

commerce consumer userexperience

Search + Faceted Navigation +Visual Analysis

Search and select attributes, like aweb site

Interactive Exploration Responsive Endeca Server


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BI And Data Discovery Are Peers

Proven Answers ToKnown Questions

Business

Intelligence Fast Answers ToNew Questions

Data

Discovery

Drives need for

Creates new KPIs for


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Oracle Endeca Information Discovery

A platform for data discovery applications across the enterprise

Endeca Information Discovery(EID) helps organizationsquickly explore all relevant data

Combine structured & unstructureddata from disparate systems

Rapidly assemble easy to useanalysis applications

Automatically organize informationfor search, discovery & analysis


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Discovery Application Lifecycle

Structured

Semi-Structured

Unstructured

Diverse and changinginformation

Automatically unified andenriched in Oracle Endeca

Server no predefinedmodel required

Drag-and-drop applicationcomposition

Interactive search,navigation and analytics

for exploration andanalysis


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Integration Suite

Lightweight ETL with nativeEndeca Server connectivity

Java SDK for extensibility easilyconnect to additional data feedsand APIs

Modules for unstructured data: Text Enrichment Sentiment Analysis Content Management System

Connectors


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Oracle Endeca Information Discovery Integrator

Eclipse-based UI Standard ETL functions, And Endeca-specific

Discovery functions /connectivity into EndecaServer


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Key-Value Store Model No segmentation into tables No overarching schema

Simple concepts: Attributes like columns, except may be sparse,

multi-valued, hierarchical

Records each record is an arbitrary collection ofattribute/value pairs, identified by a spec attribute Accommodates:

Idiosyncratic structure!each record is self describing, has its own possiblyunique schema

Multi-valued fields Unstructured fields

Faceted Data Model

Enables easier loading and update of data from any source !?*6@ A BCDCE F0&./3-6@ A GHI J1-#+&08 A K&/*-1)* L)


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Faceted Data Model: Structured Data

Structured data can be easily and directlyloaded into a faceted model via ETL!

Each Tuple becomes a Record Each Column becomes an Attribute

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Semi-structured data from enterpriseapplications, feeds, XML sources, etc. caneasily be loaded as attribute/value pairs

This is a common cause of heterogeneousrecord structure

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Unstructured data can be linked to Records by anyavailable key

Or unstructured elements can be stored as theirown Records for side by side analysis

Accommodates documents, RSS, Twitter,Facebook, forums, etc..



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Any unstructured attribute can beenriched using text analytics toexpand the structure of its containingrecord

Common techniques include: Automatic tagging Named entity extraction Sentiment analysis Term extraction Geospatial matching



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Studio

Interactive, visual Discoveryenvironment

Drag-and-drop configuration Full-featured component library Based on best practice UI design

patterns

Built on Java portal technologystandards


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Application Construction is More Like a Domain

Expert Conversing with the Data

Encourages discovery,to gain new insights

Fast to extend andchange

Quickly iterate on newdata as it arrives

Rapidly respond tobusiness changes

Nocoding

required


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Oracle Endeca Server

Hybrid search-analytical database Search, navigation,

and analytics on diverse,changing information

Architected for Discovery Faceted data model Columnar storage In-memory analytics


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Endeca Server | Scalability and Performance

Multicore query parallelism increasescale and reduce latency with additionalcores

In-memory caching of hot working setof column segments, and query results

Per-attribute columnar storage Range of built-in automatic compression

techniques Prefix, String Coding, Run Length, Delta,,

Variable Length Numeric Coding, etc!

Generational updates

Endeca Server

Disk

RA

M

Cores

CompressedColumnar

Physical Storage

Multi-coreData ParallelQuery Engine

Data Cache Query Cache

Date

Category

!


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First Enterprise Solution For Data Discovery

Combines structured and unstructured data,inside or outside the company

In-memory performance, but not memory bound Solution for provisioning targeted discovery apps


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Model-As-You-Go Deployment in CPG

Derives own model from the incoming records anddocuments

Changes in data automatically appear in UI Drag-and-drop app composition


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Consumer Ease-of-Use at Land OLakes

Integrated search, faceted browsing and analytics Faceted browsing across diverse data Faceted analytical model encourages exploration


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