HPE IDOL Technical Overview - july 2016

HPE IDOL Technical OverviewSearch and Analytics Platform for Text and Rich Media

April 2016

Open Innovation is transforming everything

Closed technology architecture design

After-the fact static analytics, e.g.Monthly reporting

Analyze data at rest

Real-time insight & understanding via machine learningPut data science into your processes Next-gen appsand services

Analyze and apply perishable dataanywhere at any time

Premise-based systems

Seamless blending of open source, advanced technology, deployment choices

Contain Cost Create Outcomes

Traditional Data Analytics Open Innovation Data Analytics

Journey to the New Style of Business

PresenterPresentation NotesEvery customer will need to find the Sweet Spot

How do we help them Lower the cost of terrestrial hosted workloads, hardened systems and networks and protecting their most precious data in the data center

All while creating the opportunity to accelerate the creation of new services, predict where the new threats will come from and provide continuous delivery of real-time insights.

Human data

Connected people, apps and things generating massive data in many forms

Machine data

Business data

faster growth than traditional business data

10x

PresenterPresentation NotesToday, being data driven is about: Harnessing all the relevant data available today and in the future including business, human and machine Democratizing the data by empowering and delivering insights for all stakeholders collaboratively in your organization from LOB leadership, operations, line workers, etc. irrespective of level or function, in-real time, at the moments that matter Operationalizing analytics through many applications, resulting in better results across your entire business/operations

Achieving greater value through insight and foresight analytics answering why did something happen? or what will happen? instead of just reactively what happened, so you can take action and be proactive

In yesterdays data driven enterprises, analytics and insights were limited to (and for) traditional business data the data generated from business-process applications like CRM, ERP, HRM, and supply chain. But as we have all seen, the data landscape has been radically changing over the past few years 90% of the data available today was created in just the last 2 years - and the landscape will continue to change due to the fastest growing data segments: Human and Machine.

Human data includes all the content we create some of which is highly regulated for compliance purposes (contracts, legal docs) , but much of it is social media, emails, call logs, images, audio, and video.

Machine data is the complete opposite of Human. Its the high-velocity information generated by the computers, networks, and sensors embedded in just about everythingthe Internet of Things.

Together, Human Data and Machine Data are growing 10x faster than traditional Business Data, and organizations that are data-driven are not only able to leverage this data to create new value, but they are able to bridge the interconnection of data across the silos and repositories for integrated intelligence.

For example, in retail retailers can maximize customer loyalty across multiple channel by integrating data from real-time inventory, in-store location positioning sensors, RFID, and social media.

How do you bridge the gap between data and outcomes?

4

How do you consume any data generated

or understood by humans?

How do you identify key aspects and

patterns to determine outcomes?

How do you automate to take

action?

Data sources Diverse Modern Apps

Q1 Q2 Q3

PresenterPresentation NotesThis is the core task of IDOL11. To help our customercreate applications quicker and with more insight than ever before.

Essentially with IDOL11 we are bridging the gap between the stores of human information and the applications we dream of creating for our customers and partners.

Given that we need to do this at the speed of business. Time is a critical variable.

In that space of time we need to learn or use technology to answer the following questions;

How do you consume any data generated or understood by humans?How do you identify key aspects and patterns to determine outcomes?How do you automate to take action?

Augmented Intelligence power apps for competitive advantage

5

Augmented Intelligence powered by HPE

Artificial intelligence, machine learning and natural language processing using advanced analytics functions.

PresenterPresentation NotesConnect: Thousands of connectors for text, video, image and audio available designed to handle enterprise and government scale volumes of data. Available in over 155 languages + 55 languages for speech to text

Process & Analyze - Established and proven technology to determine outcomes bas

Build - Portfolio of hundreds of advanced analytics functions and APIs to automate and take actioned on machine learning and deep neural networks to enrich data findings, identify key aspects and patterns

Machine Learning at the Service of BusinessAugmented Intelligence

PresenterPresentation NotesWe are living a revolution in machine cognition. Cognition being understood as knowledge, attention, memory and working memory, judgment and evaluation, reasoning and "computation", problem solving and decision making and finally comprehension.Things that human beings do well. But machines historically have not.But what if a human could apply our ability for cognition to all the data that surround us? Thats simply not possible so; what if a machine could do a percentage of the cognition for the people that are dealing with say building applications for businesses?We would then be amplifying what experts can do. We would be augmenting them with an intelligent machine. We refer to this as Augmented Intelligence.Using cutting edge machine learning techniques we extend the ability of machines to apply cognition to unlimited amounts of the information that a human can understand and can produce.With comprehension of information comes many possibilities; finding needles in haystacks, choosing the right answer for a human and context rich question, automating the process of adding value to information as we would add comments to a document, etc the sky is the limit.IDOL11 is a suite of off-the-shelf components that allow you to choose which aspect of cognition you want to apply to a problem. Like humans thesum is greater than the partsand IDOL components complement each other to solve more complex problem.Like a human brain we might teach it about some of the things we care about. Much like a human we might chose to train this brain differently depending on what is we are asking it to do. We might teach it to learn how things are connected so it can build webs of connections that span galaxies of connections or we might simply teach it to understand what a topic is so it might help us decide what to do when this is encountered again.Like a human brain we might want to ask it to do repeatable tasks with low cognition levels; like looking at a contract and determining its a contract and not a novel. But do this at a speed no human could ever possible achieve.Like a human we might as this brain to reflexively look at a problem and evaluate outcomes; like asking ourselves what we did last year? How many emails? What about? Now lets ask an entire company, thousands of people the same question. On reflection, whats important? On reflection what happened? How did we get there?

HPE Big Data Advanced Analytics Software Solutions

Vertica high-performance advanced analytics Real-time performance at scale Premise, Cloud, and Hybrid Native optimized

Hadoop options

IDOL augmented intelligence for human information Advanced enterprise search and rich media

analytics

Analyze text, audio, image, and streaming video

Haven OnDemand APIs and Services Machine Learning as a Service Delivered on Microsoft Azure Cloud Accessible to any developer

Deep Learning

TextAnalytics

Face Detection

NeuralNetwork

Speech Recognition

Categor-ization

PresenterPresentation NotesFrom database to sensors to text, audio, image and video data, HPE Big Data Advanced Analytics software provides the capability to monitor, process, analyze data from virtually anywhere and of virtually any format. Today, well focus on IDOL.

Foundational MethodologyHow does IDOL address big data?

8

An analysis platform without data is like humans without senses

9

150 data sources

Index without relocation

PresenterPresentation NotesOne of the major barriers for analytics is the data silo. Analyzing partial data will leave you making decision in a partial vacuum. IDOL 11 comes ready with the capability to connect to 150 data repositories so you can tap into any necessary data in virtually any format (text, video, image, audio) to gain comprehensive insights needed for faster and better decisions. Be it behind the firewall like Microsoft Exchange or Documentum or outside the firewall like Dropbox, Google drive, you can index all data where it resides and eliminates copying requirements, storage costs, and hand-off risks.

Why is processing human data different?Human Information is made up of ideas, is diverse and has context

Ideas dont exactly match like data does; they have distance.

Human Information is not static its dynamic and lives everywhere.

Legacy techniques have all fallen short.

10

MobileTextsEmailAudioVideoSocial Media

Transactional Data Documents Search Engine Images IT/OT

PresenterPresentation NotesHuman data, unlike structured data, is diverse, context sensitive and nuanced. It is scattered everywhere and changes rapidly. For example, the hot topics regarding a major sporting event (e.g. World Cup) may change with entertainment (e.g. celebrity sports stars) news and/or business/political news (e.g. FIFA investigations). The dynamic patterns, trends and relationships existing within the data are critical but cannot be easily and quickly uncovered with legacy analytics techniques.

Thomas Bayes (1702 1761)

PresenterPresentation NotesThomas Bayes was an 18th C cleric who in his spare time decided to try and use mathematics and probability to prove the existence of God. As part of his work, he developed Bayess Theorem, which looks at the problem of inverse probability essentially what is the probability of something happening given these things have already happened. Although he published several books, Bayes never published his most famous work, and Bayes Theorem was all but unknown until the 1950s, rejected as unscientific. Today, Bayesian Inference has proved to be extremely versatile and has wide applications in numerous fields, including machine learning, science, engineering, economics, game theory, medicine and law.

If we toss a coin 100 times and get heads every time, whats the probability of getting a head on the 101st?

Traditional probability says: 50%

Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

PresenterPresentation NotesIf youre not familiar with Bayesian Inference already, here is a simple example to help illustrate it.

If we toss a coin 100 times and get heads every time, whats the probability of getting a head on the 101st?

Adaptive intelligence: prior information changes the model of understanding

Bayesian Inference says: 99+% Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

Claude Shannon (1916 2001)

PresenterPresentation NotesThe other half of the IDOL engines ability to understand human information is based on Shannons Information theory. Claude Shannon was a 20th Century American mathematician, very poorly known but absolutely brilliant and considered the father of information theory without Shannon, we would not have computers as we do today. Oh and he also founded digital circuit design theory as well as a 21 year old masters student.

Alfred Butts Letter Frequencies

PresenterPresentation NotesWhat Shannon discovered was that different bits of data are not all equal, and some carry more information value than others. For example, you can listen to a conversation in a noisy room and miss half of the words but still have a reasonable understanding of what was being said through catching the high value words.In his Information Theory, Shannon defined a way to mathematically identify which bits of information have high value and which have low value.

The image here was created by Alfred Butts, the inventor of the board game Scrabble (in 1938, ten years before Shannon published his theory). In order to determine the score for each of the letter, Butts applied an intuitive and simple variation of Shannons Information Theory he counted the frequency of letters in sources such as The New York Times. The less frequent the letter occurred, the higher its value and hence the higher the score it was given.

This theorem them has many applications, from detecting and correcting signal noise, to data compression. For example, if you wanted to take a bitmap image and compress it into a jpeg, how would you determine which bits to keep and which to throw away? Shannons Information Theory allows us to calculate that, and in IDOL we are able to use this Theorem to determine which words and concepts in a document or other human information are high value and which are low value.

Strong information and weak informationKey Words are small amounts of very strong information without contextLarger amounts of weaker information is what humans refer to as context

Mercury

Is it a planet?Is it an element?Is it a car?With high certainty; its an element!

A heavy element and the only metal that is liquid at standard conditions for temperature and pressure with the symbol Hg and atomic number 80,

commonly known as quicksilver

PresenterPresentation NotesNow, Ill give you an example of how IDOL brings these two theorems together to obtain a human-like understanding of human information. If I was to say to you the word mercury what is the first thing that comes to your mind? It could be [CLICK] the planet, [CLICK] the element, [CLICK] or a car made by Ford in the 50s.

[CLICK] Take a look at this sentence no where in it have I mentioned the work mercury and yet your brain can process this and determine exactly what it is talking about. The way your brain processes it is using Shannons Information Theory and Bayesian Inference. Firstly, it applies Shannons Information Theory it looks at all the words in the sentence and discards the low value words like a or the or and, and identifies the high value words like liquid, metal, and quicksilver. Then, your brain applies Bayesian Inference it looks back through all of your experiences and tries to identify where it has seen all of these high value terms together before and it determines, with a high degree of probability at least, [CLICK] that the concept linking all this information together is mercury the element.

Using Cognitive Analysis to form a human-like understanding of content

HPE IDOL: Natural Language Processing (NLP) engine

Fundamentally created to understand naturalhuman language using probabilistic modelingand NLP algorithms Allows incoming data to dictate the model,

not pre-defined rules, dictionaries, or semantic webs

Self-Learning / Machine Learning Updates as more data is added or removed

Adapts to changing definitions or meaning

Fundamentally language-independent Treats words as symbols

Optimized with language packs Eduction, sentiment analysis, speech analytics

Information Theory and Bayesian Inference

PresenterPresentation NotesSo that is how we use those two algorithms to gain a human-like understanding of unstructured information in just the same way that the human brain does. The probabilistic approach to Natural Language Processing and Machine Learning has several advantages over other approaches such as linguistic analysis or semantic webs.

Firstly, linguistic and semantic web approaches both have significant limitations in that they need to have a set of predefines rules, dictionaries or tuples (semantic web) in order to make any sense of what they are processing, and these rules need to be constantly . So while they can sometimes perform well in very specific, niche domains or use cases, as a general analysis tool they are extremely limited. In contrast, IDOL applies machine learning over the data itself, allowing it to dictate the model and as new words appear, or existing words take on new meanings, these changes are immediately identified, learned and understood (in just the same way you can learn the meaning of a new word through its context, seeing it used several times). In Big Data analysis applications, this is absolutely essential because its very rare that you know exactly what is in the data you want to analyse (hence why you're analyzing it), and indeed its very often these new, unusual concepts or outliers that are of particular value.

Secondly, IDOLs probabilistic model also has the advantage of making the analysis process entirely language independent. This is because IDOL is not trying to break down a sentence into nouns and verbs in a completely language-dependent way, but rather IDOL looks at each word as a symbol or black-box and builds up its understanding around how it is related to other symbols to determine its meaning. This means a single IDOL engine can natively index and understand human information in any of over 160 languages, irrespective of character set and so on.

IDOLs Core Capabilities

18

Rich Media Analytics

Knowledge Discovery

Advanced Enterprise Search

Data Enrichment

What is it?Augment data with other relevant data

ExampleExtract company names from tweets and make tweets searchable by company names

Context sensitive search across internal and external sources

Search for Samsung and get results related to Samsung, Apple iPhone, Huawei

Uncover trends, patterns & relationships without explicit queries

Uncover root causes of customer attrition with social media and call center data

Recognize and analyze image, video and audio

Logo/object/text recognition and speed-to-text transcription in broadcast media

PresenterPresentation NotesLets look at the four key capabilities more closely.

Date enrichment is about augment data with other relevant data such as metadata. For example, we can extract company names from tweets, associate the tweets with the extracted names, and make the tweets searchable by company name.

Advanced enterprise search is about providing search results based upon relevant concepts associated with the search terms. This goes beyond simple keyword search. For example, if you search for HPE, you may see results associated with, HPE, IBM and Dell because IDOL understands that all these companies are related in that they are in the same industry and address very similar markets

Knowledge discovery liberates users from having to know what questions to ask beforehand. IDOL can recognize patterns, trends and relationships hidden within the data and lets the data tell the story. For example, IDOL can analyze customers tweets and call center logs to reveal root causes as to why the product has not been selling now.

Rich media analytics allows users to incorporate video, image and audio data in gaining more complete insights. For example, in addition to say, text analytics of social media, a marketer can also monitor and analyse broadcast media for logos, on-screen text and speeches.

HPE IDOL - Market leadership

19

Gartner Magic Quadrant for Enterprise Search 2015

For the 2nd consecutive year, Gartner has positioned HPE as a leader in its Enterprise Search Magic Quadrant 2015 based on ability to execute and completeness of vision.

Source: Gartner (August 2015)

This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from HPE.

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of opinions of Gartners research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

PresenterPresentation NotesHPE, for the 2nd year in a row, is positioned in the leaders quadrant. The 2015 Gartner MQ report for enterprise search is available from - http://goo.gl/p0iJRj. This sustained and consistent level of leadership speaks to our the strengths of our vision and execution.

In the 2015 Garter MQ on enterprise search, Gartner particularly cited our mapped security, our ability to reveal patterns in unstructured data and cloud-based offering as our key strengths.

20

HPE IDOL - Market leadershipThe Forrester Wave: Big Data Search And Knowledge Discovery Solutions, Q3 2015

The Forrester Wave is copyrighted by Forrester Research, Inc. Forrester and Forrester Wave are trademarks of Forrester Research, Inc. The Forrester Wave is a graphical representation of Forrester's call on a market and is plotted using a detailed spreadsheet with exposed scores, weightings, and comments. Forrester does not endorse any vendor, product, or service depicted in the Forrester Wave. Information is based on best available resources. Opinions reflect judgment at the time and are subject to change.

A leader in overall results based upon strategy and current offering

Top ranked in strategy

PresenterPresentation NotesIn addition to the Gartner MQ rating, IDOL is positioned as one of the leaders in the Forrester Wave Big Data Search and Knowledge Discovery Solutions Wave. This report can be accessed via http://www.forrester.com/pimages/rws/reprints/document/117712/oid/1-X0OHMY

Platform Features

21

Over 500 IDOL functions to augment your intelligence

Automatic hyperlinking

Conceptual search

Keyword search

Fieldtext search

Phrase search

Phonetic search

Field modulation

Fuzzy matching

Implicit profiling

Explicit profiling

Community and expertise network

Agents

Intent-based ranking

Alerting

Social feedback

Eduction

Automatic clustering

Clustering 2D/3D

Autoclassification

Auto language detection

Sentiment analysis

Automatic taxonomy generation

Automatic Query Guidance

Highlighting

Parametric refinement

Summarization

Real-time predictive query

Metadata extraction

Automatic tagging

Faceted navigation

InquireSearch your data

InvestigateAnalyze your data

InteractPersonalize your data

ImproveEnhance your data

PresenterPresentation NotesIDOL comes to hundreds of functions which are be put into four categories Inquire, Investigate, Interact and Improve. They complement each other and can be combined to address diverse use cases.

For example:Inquire Conceptual Search - The probabilistic approach of IDOLs index and retrieval process allows complex operations to occur naturally. This augments basic retrieval to allow more subtle connections to be determined and more relevant results returned than are possible in any key word engine.

Investigate Automatic query guidance automatically groups search results into dynamically generated categories so you can quickly narrow down a search set (e.g., a search for Madonna would create clusters of the singer, the religious icon, and other relevant categories).

Interact Implicit profiling IDOL can learn from a users actions document views, searches, content contributions, likes develop a profile to facilitate delivery of highly relevant information that matches the users interests

Improve Eduction - Entities such as name, place, number can be extracted from within a document and be used as metadata for the document which enriches the information and facilitates easy discovery.

Language independence

Free from linguistic restraints and rules

Automatically adapts to changing definitions

Over 150 languagesSingle,multibyte and Unicode languages

Optional language packs for localization

Product performance issues

ClusteringSide letters

Off balancesheet transactionsAutomatically

partition the data so that similar information is clustered together


InvestigateAnalyze your

data

InteractPersonalize your

data

ImproveEnhance your

data

PresenterPresentation NotesTakes a large set of data and automatically partitions it so that similar information, even in varying formats, is clustered together. Each cluster represents a concept area, making it easier for you to identify inherent themes and emerging trends.



data


data

ImproveEnhance your

data

Add context to short queries by grouping results into concepts

Automatic Query Guidance

Query Madonna

Results: Documents containing Madonna

Query search

Documents about:1.Singer2. Italian Renaissance3. Madonna Further

suggestions

Most likely meaning

Result documents

Conceptual clustering

PresenterPresentation NotesAutomatically groups search results into dynamically generated categories so you can quickly narrow down a search set (e.g., a search for Madonna would create clusters of the singer, the religious icon, and other relevant categories).



data


data

ImproveEnhance your

data

Exploratory analytics that help you discover the unknown unknowns

Enhance your data

Managed classification Create categories using business rules or training

Automatic classification and clustering Automatically determine categories based on patterns and relationships in information Spot analysis of all themes and grouping Time sensitive analysis; Whats hot? Whats New?

Eduction Apply structure to unstructured data by extracting key fields and entities Hundreds of entities supported, including names, addresses, credit card information, sentiment, intent, etc

Audio analysis Speaker independent speech to text, speaker identification, audio events, language identification, etc

Image and video analysis Next generation image classification (is this a car?/find more like this) On-screen OCR, logo detection, intelligent scene analysis, Color and texture analysis,

story segmentation, etc

Hundreds of conceptual entities

Eduction

Quickly narrow search results with auto-identified facets and conceptual entities such as employee names from documents

Validate or customize entities Is this a valid credit card number? What are all docs that contain SSNs? If area code is 415, output as Home Office

Pinpoint accuracy for multibyte languages such as CJK, Thai and some European languages

NamesPlacesIP addressesCompaniesEventsRelationshipsMedicinesAirportsCarsSocial Security numbersPhone numbersCredit cardsDatesHolidaysJob titlesCurrencies many more



data


data

ImproveEnhance your

data

PresenterPresentation NotesAutomatically identifies and extracts terms in documents that lend themselves to key fields, such as the names of companies or people, locations, addresses, and telephone numbers. IDOL offers hundreds of entity grammars out-of-the-box across numerous languages



data


data

ImproveEnhance your

data

Analyze your data

Quickly evaluate the relevance of informationAutomatic Query Guidance (providing top themes from query results in real time)Concept navigation via advanced visualizations (node graphs, theme tracking, topic maps, broadcast analysis)

Intelligent summarization (simple, concept and context)Intelligent highlighting (search terms, phrases, concepts, context, fidelity to query grammar)

Concept streaming (Real-time summaries from audio that are contextual to queries and intent)

Intelligent de-duplication, including near de-duplication Use structure to navigate the data

Structured, semi-structured and XML supportParametric search (unlimited nesting and association support)Directed navigation (create compelling navigation for users)

Personalize your dataWe are what we InquireSearch your data InvestigateAnalyze your data


data

ImproveEnhance your

data

PresenterPresentation NotesConstructs an understanding of your interests and skill set to deliver more accurate, targeted results based on content consumption, including browsing histories, content contributions, and interactions. You can also explicitly define your interests and train the search engine.

Discover Relationships for Richer Insight

30

Knowledge Graph

Customer A is in Customer Bs network

Customer C is linked to Customer E via

Customer D

Customers F and G purchased the same

model last year

Customer H is the most influential in

Customer Bs network

PresenterPresentation NotesWhat is it? It discovers relationships between entities (e.g. people, places, companies) that lead to richer and more impactful knowledge discovery. It identifies and reveals connections, connection path(s) and common traits.

Why does it matter? It provides critical insights into how entities relate and facilitates investigation into potential network of influence. For example, it is now possible to answer the question of what your customers have in common besides using your flagship product.

Intent-based ranking

Search results personalized and targeted based on user and context

Profile developed through complete behavior analysis implicit or explicit profiling

Gather data from content consumption,

content contribution, interaction with colleagues, etc.



data


data

ImproveEnhance your

data

Topical sentiment analysis

Decomposition and classification within a sentence to pull out specific topics

I stayed at the Marriott last week, and though the mattresses were very nice, the service was awful.

Is this Positive? Negative? Neutral?

How much Positive? How much Negative?



data


data

ImproveEnhance your

data

PresenterPresentation NotesDetermines the degree to which a given texts sentiment is positive, negative, or neutral for the entire content or a segment of the content. IDOL uses both linguistic analysis and a statistical, pattern-based approach to derive sentiment. Currently offered for: Arabic, Chinese, Czech, English, French, German, Italian, Polish, Portuguese, Russian, Spanish, and Turkish.

Search video as easily as textTransform rich media into intelligent assets



data


data

ImproveEnhance your

data

Live video or playback from archived footage

On-screen text recognition

Face identification

Automatically generated transcript using speech

recognition

Speaker identification

Timecodesynchronization

Automatic keyframe generation

AutomateAutomatically create metadata, keyframes, transcriptions

UnderstandUnderstand video footage and audio streams in real time

ActApply advanced analytics such as clustering and categorization, and link with other file types

Image technology: 2D objects

Registered image Test image

Generic Logo recognition

Registered Logos

Test image



data


data

ImproveEnhance your

data

PresenterPresentation NotesThis works best trying to recognize objects which have a 2D plane of interest. That is, the interesting parts of logos or paintings are flat parts with little to no 3D contours. Rotations, skewing, and distortions including light distortions are OK and generally handled very well.

Intuitive Knowledge Discovery for Self-Service Analytics

35

Visualization to simplify analytics workflow Topics MapSunburst

Result ComparisonRich Contextual View

Business Intelligence for Human Information (BIFHI)

PresenterPresentation NotesWhat is it? A new end-user GUI provides a straightforward analytics workflow for diverse use cases. BIFHI incorporates visualization functionality such as topic map to highlight key concepts, sunburst diagram to enable easy filtering based upon extracted entities (e.g. people, place, company),result set comparison to examine how a change of search parameter may impact the outcome and rich contextual view where the query result includes not only the document itself, it shows the metadata and other relevant information such as documents by the same author or documents from around the same period. Why does it matter? The intuitive interface enables business users to perform self-service analytics and shortens time to insight. For example, the user can search for a topic, visualize the result breakdowns on the main panel, and refine the search parameters on the side panel with automated guidance based upon IDOLs deep understanding of queried data, and see real-time result changes, all within the same window.

Use CasesCross Industries and Industry specific

36

Customer care, turbocharged

Customer Self Service via IDOL Search

Key Differentiators

Automate more customer service with advanced features such as contextual search, automatic hyperlinking, implicit query, sentiment analysis, alerting, and chat agents

Find and act on 100% of information - regardless of language, source or information format

Scalably and securely access virtually all systems, including cloud repositories with over 400 pre-built enterprise-class connectors

How Customer Would DeployIDOL powered self service web-based support using all available knowledge sources: knowledge base, contact center, forums, product reviews and more, with connectors to existing OSS, BSS, media solutions and network management as needed

How IDOL would drive competitive advantage for customer Reduced churn & improved CSAT due to enhanced automation of customer self-service and improved user experience; SG&A cost reduction with single systems for internal and external support

Solutions like HPE Service Anywhere run IDOL Search

to improve service quality and staff efficiency

PresenterPresentation NotesSelf Service portal: Easy Google like search. Ask a question and IDOL prompts end user with knowledge articles, catalogue items and collaboration threads. End users can start or contribute to collaboration threads to get or provide answers.

IDOL Find powers many applications, including Service Anywhere

Monitor social media to proactively address incidents and issuesSocial Customer Service via IDOL

Key Differentiators

Combine social and public data (Twitter, news, etc) with customer data in the enterprise to gain insights

Strong text analytics to synthesize and summarize large volumes of data sentiment analytics, concept extraction, extract place names

xxxxxHow Customer Would DeployDeploy IDOL with connectors to various data sources.

How Social Customer Service would drive competitive advantage for customerTap into other sources of customer feedback for proactive and reactive resolution of service issues.Improve customer satisfaction, mitigate churn, identify upsell opportunities

Build a knowledge graph of your organization and automate customer interactionWorkforce Productivity via IDOL Knowledge Management

Key Differentiators

Automates manual customer care processes & actions

Expertise location to team and deliver best response

Proactively deliver and manage relevant & timelydata

How Customer Would Deploy

Deploy a comprehensive platform for customer interaction to automate a time-consuming, labor-intensive process.

How IDOL would drive competitive advantage for customer

SG&A cost savings: Increased customer satisfaction (decrease churn rate), decreased call center load, understand your organization better to align resources and eliminate inefficiency

Increased revenue: Re-deploy resources to high value customer add services

Unstructured

Structured

Collaboration

Expertise Location

Categorization

Eduction

Taxonomy

A Smarter Data Lake Needs

Automatically analyse rich media

Connectors & Policies

IDOL FeaturesIntegration points with Hadoop

Understand myriad file formats and types

Breakdown information silos across enterprise

Improved, intuitive visibility to contents

KeyView

IDOL Server (incl HDFS Sync)

Image Server & Video Server

Using IDOL to enhance Hadoop (Beta for Evaluation) Any Source Build, enrich, and clean up your data lake

Data Clarity and Mapped Security Data dictionary and information security within your data lake

Advanced Analytics - Provide contextual search and text, image, video, speech machine learning

On Screen Text Recog.

Analyze video, audio, images to support & drive the next wave of experience and monetizationMultimedia Analytics via IDOL Multimedia

Key Differentiators Automate - create metadata, key frames, transcriptions

Understand - video and audio streams in real time

Act apply advanced analytics (cluster, categorize, link)

How Customer Would DeployIn line with strategic next wave value added services, rich content, and services strategy

How IDOL Multimedia Analytics would drive competitive advantage for CustomerDrive next wave content, publishing, and advertising/monetization (revenue enhancement) - Value Added Services to complete against OTT- Content screening, moderation- Ad verification- Compliance

New Age On-Demand Internet Video, Audio

Multi Language

Video Analytics

Face detection

Sentiment extraction

Advanced IDOL

Analytics

Speech-to-Text

Speaker Identify

IDOL powered Healthcare Analytics for 360 degree clinical intelligence

Core Capabilities: Integrated modular platform for variety of use cases Hundreds of data connectors and data types Rapid identification of concepts, patterns and relationships Conceptual search on all data Advanced security for compliance Healthcare specific capabilities: SNOMED CT taxonomy with 344K+ concepts and 2M terms Integrated ICD codes

Reconciliation

ID discrepancies between

diagnostic code and clinical notes

Monitor KPIs and Metrics

Reporting

Abstraction

Rapid Chart Access

PresenterPresentation NotesHP HCAP is an integrated solution that enables users to unlock full value from data, most of which has been sitting in their operations untapped. It is powered by HP IDOL, which as you know, is a proven search and analytics engine in many compliance centric industries such as financial and legal. It leverage core capabilities from IDOL that you already know and love. What makes this special is that this is a solution designed by healthcare professionals for healthcare professionals. It incorporates the key essential ingredients such as medical taxonomy, coding, UI and visualization to make it a robust platform of vertical depth and modular breadth to effectively address the uniqueness of healthcare and the diversity in use cases.

IDOL powered Smart City Solution

Integration Analytics Data Fusion

Integrate data feeds from across the city into a common command center for investigation and event monitoring

Add video, audio, and event analytics to the feeds to enable real time monitoring for security trends and incidents

Complete the puzzle with additional information sources like social media, broadcast media monitoring, employee databases, etc.

Built-in Scalability

Unlimited expansion and connectivity already included at all levels by design.

Automation

Streamlined workflow and automated processfor triggers and alerts

Customer Stories IDOL in Action

44

Challenge Create airline passenger registration system and compare

information against existing police databases, to protect the country against crime.

Been able to intercept suspect passengers before they take a flight, during transit or at their destination point.

Solution HPE IDOL + Vertica

Benefits Extract meaning from virtually all forms of information associated with any airline

booking, including unstructured data such as audio, video, images, social media, email and web content, as well as structured data such as customer transaction logs

Perform language-independent analysis and flag potential targets.

2016 will see 3.6 billion passengers worldwide making journeys by air, so we need to employ every possible way to protect our borders against crime

Spanish Ministry of Interior Improves Safety With Big Data Analytics

PresenterPresentation NotesThe PNR will contain all the information relating to an airline reservation, including how the booking was made, how it was paid for, and whether it forms part of a regular pattern of travel. Based on these and other risk indicators,

Mission Proposal for a EUROPEAN PARLIAMENT AND COUNCIL DIRECTIVE on the use of Passenger Name Record data for the prevention, detection, investigation and prosecution of terrorist offences and serious crime.The proposal for an EU PNR Directive is part of the wider agenda to better protect European citizens against security threats, such as terrorism or serious crime, as identified in the EU Internal Security Strategy in Action presented by the Commission in November 2010 The proposal obliges air carriers to transfer the PNR data of passengers on international flights to the Member States of arrival or departure. There the PNR data will be analysed and used for the purpose of fighting serious crime and terrorism.The projectsMore systematic use of Passenger Name Record (PNR) data of such passengers for law enforcement purposes.

Main challenges & how they were overcomeGreen field for HPE Software at the National Security Department of Ministry of InteriorFirst engagement through local HPE Partner back in January 2014Public Sector rules of engagement procurement process via Catalog

Demonstrated Big Data platform capabilities to differentiate against competitorsStrong HPE references in Investigative analytics for Security Agencies in GovernmentHybrid Solution combining Hardware and Software

One HPE approach and getting engaging early n the cycle we were able to define the project.Excellent understanding of PNR proposal and Use Cases definition together with the customer.Co-operation with other Police Agencies and Departments.

6 months of engagement to define the complete end-to-end PlatformBecome in a trusted advisor and long term provider for the customerExcellent customer relationship

HPE engagement together with local partner up to Political (Secretary of State) level

Business Value Proposition

To create airline passenger registration system and compare information against existing police databases, to protect the country against crime. In 2016 they expect to see 3.6 billion passengers worldwide making journeys by air.Support all proposed use of PNR by Law enforcement authorities (re-active, real-time and pro-active use cases) as stated in proposal Directive.Extract meaning from virtually all forms of information associated with a passenger name record to support PNR implementation for passenger identification, passenger profile, travel routes and airport intelligence.

Technology

The solution proposed by HPESW is based on the HPE Big Data Platform:HPE IDOL Analytics PackageHPE Vertica Analytic Database

on Enterprise Group systems:4x HPE DL560 Gen8 SFF CTO Chassis4 x HPE DL380p Gen8 25-SFF CTO Server4 x HPE DL380p Gen8 8-LFF CTO Chassis

Why we won?We have one of the best Big Data Platforms out there in the market.Demonstrated the capabilities to differentiate against competitorsTaysa -key partner. They gave us the deal and the high level contacts to close the deal.Flexibility to support and define the proposed PNR Use Cases and requirementsGood References and Demo capabilities

China MobileCommunications service provider industry

Challenge Allow users to access information on thousands of public services

directly from their mobile phones success of the Wireless City platform depends on the users ability to quickly find information

Solution HPE IDOL

Result Over 740 million subscribers can search through more than 8,000

applications for public service information, including public transportation schedules, public health records, traffic offenses and more

Users receive more accurate search results than ever before China Mobile customers get the most relevant and useful information

regardless of the terms they use in the search

Private | Confidential | Internal Use Only 46

PresenterPresentation NotesBackground: China Mobile boasts the worlds largest mobile network and the worlds largest mobile customer base. They call the creation and development of the Wireless City their most critical project during the countrys five-year economic development initiative that began in 2011.

Much of the success of Wireless City depends on the users ability to quickly find information and harness the full potential of the platform said Cao Yang, project manager, Wireless City, China Mobile. HPE IDOL stood out by having a great support infrastructure. We believe that the unique conceptual search capabilities of HPE IDOL can help us deliver an unmatched experience and a highly valuable service to our customers.

News release: http://www.autonomy.com/work/news/details/ho65btia

Leading American multinational telecomPaying careful attention to every aspect of customer-facing processes and applications

Challenge Provide support desk staff with fast access to precise information

required to address customers problem Improve knowledge management system search capabilities

Solution HPE IDOL HPE Big Data Professional Services

Result Reduced time-to-resolution with fast queries that ensure support

experts can resolve customer issues quickly Relevant results as query functionality makes sure that results deliver

information most likely to resolve customer issues


PresenterPresentation NotesInternal only: https://irock.jiveon.com/docs/DOC-123105

Leading financial software, data and media companySubscribers require up-to-the-second information on market conditions and trends

Challenge Deliver search performance at the scale required by the size of its data

repository, 200 million messages, 15-20 million chats daily Provide robust, cost-efficient solution with scalability for large and

growing volume of data, supported by small IT headcount

Solution HPE IDOL HPE Big Data Professional Services

Result Detects trends in real-time messaging and chats for subscribers Accommodates 10+ billion of document entries without compromising

performance today Ensures scalability delivers ROI in the future


PresenterPresentation NotesAnonymousURL link Internal Use Only: https://irock.jiveon.com/docs/DOC-56482

NANA Management ServicesHPE IDOL brings higher security, lower cost, better business data

Challenge Businesses are challenged to manage high expense of traditional

guard services, false alarm rate and security equipment failure

Solution HPE IDOL engine embedded in OEM security solution NMS Virtual Guard with Milestone video surveillance platform

Result Increased visibility with limited number of cameras versus human

security guards. NMS Virtual Guard records every event Better value from assets, system alerts users when a camera goes

down (often recording only black) Efficient cost structure, NMS Virtual Guard and HPE IDOL can reduce

security costs by 80% over traditional guard staffing


PresenterPresentation NotesNANA Management Services (NMS)http://h20195.www2.HPE.com/V2/GetDocument.aspx?docname=4AA5-7114ENW&cc=us&lc=en

NANA Management Services (NMS) provides a highly flexible security solution for organizations of all sizes and technological capabilities. Its called NMS Virtual Guard, and it integrates real-time video surveillance with advanced computer analytics to instantly identify a potential threat. In the fall of 2014, NMS announced that it will base the systems analytical capability on HPE Havens IDOL engine to allow analysis and interpretation of video, audio, and text data from virtually any source.

In the traditional business, IT and security are still the last things to be budgeted, says Edward Knoch, Director, NMS Security Technology Solutions. In days past, you built an $80 million dollar building, then turned the keys over to an $8.00 per hour guard at night. More recently, automated solutions offered some improvements, but their basic analytics produce a ton of false positives. Out of, say, 36k reported events, only 4 may be actual security breaches. Our NMS Virtual Guard Service, with the embedded IDOL analytics engine, provides a powerful solution to this problem for a wide variety of purposes, not just surveillance.

Challenges: High security costs, limited effectivenessLarger businesses, on average, can spend up to $60,000 a month on 24x7 security guard payroll; and guards can only monitor so many locations and cameras at one time.

Most automated video surveillance systems produce tens of thousands of false alarms for every actual security breach; broken cameras may be streaming what appears to be live data, but in reality, all that is recorded is black, and faulty equipment may not be discovered for months.

Top benefitsIncreased visibility. Compared to security guards visually monitoring a limited number of cameras, NMS Virtual Guard can see everything.Better value from assets. The value of most cameras is in their forensic (after the fact) data, not live monitoring. NMS Virtual Guard alerts users when a camera is non-functional, creating better value for their customers.Better cost structure. NMS Virtual Guard and HPE IDOL offers high-end analytics for low cost, and can reduce guard staffing requirements by 80% or more.

The business case for security analyticsImagine a business problem related to on-premises security. A threatening individual visits the property regularly, so the business has a restraining order against this individual, with specific limitations regarding how closely they can approach the business property. How do you stop them before they get to that point? asks Knoch. Placing a security guard on site, watching for this individual to the tune of $7-9K per month is one option. And placing an armed guard on site will cost more like $12-15K per month.

But if you apply facial recognition via analytics, you can post a single guard for general purposes, who gets alerted only when an actual event occurs. With pre-identification, you can stop certain individuals whose behavior is predictable, and save money on security staffing in the process.

The role of HPEs IDOL engineThe worse thing for a guard company is to have to look at multiple interfaces to understand an event. With NMS Virtual Guard and IDOL, our security team has a single interface on Milestone, with HPE technology embedded inside with easy integration. The IDOL technology simply works, and it lives inside our security platform of choice.

The HPE IDOL engine provides our customers a very high-end analytics solution at a low implementation cost. They get the benefit of that great technology, and NMS gets the benefit of working with a company we know is going to be here in ten years. I just cant say that about the competitors we looked at before choosing HPE.

Free State of SaxonyHPE IDOL offers government powerful, centralized search

Challenge State government needed a future-proof, easy-to-administer search

solution for all administrative departments in Saxony, Germany

Solution HPE IDOL

Result A reliable, cost-effective search solution with simple administration and

high-speed indexing of web services, files, cartography, more 150 different internet portals indexed each night, with changes to

100,000+ documents System manages 110 km of documents, covering 1,100 years of

Saxon, German, and European history across five locations


PresenterPresentation Noteshttps://refsuccesscenter.HPE.com/SearchResultsFilteredV3.aspx?SearchType=MB&SearchId=236375

A centralized solution for everything The Saxon State Chancellery worked with T-Systems to introduce HPE IDOL as a search solution for the content of all of the www.sachsen.de websites, and now also provides this software to the administrative departments as a centralized solution for their internal and external search requirements. For example, this has enabled geodata searching, as well as searching within the Saxon State Archives electronic archives.

Many solutions, high administration costSaxony is one of Germanys 16 states. The Free State covers 18,420 square kilometers, and is currently home to 4.05 million people. The Free State of Saxony is a little more than 10 years old and started to build the central e-government infrastructure of the Saxon government.

The Free State of Saxony first started developing its central e-government infrastructure over ten years ago. It provides the administrative departments with centralized e-government software components that are not to be further developed multiple times for economic reasons. These base components form the Saxon e-government platform. They are connected to the internal IT processes of the state and local administrative departments via secure administrative networks. One of the base components is the search function; both citizens and administrative employees want to find information quickly and with precision, explains Dietmar Gattwinkel, formerly consultant at the Saxon State Chancellery and now at the Saxon IT Services the person in charge of the base components for the search engines.

The search function was a central requirement for the Saxon e-government platform right from the start.

Right from the start, we wanted to have a search engine that could be used with all of our systems and services, so that we wouldnt have to develop a range of search technologies that would require the user to maintain particular knowledge and expertise, says Gattwinkel. And that is why the Saxon State Chancellery chose to implement centralized software for searching that could, most importantly, integrate easily with the OpenText content management system. But over the years, as more and more websites were developed, the chosen solution became increasingly difficult to administer.

SolutionHPE IDOL is a safe investmentWe needed search software that could be specifically configured to meet the particular needs of the administrative departments. The search results needed to be better or at least as good as the leading internet search engines in terms of both recall and precision. And we also wanted a future-proof solution that would also allow us to search information and file types in the future that we couldnt even imagine existing at the time. HPE IDOL met all of these requirements, says Gattwinkel. With HPE, we could be sure that the software will continue to be actively developed in the future. HPEs position within the Gartner Magic Quadrant assured us that there was a vision for future developments with HPE IDOL in Saxony. Later it became key that HPEs partner company, T-Systems, is not only German-speaking, but also has in-depth knowledge of the software and many years of experience in similar projects.

AdvantagesA centralized, reliable search for the administrative departmentsDeveloping the website search system was a flagship project for us. Now that we have it, we can, as the central service provider for the Free State of Saxonys administrative departments, provide very effective, reliable, centralized search solutions tailored to suit the individual needs of the websites, as well as for internal searches, explains Gattwinkel.

This opportunity has been used several times since the software was introduced. This comes as no surprise; before, the administrative departments were responsible for the procurement process, implementation and administration of their own search solutions. Employees with the required expertise for this were few and far between. Now, the base component has a centralized, cost-effective solution in the form of HPE IDOL.

HPEs Resume Search solutionFinding talent using Big Data Platform

Challenge Provide a fast, reliable means for finding the right talent for contracted

service engagements n HPEs client base

Solution HPE IDOL HPE Project Portfolio Management

Result Meaning-based search of unstructured data across thousands of

resumes helps locate in-house talent quickly Resource Brokers identify key attributes, skills and experience

required by Enterprise Services projects


PresenterPresentation NotesHPE Resume Search solutionhttp://h20195.www2.HPE.com/V2/GetDocument.aspx?docname=4AA5-5979ENW&cc=us&lc=en

HPE Enterprise Services (ES) has introduced an innovative new solution for rapidly filling labor demand based on its own in-house talent. Now ES Resource Brokers use Resume Search to extract accurate, comprehensive results from the unstructured data that comprises up to 135k resumes on file. Searches across documents in all formats return matches conceptually related to a query, but not dependent on the key words themselves. As part of HPE ESs internal Qualifications Inventory resume repository, the solution is based on Intelligent Universal Search (IUS) and Intelligent Data Operating Layer (IDOL), both of which are key technologies supporting HPE Haven. The solution showcases the power that HPE Haven brings to unstructured data search.

Major business transformations are the bread and butter of the HPE Enterprise Services group, one of the largest organizations within HPE. With more than 135,000 specialists, HPE Enterprise Services (ES) needs to manage its own workforce carefully to handle the growing demands from its clients around the globe. We need an accurate view of both the market demand and our talent pool. We need to know what people we have available, what their skills are, and how to balance the need in the marketplace with our supply of talent, explains Jeanne Brekelmans, business operations chief of staff for HPE ES. The complexity of HPE ESs talent poola constantly growing body of individuals, each with different levels of skills, and different degrees of familiarity with current and emerging technologieshas made it critical for HPE ES to understand the unstructured data in the steadily evolving resumes of its staff. To help with this need, HPE created the Labor Demand and Supply Management program, or LDSM. The goal is putting the right people at the right place at the right time. One of the keys to LDSM is having a clear picture of all peoples skills and resumes.In June 2014 and as a part of the LDSM Program, HPE introduced HPE Resume Search, a new solution that leverages HPEs patented algorithms to form a conceptual understanding by extracting results that are accurate and comprehensive, finding resumes in all formats that are conceptually related to a query, yet not dependent on key words. At the heart of HPE Resume Search is HPE Haven, a highly advanced big data platform which uses multiple search models to help significantly improve the speed, accuracy, and completeness of search while providing automatic extraction of entities such as names, email addresses, locations, and languages directly from the resumes. This powerful new capability is now part of HPE ESs internal Qualifications Inventory resume repository.

Meaning-based search inside unstructured dataGil Doron, project and program manager for HPE Global Functions IT, explains the extent to which HPE IDOLs search capability surpasses a simple search on a string of characterswhat most of us do when we look for key words in a Word doc or PDF. This is where the unstructured data capabilities in IDOL come into play, says Doron. All resumes are unstructured; there are no tables created in order to enter talent data into the system. Consider what this means. With structured data, say in a spreadsheet, you have columns and rows that can be addressed and often understood according to data type. With unstructured data, as in a resume, youre dealing with data that isnt at all consistent, especially from one resume to the next. And the HPE IDOL engine is able to take that unstructured data, store it, and retrieve it easily through verbose, everyday language queries. An example of a meaning-based search is a natural language query, for example: I want a project manager who also has SAS skills. IDOLs breadth of connectors to different repositories, its ability to re-use existing indexes, and its meaning-based computing technology combine to create relationships within data that delivers intelligent, personalized search. IDOL is able to extract text from these documents and store it in such a way that allows queries to return results in seconds. It also can rate the likelihood of finding what youre looking for according to your set of keywords. When it finds a resume that contains the keywords youre searching for, it can then drill down and find other resumes that closely match it in a cross comparison. These resume documents can be in any format a Word doc, a PDF, a plain text file, etc., says Doron. You can drop all these file types into a single directory, and Autonomy will search it without any additional work on the users part. A resume comes in, you add it to a folder, and the system automatically indexes it for you.

Expanded use of Haven and features of Resume SearchHPEs resource brokers not only use the LDSM system to know who has the right skills for an assignment, but also who needs training in certain areas. We may be short on certain skills, says Brekelmans. We may have too many people within a single skill set. There is all sorts of analysis that comes out of LDSM, which gets rolled up into many places within HPEfor annual planning, for instance, where were going with our people and our accounts.Now that the solution has been in place for 6 months, were seeing users reach out to us with new and innovative ways that will further enhance the product, says Nedea. We are seeing requests to bring in additional information from PPM and the Human Capital Management system to provide a holistic view of the persons current availability and current location. In our bid process we ask applicants to quantify their depth in certain skill sets. Were starting to see more requests for rarer skills that are not in our qualifications catalogue. With the Haven-based Resume Search capability, were able to answer those questions. These requests most often come from RFPs, but were seeing them come increasingly from our own internal projects and analysis from Enterprise Services.

HPE on HPE CX AnalyticsAnswering critical customer satisfaction issues better and faster

Challenge Pull all customer-related data into a centralized repository Create a set of analytics services its business units can use to

improve the companys Net Promoter Score (NPS)

Solution HPE IDOL Information Analytics and HPE Vertica Analytics Platform Tableau Hadoop

Result Maximize value of customer experience data to improve customer

satisfaction Provide snapshot of customer experience metrics that is current and

comprehensive; answer complex questions in 5-10 minutes Generate a 360-degree view of the HPE customer experience


PresenterPresentation NotesHPE on HPE CX Analyticshttp://h20195.www2.HPE.com/V2/GetDocument.aspx?docname=4AA5-9341ENW&cc=us&lc=en

Dept. of State Development, Business and InnovationPublic Sector Victoria, Australia

Challenge Provide a single, secure, enterprise-wide search platform across

multiple information sources inside and outside the organization Locate information from different information sources such as HPE

TRIM, the DSDBI Intranet, shared network drives, Salesforce and external sites such as Hansard, Australian Bureau of Statistics, Victoria online and other websites

Solution HPE IDOL, Microsearch Portlet, Microsearch consulting services

Result Easily and quickly find relevant information with near real-time search

across millions of documents, 9 enterprise and Internet content sources, leading to significant time savings

Single sign-on allows filtered results, preventing the inadvertent disclosure of sensitive information


PresenterPresentation NotesBACKGROUND: Victoria, Australias DSDBI engages with businesses and represents their needs to all levels of government, provides strategic economic planning advice and targeted business development assistance, encourages investment and trade, and markets Victoria in Australia and internationally. They operate a number of systems, applications, internal and external sites and related information portals to support its business operations.

Business Drivers:Improved user experienceImproved staff productivityReduced costs through technology consolidation

Case study: http://www.autonomy.com/pdoc/assets/global/pdf/Offerings/unified-information-access/20131023_PL_CS_DSDBI_web.pdf

Dubai PoliceAccelerating law enforcement for Smart Cities

Challenge Use automation to locate wanted vehicles efficiently Read a range of number plate styles in both English and Arabic

lettering and different color codes

Solution HPE IDOL HPE Media Management and Analytics Platform

Result System helped Dubai Police capture 2,739 people locally and

internationally, over 18 month period Success led to version 2, incorporating improved cameras with ability

to read across six lanes of high-speed traffic


PresenterPresentation NotesDubai Police http://h20195.www2.HPE.com/V2/GetDocument.aspx?docname=4AA5-6223ENW&cc=us&lc=en

Dubai, one of seven Emirates that form the United Arab Emirates (UAE), maintains a sophisticated police establishment with more than fifteen thousand employees with multiple high-level specialties and training. They are proud to be one of the best security institutions on a local, regional, and global scale. In 2009, the Dubai Police deployed a new type of scanner mounted to the top of their patrol cars, capable of reading vehicle license plates and rapidly detecting those whose owners are wanted by the authorities. Associated crimes range from traffic violations to criminal activity.

At the heart of this new Automatic Number Plate Recognition (ANPR) system is HPE IDOL, a secure search and analytics engine of the HPE Haven platform that delivers actionable intelligence from both structured and unstructured data.

Challenges: Replace a cumbersome, manual task with extensible technologyZenith began working with the Dubai Police in 2007, when Zenith first approached the police to introduce a new mobile ANPR solution.

Previously, an officer with a printed list of wanted plates would comb through lots and garages full of parked cars, and occasionally find a match.To significantly improve effectiveness they needed to automate the process through the use of technology.The system needed to work day and night and read a wide range of number plate styles within the seven Emirates of the UAE, which incorporate both English and Arabic lettering and different color codes.They also needed the ability to find and track wanted vehicles in moving traffic, but ensure up-to-the-minute data updates so only those still wanted would be IDd.

Top benefitsIn the past 18 months, the system has helped Dubai Police capture 2,739 people locally and internationally.Given the success of ANPR, the Dubai Police will soon be expanding their capability with the next generation of the Zenith Intelligent Lightbar system, which will offer a much wider range of detection for wanted plates and incorporate 360 degree video surveillance, all embedded discretely in the patrol cars roof-mounted lightbar.

Real-time response on busy city streetsBeing able to connect in real time, and being able to respond in real time, is what this is all about, says Russell Hammad, CEO of Zenith Gulf Security Systems, which developed the Zenith Intelligent Lightbar 360 degree, remotely accessible surveillance system. This technology combines high-end cameras and HPE IDOL, which enables capturing an enormous amount of raw data rapidly and making sense of it almost instantly. And this system had to be extremely user-friendly for law enforcement; they cant be bogged down with hard-to-use technology on the job.

The heat is onCreating the ANPR system involved more than the interface of HPE IDOL with display screens inside police carsplacing a sensitive camera system on top of a police car creates a high-heat issue, especially in Dubai, where the sun can cause a cars rooftop temperatures to go as high 60-70 degrees Celsius (140-150 degrees Fahrenheit). So, in every camera, theres a dual camera optic system for redundancy and failover, explains Hammad. These are high quality cameras suited for whats called an IP-68 environment; they are very insulated for the temperature conditions. Weve had the version 2 system running for the last 6 months in one vehicle to test the latest camera design.

The Dubai Police are very forward thinking. They see the vision, and because they are known as leaders in municipal security, we have a number of other police forces in the region who are keenly discussing similar implementations of this technology.

Auckland TransportDriving groundbreaking Futures Cities initiative

Challenge Enable Safe City Solution to be predictive instead of reactive Deploy video analytics to support safety and well-being of citizens with

Future Cities initiative


Result Optimizing video analytics with more than 2000 video feeds recorded,

200 video analytics running in real time Detect red light jumps, congestion, clearway violation & much more Utilize data from more than 2,000 cameras monitor traffic patterns for

more than 1.4M citizens Implement license plate recognition for accurate identification and

scene analysis


PresenterPresentation NotesAuckland TransportLink to press release: http://www.autonomy.com/work/news/details/i0i5nizu City of Auckland, New Zealand Selects HP to Drive Groundbreaking Future Cities InitiativeSep 30, 2014HP HAVEn Big Data Solution will streamline traffic flow and provide enhanced safety for citizensPalo Alto, Calif., Sept. 30, 2014 HP today announced that the city of Auckland, New Zealand has selected HP Software to deliver a visionary Big Data project designed to provide a safer community and more efficient roadways for its citizens.Auckland Transport, Auckland's government agency responsible for all of its transportation infrastructure and services, will deploy video analytics powered by HP IDOL on servers and storage from HPE Enterprise Group, and with support from HP Software Professional Services."The safety and well-being of our citizens is always our top priority and the Future Cities initiative is a big step in the right direction," said Roger Jones, CIO Auckland Transport. "Only HP could comprehensively deliver the custom solution, expertise and ecosystem at this scale to transform our vision into reality."Auckland Transport (@AklTransport) will use HP's integrated big data platform, HAVEn, to analyze, understand and act on vast quantities of data of virtually any type including text, images, audio and real-time video. The system will leverage data from a variety of sources, including thousands of security and traffic management cameras, a vast network of road and environmental sensors as well as real-time social media and news feeds.In the first phase of the project, Auckland Transport will focus on improving public safety. Auckland Transport will use HP Intelligent Scene Analysis System and license plate recognition for accurate identification and scene analysis for dangerous activities and analyzing safety threats from over 2,000 cameras deployed within Auckland. Going forward this information will be linked with rich insight from social media news sources to provide a comprehensive solution that can proactively identify breaking trends and respond to critical safety incidents for cyclists and transport users.HP Enterprise Group will supply the hardware infrastructure for Auckland Transport, a combination of powerful servers and storage systems. HP Proliant Gen8 BladeSystem, HP 3PAR StoreServ Storage, HP StoreAll Archive and HP FlexFabric will give Auckland Transport the most advanced hardware, providing superior capabilities for the safe city initiative.HP Software Professional Services will also be instrumental in the process, lending support and expertise to ensure a swift and smooth implementation.HP partner VidSys (@VidSys), a global leader in physical security information management systems, will provide a platform that unifies the control and monitoring functions of physical security, building and traffic management, and computer aided dispatch systems.Auckland Transport's investment in big data technologies from HP is part of a larger trend around the emergence of "Smart Cities." Enlightened city planners are looking at how to leverage big data, sensor data, and data from people and their devices to create improved products and services for citizens. According to market research firm IHS, investment in Smart City projects and technologies will rise from $1 Billion in 2013 to $12 Billion in 2025.

High risk environmentBase protection

Challenge Detect threats anytime, anywhere by correlating

intelligence from multiple sources in various forms audio, video, reports and 3rd party sensors


Result Automatically flag anomalies by analyzing feeds from

aerostat, UAV, towers, and correlating with other events Use biometric databases to relay real-time recognition of

facial features and license plates


PresenterPresentation NotesThis is a solution where analytics is deployed to detect threats by monitoring and analyzing different sources to detect threats. HPE IDOL and HPED MMAP work seamlessly together across video, audio and text data sources to uncover anomalies and issue alerts for high risk environment protection.

Stanford Childrens HealthResearch for healthcare provider ranking study Challenges Quality and clinical effectiveness research on ~115K patients, ~390K

encounters, ~3M documents Diverse data types (structured and unstructured) across data silos

involved Time constraints vs extensive search scope

Solution HPE IDOL Ontology Tagger and Analytics User Interface

Results Cross patient search for cohort identification Intuitive UI for simple query construction Easy clinical note review with highlights, navigation and related

concepts Portable queries and results Fast indexing


PresenterPresentation NotesStanford Childrens Health needed to respond to U.S. News and World Report ranking questionnaire. The questions regarding in-depth research into extensive hospital records. IDOL enabled researchers to quickly uncover salient insights by providing the self-service analytics capability with intuitive data exploration.

Global health servicesRobust search technology supports health services needs of 80 million customers worldwide

Challenge Detect meaning of data even if data didnt conform to specific standard

e.g. physician, MD, doctor, or Dr Fast query results to support positive customer experience

Solution HPE IDOL

Result Customers can quickly identify providers that meet their needs for

specialty, location and other important criteria Solution supports business and fiscal objectives with lower cost-in-

network providers Scalability maximizes ROI over time


PresenterPresentation NotesAnonymoushttps://irock.jiveon.com/docs/DOC-56495

Fortune 500 global diversified healthcare company


Claims data Provider information

FWA recovery data

Call center data

Treatment/Service data

Social media

Population and community health

Care management/Care coordination

Surveillance, Analysis, Product development innovation

Consumer cctivation/Engagement/Education

Reputation management/Outreach

Innovation focus

Lines of business

Innovation

Brand

Care delivery

Product development

Payment integrity

Provider

Consumer activation

PresenterPresentation NotesKey Messages:

Large Diversified Healthcare Company , acts as a payer & provider Claims are the life-blood of their operations, used traditional Data-Warehouse, BI, and statistical tools Challenges:Business SMEs with knowledge of payments processes not data-scientistsReport generation took long time: 30-45 daysDid not speak the same languageConstant pressure to reduce Fraud, Waste, and Abuse Payment Integrity early user of analytics - identified as high ROI target for Hadoop and AnalyticsChallenging because patterns of providers and fraud constantly changingChanges in regulations & contracts, + errors in data entry and process can result in incorrect payments.Government estimates that $50B of $500B on Medicare is lost to FWA, private health insurers are also affected

IDOL solved this problem by providing self-service analytics to business users and data-scientist. Hadoop is being used to scale out to all payment systems New data sources and use-cases being added constantlyEnabling a wide variety of lines-of-businessHas potential for very big impact on the organization

Population and Community HealthPrediction capabilities (symptoms, ailments, outbreaks, etc.)Clear picture of Community Health (attitudinal trends, demographics, geospatial) International impactBenefit/Reference-based plan design

Care Management/Care CoordinationCombine with Claims to fill in gaps (symptomatic, attitudes, education)Outcome Success

Surveillance, Analysis, Product Development InnovationCompetitive intelligenceTrends (attitudinal/behavioral, caregiving, device usage, etc.)Monetized data insight opportunities

Consumer Activation/Engagement/EducationConsumer conversations, trends, blogsInteractive/participative approachExpand Circles of InfluenceSets Quality Standards for Care/Providers

Reputation Management/OutreachSentiment management (competitor & brand)Outreach to support members, clients, providersVoice of the Customer

Fortune 500 global diversified healthcare companyAccelerate and increase cost savingsChallenges Drive to find savings by improving payment integrity Address evolving patterns of FWA Disparate payment systems , no single view Skill gaps limit access to analysis Long turn around time for BI analysis reports

Solution HPE IDOL

Results 24X Improvement in analysis turnaround Multi $M savings in weeks Self-service analysis for business analysts Single point of access covering multiple systems Dynamic rule-engine tests against new and historical claims to identify

potential recoveries Scale out on Hadoop Architecture Flexible platform supporting continual additions of new data and use-cases

60Private | Confidential | Internal Use Only

PresenterPresentation NotesKey Messages:

Large Diversified Healthcare Company , acts as a payer & provider Claims are the life-blood of their operations, used traditional Data-Warehouse, BI, and statistical tools Challenges:Business SMEs with knowledge of payments processes not data-scientistsReport generation took long time: 30-45 daysDid not speak the same languageConstant pressure to reduce Fraud, Waste, and Abuse Payment Integrity early user of analytics - identified as high ROI target for Hadoop and AnalyticsChallenging because patterns of providers and fraud constantly changingChanges in regulations & contracts, + errors in data entry and process can result in incorrect payments.Government estimates that $50B of $500B on Medicare is lost to FWA, private health insurers are also affected

IDOL solved this problem by providing self-service analytics to business users and data-scientist. Hadoop is being used to scale out to all payment systems New data sources and use-cases being added constantlyEnabling a wide variety of lines-of-businessHas potential for very big impact on the organization

Beijing Future AdvertisingNext generation sports marketing

Challenge Deliver high value-add services for advertising clients

Solution HPE Media Management and Analytics Platform HPE IDOL

Result Integrated: Bring broadcast and social media analytics together Efficient: Automate monitoring & analysis of broadcasts & audience

reactions. Reduced data classification and processing time from 10 tens to minutes

Effective: Tap into insights from audience/consumer engagements Impactful: Provide guidance for strategy and resource investment


PresenterPresentation NotesSuccessful TV advertising campaigns rely on rapid access to marketing and consumer insights, particularly during live sports events. Beijing Future Advertisings objective was to enable advertisers to maximize ROI with precision marketing by significantly accelerating the provision of high value insights from advertising campaign results, through real-time video capture, and automated video and social media data analysis.

NASCARFan and Media Engagement Center

Challenge Economic conditions Rapidly changing media landscape (social media growth) Rev pressures from sponsors Industry leadership expectation

Solution HPE IDOL

Results Live monitoring and analysis of broadcast, news and social media Sponsors brand and fan sentiment analyses Analytics to support race team sponsorship renewals Crisis management Build fan base with active engagement

View customer testimonial on YouTube


PresenterPresentation NotesNASCAR Fan and Media Engagement Center (FMEC), a resource that enables NASCAR to better serve the industry, media, and fans through a solution that facilitates near real-time response to traditional, digital, and social media. HPE IDOL helps NASCAR analyze and determine the right voice, the right tone, and the right message to reach critical new audiences and increase the fan experience. Located in Charlotte, N.C., the facility opened in October 2012. Powered by HPE IDOL, FMEC can listen to, monitor, and engage with leading media channels. NASCAR now has access to a complete analysis of all key forms of media, including print, television, radio, video, images and social media, which will provide the sports leader and its industry partners with actionable insights on trending news and conversations. By facilitating more collaboration around this information, NASCAR and its partners will be better equipped to enhance the fan experience.

Highlights of the FMEC include:-Provides real-time data capture and analysis of conventional media (i.e. video and audio) and social media (blog, Twitter, Facebook) to help understand fan behavior across all forms of media-Allows NASCAR to directly share its voice with fans, facilitating direct and network discussions-Transforms data into meaningful and actionable business information across the enterprise and with teams and partners-Solutions are very flexible, being able to leverage NASCARs existing data assets and information provided from 3rd party agencies-Provides broadcast worthy visualizations and content

The system aggregates a mass of data and metrics that are relevant to NASCAR:TweetsFacebook postsOnline news articlesBroadcast programming Blog post, and more API plug-ins to social platforms (i.e. Twitter firehose)Web scraping for online news contentPulling online data feeds

https://www.youtube.com/watch?v=UOt0dt2nkys

Summary

Holistic Integrate data silos & unlock hidden insights Proven Sustained market leadership Versatile One platform for diverse use cases

63

For more information, please visit:

www.hpe.com/software/IDOL

Appendix

64

Architecture

65

IDOL Connector overview

Connector actionsSynchronize (fetch)ViewIdentifiers, Collect, Hold, ReleaseHold

Insert, Delete, Update

Repository ConnectorConnector framework

serverIDOL

LUA w/IDOL extensions

Document Format detection

Pre-import processing

KeyViewfiltering

Post-import processing

LUA w/IDOL extensions

Index into IDOL

Connector framework server

DIH

Repository

Connector

IDOL

Repository

Connector

Repository

Connector

IDOL IDOL

IDOL Data Ingestion pipeline

LUA scripting engine is available within connectors

KeyView file format process, Eduction and LUA scripting engine are available within CFS

OCR

Audio/Video

Category

APA Agents

Repository

Connector

Connector framework server

Content

Repository

Connector

Repository

Connector

DIH

Data & Analytics

HPE IDOL Technical Overview - july 2016