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Become an Information-Driven Organisation with
Cognitive Search & Analytics
Hans-Josef Jeanrond
Sinequa CMO
15/11/2017
2
Welcome to the Convention of Alchemists
Where people promise to turn data into gold
Painting by Jan Matejko, 1867
3
How do you turn Data (lead) into gold?
You will have heard – and hear –
different stories:
• Data is Gold / Oil / Lifeblood …
Just put it into a data lake and you will be rich
- maybe
4
Stories on how to turn Data into Gold
• Refine your data with a Statistics /
BI Refinery
 Order and Structure your Data
 Unstructured data is just unfinished
work
The Eternal Promise
 “Structure the World to Possess it” is
deeply rooted in our minds
 But it is like chasing the Grail
 The percentage of unstructured data
is growing, despite all efforts of
structuring the world
5
Stories on how to turn Data into Gold
The overly structured world • Order vs comprehensiveness
• What is missing in the “orderly” image?
6
Stories on how to turn Data into Gold
The overly structured world • Order vs comprehensiveness
• Too much order misses the art and the value!
~20 M$ ~20 $
7
Stories on how to turn Data into Gold
• Use Search to find Gold in Data
(A Paradigm Shift: less magic)
 Too much sand with the gold?
 Add Natural Language Processing
to better search in your Unstructured
Data
• Keywords and Statistics will do – they
always have!
• Did they really?
8
Stories on how to turn Data into Gold
• Still too much sand in your pan?
• Add “Real NLP” – Linguistics,
Semantics, Sentiment Analysis,
etc.
 Discover semantic similarities
 Are customers happy or angry?
 Which products / services do they
like / dislike
9
Stories on how to turn Data into Gold
• Need to dig deeper still?
• Use Deep Learning and
Machine Learning
To detect whole gold mines
10
Forrester Predictions 2018: The Honeymoon For AI Is Over
“Success At Artificial Intelligence
Means Hard Work –
Treat It Like A Plug-In Panacea
And Fail”*
Abstain from AI – and fail as well!
Do it right
Don’t let technology make it harder
than it needs to be.
*Forrester Report by Boris Evelson, Michele Goetz, and Brian Hopkins,
November 9, 2017
11
So what do you do as a budding Alchemist?
• You need to do all of the above
– but:
 You can’t sprinkle NLP, ML, AI on
basic search and analytics like
icing on a cake
12
So what do you do as a budding Alchemist?
• You need to do all of the above
– but:
 You can’t sprinkle NLP, ML, AI on
basic search and analytics like
icing on a cake
 You need a Cognitive Search &
Analytics Platform that is
• well engineered and scalable
• providing native security
• Connecting to many data
repositories “out of the box”
13
What is Cognitive Search?
Cognitive Search = Search + NLP + AI/ML
A simple definition:
14
Combination makes the difference!
• Technologies are applied in
combination – not simply in
parallel
• Each technology enriches the
others
• The end-result is more than the
sum of its parts
15
What Can Cognitive Search and Analytics
do to Help the Apprentice Alchemist?
16
What Can Cognitive Search and Analytics do to Help?
Cognitive Search delivers
relevant information from data
to users in their business context,
such that they can
 make better decisions
 drive innovation
 reduce risk
 create new business models and
business processes
 be more efficient
17
Is it worthwhile? Some Research Results
“By 2020, organizations able to analyze all
relevant data and deliver actionable
information will achieve an extra $430
billion in productivity benefits over their
less analytically oriented peers.”
Source: IDC FutureScape: Worldwide Analytics, Cognitive/AI and Big Data 2017
“The knowledge worker spends
about 2.5 hours per day, or
roughly 30% of the workday,
searching for information….”
Source: IDC White Paper – The High Cost of Not Finding Information
“Employees spend 1.8 hours
every day—9.3 hours per
week, on average—searching
and gathering information.”
Source: McKinsey Report - Time Searching for Information
18
How to build a Cognitive Search & Analytics Platform?
LOGICAL DATA WAREHOUSE
ANALYTICS
INFORMATION
SELF-SERVICE
SBA Studio Global Business API Global Analytics API
Natural Language Processing
Statistical Analysis Semantic Extractors
Machine Learning
Algorithms
150+
SMART
CONNECTORS
Directories Archives
Cloud SourcesSocial Networks
Websites/Intranet
Databases
BI/Data LakeE-mails
CMS/ERP/CRM Applications
External SPARK
Cluster
HADOOP
Data Lake
External Entity
Extractors
External
Convertors (video,
speech, image)
THIRD PARTIES
19
MACHINE LEARNING ALGORITHMS
LOGICAL DATA WAREHOUSE
SINEQUA
ANALYTICSSPARK Cluster
Spark Master
Worker Worker Worker Worker
SINEQUA DataFrame SPARK DataFrame (Csv, Json, Jdbc)
APPLICATION (Spark SQL / Spark ML / Spark Streaming)
Similarity Clustering ClassificationRecommendations Predictive Analytics
20
CREATIVE USE CASES AND SBA
Imagination – Speed – Agility - High ROI
Create a 360° view of a customer
• Detect and reduce Churn
• Provide better customer service at lower cost
Find experts on a given subject
• Create multidisciplinary teams on a given subject
• Assemble the “dream team” for a new project
• Find scientific and industrial partners
• Discover redundant projects
Find existing technology for reuse
• Avoid costly re-developments
• Accelerate projects and time-to-market
Push news on a given subject
to subscribers
• No more searching – push info
Create a news digest on given subject – even complex
scientific subjects
Assemble R&D Intelligence
Measure research activity in a given field:
• Find research trends in industry
• Discover potential competitors’ projects in your area
21
VERY DIVERSE CREATIVE USE CASES AND SBA
Imagination – Speed – Agility - High ROI
Detect fraud in financial transactions
Minimize risk for insurance companies
Assemble military intelligence
on an operations theatre
Discover terrorist networks
Discover money laundering
networks
Facilitate case management
and collaboration at anti-trust authority
Find legal matter experts for a case
Extract relevant data from clinical trials
Find information on drugs by scientific and
brand names and by chemical structures
22
USE CASES: ORGANIZATIONS NEED IMAGINATION
• Cognitive computing is in its infancy
• There are no “best practices” to be copied
• Inspiration is needed, not copying
• Organizations must transpose intelligent use cases of
leaders into their business environment
• The growth of this new market of cognitively enabled
information systems is more limited by organizations’
creativity than by their budgets!
• You play a key role in spreading these truths
23
For questions, demos and more details on use cases,
find us @ our booth #433
Listen to my colleague Gengis Birsen talking about
Cognitive Search & Analytics – Bringing the Power of AI to
Enterprise Search
tomorrow at 11:50 in the AI Lab Theatre
Follow @Sinequa
Contact: hans-josef.jeanrond@sinequa.com
24
Sinequa helps AstraZeneca drive
innovation, accelerate research
and shorten Drug Time-to-Market.
With Sinequa, we are building a powerful
next-generation search platform that is
simple and intuitive enough for our R&D
scientists to use easily and be alerted
to new information anywhere, anytime.
Nick Brown
Technology Incubation Director,
CTO Office – AstraZeneca
«
»
25
200 Million Documents
40% Internal, 60% External
Find Documents and Expert Networks
across a large R&D Organization
10,000 People in R&D
26
RESULT:
Identification of knowledge and expertise across the organization
Drugs
Diseases
Brands
MOA
Genes
arteriosclerosis
27
Autosuggest with categories guides the user
28
Find People, not just Documents
29
Dynamic, automated profiles of experts
Dynamically generated by Sinequa ES based
on content analytics upon the 200M documents
30
Weight Skills (+ or -)
Matrix of similar people with similar skills
31
Query on “arteriosclerosis”
Navigate by source
and corporate
taxonomy
Publication timeline
Refine by format
(PDF, Word, SAS
file, etc.)
Top 20 people
in related
documents
Drugs in
development and
their relevance
Available drugs and
their relevance
Associated skills
32
R&D Search on Mobile Devices
33
Find Top Authors on a Given Subject
34
Current Events – News and Alerts
35
Skadden leverages Sinequa's
Cognitive Search & Analytics platform
for insights into millions of records and
documents including attorney
biographies, subject matter summaries,
billable hours, and more.
Skadden
36
Amplifying Legal Expertise
37
• BI on customers: all customers
• “Dashboard” on one customer?
• Customer data is spread over 30+
enterprise applications
• Real-time is essential:
• Provide a 360° customer view to
10,000 Call Centers Operators.
ROI of $60M over 3 years
Mobile and Internet
Provider
38
360° CUSTOMER VIEW IN A CALL CENTER
PROJECT
• Modernization
of the Service Center
for a large telco company
SIZE OF THE COMPANY
• 20 Million Mobile Clients,
land line & DSL
• > 250 applications with
customer information
VOLUME AND VARIETY
• 10 000 call center agents
connected simultaneously
• 30 applications used by agents
• 5 to 15 applications opened per call
• Billions of records per year (billing,
calls, call reports, ...)
39
BUSINESS BENEFITS
• Get an instant 360° view of the customer (<2 sec.)
• Reduce average call time
• Increase First-Time-Resolution
• Increase up-selling and cross-selling
• Intuitive and unique interface shortens training time
 50% turnover per year: 5000 new employees
 30 days to 1 day in training time per employee,
150,000 person days to 5,000 days in total!
• 60M€ ROI over 3 years
40
Industry Analysts rate our platform well
Named a Leader in The Forrester Wave™: Cognitive
Search And Knowledge Discovery Solutions, Q2 2017
Named a leader in the Gartner Magic
Quadrant Insight Engine, 2017
41
SINEQUA IN A NUTSHELL
• Leading Independent Software Vendor – Cognitive Search and Analytics
 Natural Language Processing, machine learning
 End-to-end platform to unify information from multiple business applications
 150 ready-to-use connectors for all enterprise data sources
 High performance and scalability for Big Data
• Offices in New York, Paris, London, Frankfurt
• Privately held, rapidly growing (double-digit growth YOY)
• Established within Global 2000 companies
• Extensive network of service and technology partners
42
GLOBAL DATA-INTENSIVE CUSTOMERS
INDUSTRY/SERVICES/TELCO LIFE SCIENCES/PHARMA
FINANCE/BANKING/INSURANCE/LEGAL GOVERNMENT/PUBLIC/NON-PROFIT

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Big Data LDN 2017: Become an Information-driven Organisation With Cognitive Search & Analytics

  • 1. 1 Become an Information-Driven Organisation with Cognitive Search & Analytics Hans-Josef Jeanrond Sinequa CMO 15/11/2017
  • 2. 2 Welcome to the Convention of Alchemists Where people promise to turn data into gold Painting by Jan Matejko, 1867
  • 3. 3 How do you turn Data (lead) into gold? You will have heard – and hear – different stories: • Data is Gold / Oil / Lifeblood … Just put it into a data lake and you will be rich - maybe
  • 4. 4 Stories on how to turn Data into Gold • Refine your data with a Statistics / BI Refinery  Order and Structure your Data  Unstructured data is just unfinished work The Eternal Promise  “Structure the World to Possess it” is deeply rooted in our minds  But it is like chasing the Grail  The percentage of unstructured data is growing, despite all efforts of structuring the world
  • 5. 5 Stories on how to turn Data into Gold The overly structured world • Order vs comprehensiveness • What is missing in the “orderly” image?
  • 6. 6 Stories on how to turn Data into Gold The overly structured world • Order vs comprehensiveness • Too much order misses the art and the value! ~20 M$ ~20 $
  • 7. 7 Stories on how to turn Data into Gold • Use Search to find Gold in Data (A Paradigm Shift: less magic)  Too much sand with the gold?  Add Natural Language Processing to better search in your Unstructured Data • Keywords and Statistics will do – they always have! • Did they really?
  • 8. 8 Stories on how to turn Data into Gold • Still too much sand in your pan? • Add “Real NLP” – Linguistics, Semantics, Sentiment Analysis, etc.  Discover semantic similarities  Are customers happy or angry?  Which products / services do they like / dislike
  • 9. 9 Stories on how to turn Data into Gold • Need to dig deeper still? • Use Deep Learning and Machine Learning To detect whole gold mines
  • 10. 10 Forrester Predictions 2018: The Honeymoon For AI Is Over “Success At Artificial Intelligence Means Hard Work – Treat It Like A Plug-In Panacea And Fail”* Abstain from AI – and fail as well! Do it right Don’t let technology make it harder than it needs to be. *Forrester Report by Boris Evelson, Michele Goetz, and Brian Hopkins, November 9, 2017
  • 11. 11 So what do you do as a budding Alchemist? • You need to do all of the above – but:  You can’t sprinkle NLP, ML, AI on basic search and analytics like icing on a cake
  • 12. 12 So what do you do as a budding Alchemist? • You need to do all of the above – but:  You can’t sprinkle NLP, ML, AI on basic search and analytics like icing on a cake  You need a Cognitive Search & Analytics Platform that is • well engineered and scalable • providing native security • Connecting to many data repositories “out of the box”
  • 13. 13 What is Cognitive Search? Cognitive Search = Search + NLP + AI/ML A simple definition:
  • 14. 14 Combination makes the difference! • Technologies are applied in combination – not simply in parallel • Each technology enriches the others • The end-result is more than the sum of its parts
  • 15. 15 What Can Cognitive Search and Analytics do to Help the Apprentice Alchemist?
  • 16. 16 What Can Cognitive Search and Analytics do to Help? Cognitive Search delivers relevant information from data to users in their business context, such that they can  make better decisions  drive innovation  reduce risk  create new business models and business processes  be more efficient
  • 17. 17 Is it worthwhile? Some Research Results “By 2020, organizations able to analyze all relevant data and deliver actionable information will achieve an extra $430 billion in productivity benefits over their less analytically oriented peers.” Source: IDC FutureScape: Worldwide Analytics, Cognitive/AI and Big Data 2017 “The knowledge worker spends about 2.5 hours per day, or roughly 30% of the workday, searching for information….” Source: IDC White Paper – The High Cost of Not Finding Information “Employees spend 1.8 hours every day—9.3 hours per week, on average—searching and gathering information.” Source: McKinsey Report - Time Searching for Information
  • 18. 18 How to build a Cognitive Search & Analytics Platform? LOGICAL DATA WAREHOUSE ANALYTICS INFORMATION SELF-SERVICE SBA Studio Global Business API Global Analytics API Natural Language Processing Statistical Analysis Semantic Extractors Machine Learning Algorithms 150+ SMART CONNECTORS Directories Archives Cloud SourcesSocial Networks Websites/Intranet Databases BI/Data LakeE-mails CMS/ERP/CRM Applications External SPARK Cluster HADOOP Data Lake External Entity Extractors External Convertors (video, speech, image) THIRD PARTIES
  • 19. 19 MACHINE LEARNING ALGORITHMS LOGICAL DATA WAREHOUSE SINEQUA ANALYTICSSPARK Cluster Spark Master Worker Worker Worker Worker SINEQUA DataFrame SPARK DataFrame (Csv, Json, Jdbc) APPLICATION (Spark SQL / Spark ML / Spark Streaming) Similarity Clustering ClassificationRecommendations Predictive Analytics
  • 20. 20 CREATIVE USE CASES AND SBA Imagination – Speed – Agility - High ROI Create a 360° view of a customer • Detect and reduce Churn • Provide better customer service at lower cost Find experts on a given subject • Create multidisciplinary teams on a given subject • Assemble the “dream team” for a new project • Find scientific and industrial partners • Discover redundant projects Find existing technology for reuse • Avoid costly re-developments • Accelerate projects and time-to-market Push news on a given subject to subscribers • No more searching – push info Create a news digest on given subject – even complex scientific subjects Assemble R&D Intelligence Measure research activity in a given field: • Find research trends in industry • Discover potential competitors’ projects in your area
  • 21. 21 VERY DIVERSE CREATIVE USE CASES AND SBA Imagination – Speed – Agility - High ROI Detect fraud in financial transactions Minimize risk for insurance companies Assemble military intelligence on an operations theatre Discover terrorist networks Discover money laundering networks Facilitate case management and collaboration at anti-trust authority Find legal matter experts for a case Extract relevant data from clinical trials Find information on drugs by scientific and brand names and by chemical structures
  • 22. 22 USE CASES: ORGANIZATIONS NEED IMAGINATION • Cognitive computing is in its infancy • There are no “best practices” to be copied • Inspiration is needed, not copying • Organizations must transpose intelligent use cases of leaders into their business environment • The growth of this new market of cognitively enabled information systems is more limited by organizations’ creativity than by their budgets! • You play a key role in spreading these truths
  • 23. 23 For questions, demos and more details on use cases, find us @ our booth #433 Listen to my colleague Gengis Birsen talking about Cognitive Search & Analytics – Bringing the Power of AI to Enterprise Search tomorrow at 11:50 in the AI Lab Theatre Follow @Sinequa Contact: hans-josef.jeanrond@sinequa.com
  • 24. 24 Sinequa helps AstraZeneca drive innovation, accelerate research and shorten Drug Time-to-Market. With Sinequa, we are building a powerful next-generation search platform that is simple and intuitive enough for our R&D scientists to use easily and be alerted to new information anywhere, anytime. Nick Brown Technology Incubation Director, CTO Office – AstraZeneca « »
  • 25. 25 200 Million Documents 40% Internal, 60% External Find Documents and Expert Networks across a large R&D Organization 10,000 People in R&D
  • 26. 26 RESULT: Identification of knowledge and expertise across the organization Drugs Diseases Brands MOA Genes arteriosclerosis
  • 28. 28 Find People, not just Documents
  • 29. 29 Dynamic, automated profiles of experts Dynamically generated by Sinequa ES based on content analytics upon the 200M documents
  • 30. 30 Weight Skills (+ or -) Matrix of similar people with similar skills
  • 31. 31 Query on “arteriosclerosis” Navigate by source and corporate taxonomy Publication timeline Refine by format (PDF, Word, SAS file, etc.) Top 20 people in related documents Drugs in development and their relevance Available drugs and their relevance Associated skills
  • 32. 32 R&D Search on Mobile Devices
  • 33. 33 Find Top Authors on a Given Subject
  • 34. 34 Current Events – News and Alerts
  • 35. 35 Skadden leverages Sinequa's Cognitive Search & Analytics platform for insights into millions of records and documents including attorney biographies, subject matter summaries, billable hours, and more. Skadden
  • 37. 37 • BI on customers: all customers • “Dashboard” on one customer? • Customer data is spread over 30+ enterprise applications • Real-time is essential: • Provide a 360° customer view to 10,000 Call Centers Operators. ROI of $60M over 3 years Mobile and Internet Provider
  • 38. 38 360° CUSTOMER VIEW IN A CALL CENTER PROJECT • Modernization of the Service Center for a large telco company SIZE OF THE COMPANY • 20 Million Mobile Clients, land line & DSL • > 250 applications with customer information VOLUME AND VARIETY • 10 000 call center agents connected simultaneously • 30 applications used by agents • 5 to 15 applications opened per call • Billions of records per year (billing, calls, call reports, ...)
  • 39. 39 BUSINESS BENEFITS • Get an instant 360° view of the customer (<2 sec.) • Reduce average call time • Increase First-Time-Resolution • Increase up-selling and cross-selling • Intuitive and unique interface shortens training time  50% turnover per year: 5000 new employees  30 days to 1 day in training time per employee, 150,000 person days to 5,000 days in total! • 60M€ ROI over 3 years
  • 40. 40 Industry Analysts rate our platform well Named a Leader in The Forrester Wave™: Cognitive Search And Knowledge Discovery Solutions, Q2 2017 Named a leader in the Gartner Magic Quadrant Insight Engine, 2017
  • 41. 41 SINEQUA IN A NUTSHELL • Leading Independent Software Vendor – Cognitive Search and Analytics  Natural Language Processing, machine learning  End-to-end platform to unify information from multiple business applications  150 ready-to-use connectors for all enterprise data sources  High performance and scalability for Big Data • Offices in New York, Paris, London, Frankfurt • Privately held, rapidly growing (double-digit growth YOY) • Established within Global 2000 companies • Extensive network of service and technology partners
  • 42. 42 GLOBAL DATA-INTENSIVE CUSTOMERS INDUSTRY/SERVICES/TELCO LIFE SCIENCES/PHARMA FINANCE/BANKING/INSURANCE/LEGAL GOVERNMENT/PUBLIC/NON-PROFIT