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Software EMEA Performance Tour 2013 London, UK 2 July
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Big Data Analytics: Generate Return on Information Gary Palmer July 2nd, 2013
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 3
The Big Data reality
• Digital information will grow by a factor of 44, to 35 ZB in 2020
• Includes data both in motion and at rest
• Need for more agile, flexible technologies for analysis
• Massive amounts of data can provide more accurate insights, better decisions
2009 2020
35 Zettabytes*
Source: IDC Digital Universe Study, 2010
0.8 ZB
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 4
50 million voice recordings
7 million chat sessions
6 million email interactions
CONTACT CENTRE
100 million web visits
WORD OF MOUTH >1 billion indirect insights
WEB
Over 160 million customer interactions per year
One organisation’s global complexity
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 5
At a scale never seen before
Data is being shared in ways never imagined
Source: Company Data
Waze • 48MM users, +2xY/Y
• 1B+ miles driven per month w/Waze Open
Jawbone UP • Billions of steps/day
• 700K+ hours of sleep/day
• 5x App interactions per user/day
Yelp • 102MM users, +43% Y/Y
• 39MM user-generated reviews, +42% Y/Y
© Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 6
The lost opportunities of Big Data
Today’s reality
3% 23%
% of data that would be
potentially useful IF tagged and analysed
actually being tagged for Big Data value
% of the digital universe that is
actually being tagged, analysed and
leveraged ¹Source: IDC The Digital Universe in 2020, December 2012
0.5%
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 7
Big data: volume, velocity, variety and complexity
Extreme information challenges
Extreme information is becoming routine generated by a sea of mobile devices, social media, sensors
Social computing Context-aware computing
Pattern-based strategy
Information sources
Social Media Video Audio Email Texts Mobile Transactional Data
Documents IT/OT Search Engine Images
Velocity Volume
Variety Complexity
Big Data
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 8
Lots of interesting data, but often locked away in siloes Inhibits ability for organisations to understand what is happening in a timely way
Social Media
Audio
Texts
Word, Excel
Images
Financials
Legal Documents
Call centre
Cloud
Cloud
Archive
Laptop
Mobile Phone
Data Centre
Data Center
Remote Office
Video
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 9
Clickstream Data
Transactional Data
Logs
ERP CRM
HRMS Procurement Supply Chain Management/
Inventory Mgmt
Human information—the big data challenge & opportunity
“Missed opportunity” “Increased risk” “Cost & complexity”
Social Media Video
Audio
Texts Messages
Word, Excel
Images
Need to handle 100% of the information
Unstructured Structured
10% 90%
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 10
The 800 lb gorilla is in the room
• Human information is diverse: text, audio, video, social
• Information is dynamic
• Information is complicated
• Meaning is relative
• Ideas don’t match - they have distance
Keywords and metadata do not solve this problem.
“After putting the vase securely in the box he tied a bright red bow around Jennifer’s birthday gift.”
“The lead singer took a final bow following a wonderful performance.”
“The Captain pointed the bow of the ship into the wind.”
A majority of big data is “human information” which is fundamentally different
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 11
Understanding the “what” and “why” of your business performance
When to consider Autonomy for big data
• Analyse unstructured and semi-structured data from a wide variety of sources
• Analytics is seen to augment/ tune rather than “rip and replace” an existing system and personnel
• Iterative and exploratory analysis can be of value
• Sampling of data yields insufficient results
• Business measures or KPIs are not predetermined
• Data needs to be worked by non-technical staff – i.e. marketing, LOB, etc.
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 12
Answer questions that could not be answered before
Trending big data use cases
Customer sentiment & intent “Love the new DreamWorks app”
Fraud detection looking for outliers Russian accents, 212 area code, replacement phones
Real-time dynamic retail Make an offer that can’t be refused – now!
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 13
Draw up your game plan before taking the field
Big data starts with big preparation
1. Gather business requirements before gathering data
2. Implementing big data is a business decision, not IT
3. Use agile and iterative approach to implementation
4. Evaluate data requirements
5. Ease skills shortage with standards and governance
6. Optimise knowledge transfer with a centre of excellence
7. Embrace and plan your sandbox for prototype and performance
8. Align with the cloud operating model
9. Associate big data with enterprise data
10. Embed analytics & decision-making into operational workflow
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 14
Autonomy IDOL is designed to tackle the challenges of multichannel analytics
Need the right technology to make it matter
• Single processing layer for all data
• Conceptual and machine learning capabilities
• Proven, mapped security model
• Pre-built connectors to most common repositories
• Ubiquity: Supporting 1,000+ file types
• Language independence – over 150 languages
• Process data in-memory, in-time, and in-place
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 15
500 functions & 400 connectors
Autonomy IDOL: the OS for human information
• Conceptual distance understanding
• Meaning extraction
• Meets most demanding security requirement
• Language agnostic
• Supports over 1,000 file types and 400 content repositories
• Automates processes in real time
• Social, audio, video, text
• Manage in place
• Petabytes beyond scalability
Over 400 Connectors
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 16
IDOL architecture supporting next gen apps
Social Media Video Audio Email Texts Mobile Transactional Data
Documents XML Search Engine Images
HP Autonomy
IDOL Applications
Autonomy Connectors
eDiscovery
Enterprise Search
Media Monitoring
Social Media Analytics
Decision Support
Augmented Reality
Partner/ In-house apps
HC Analytics
Repositories
Information Types
Apps
500 Functions
IDOL Services Multimedia Informatics
Enrichment Capture
Interaction Analytics Discovery
Concept Clouds
Active Matching Visualisation
ACA
MediaBin
Connected LiveVault
TRIM
AeD
Data Protector
WorkSite
DigitalSafe
Connectors
…
Cloud Enterprise
IDOL OS for Human Information
ERP
CRM
Database Jive…
Image
HIS
Data Warehouse
Hadoop
SharePoint
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 17
Digital Marketing
Information Governance
Information Analytics
HP Autonomy solutions family, powered by IDOL
IDOL
Compliance, Litigation Readiness, Storage
Optimisation, Database Archiving
Supervision & Policy Management
eDiscovery
Supervision
Legal Hold
Unified Information Access & Analytics
Voice of the Customer
Media Intelligence
Video Surveillance
Big Data Analytics
Enterprise Search
Knowledge Mgmt
Content Access & Extraction
Policy-Driven Info Mgmt
Records Mgmt
Legal Content Mgmt
Business Process Mgmt
Document Mgmt
Records Mgmt
Workflow Automation
Legacy Clean Up
Server Data Protection
Virtual Server Data Protection
Remote & Branch Office Data Protection
Endpoint Device Data Protection
Enterprise Content Mgmt
Information Archiving & eDiscovery
Data Protection
Digital Experience Mgmt
Web Optimisation
Search Engine Marketing
Marketing Analytics
Contact Centre Mgmt
Rich Media Mgmt
Augmented Reality
Marketing Optimisation
Hybrid
OEM
Software
Cloud the OS for human information
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Autonomy IDOL Big Data Use Cases
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 19
Inflexible analytical technologies inhibit effective comprehensive analysis
Big data infrastructure best practices
Risk Exposure: poor performance and suboptimal resource / storage usage
Cost: degraded performance, poor scalability & inability to rapidly iterate and tune queries increases probability that you will not generate the insight sought in a timely manner
Best Practice: Design the index structure to support the intended use cases needed by the application. Many technologies are not forgiving after setup. Pick a flexible technology like Autonomy IDOL that allows for configuration/ optimisation before and after deployment.
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 20
Aircraft manufacturer streamline finding the right data
Real world: expertise networks Business need
• Employees waste 30 min/day finding info, duplicate work of others
• Identify expertise across global community of 35,000 engineers
• Avoid traditional, manual approaches such as users describing areas of interest with predefined keywords
IDOL Solution
• Generate user profiles automatically and in real time based on the pages visited and documents read
• Alert employees when documents, other employees match the work they are doing
Business benefits
• Reduce time spent retrieving information by over 90%
• Identify teams working on similar projects across the globe
© Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 20
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 21
IDOL-powered automatic categorisation and intelligent sectioning
Big data infrastructure best practices
Risk Exposure: Manual categorisation and sectioning is slow and lends itself to human error. Important information can be missed.
Cost: Increased labour overhead time for processing and searching data increases spend while effectively restricting an organisation's ability to conduct comprehensive intelligent, context based analysis. Net result: missed opportunities and poor decision making.
Best Practice: Incorporate technology such as Autonomy IDOL that can automatically categorize, tag and section data
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 22
Consumer services company
Real world: understanding customers
Business need
• Need better data mining of customer and affiliate calls into the call centre (average of 20,000 calls / day)
• Build better understanding of the customer to drive additional revenue, more personalised offers
IDOL Solution
• Use of Autonomy Qfiniti and IDOL to create a detailed record of customer contact sessions
• Generate reports to better assess the performance of each representative and improve processes / customer service
Business benefits
• Improved efficiency of the call centre / First Call Resolution
• Enhanced upsell opportunities as agents make offers to callers
© Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 22
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 23
IDOL-powered solution to combine unstructured and structured data
Big data infrastructure best practices
Risk Exposure: Existing information silos inhibit comprehensive data analysis leading to inaccurate misinformed decision-making lacking discovery and analysis
Cost: Limited dataset that is bounded by existing institutionalised KPIs and rigid analytical processes increases the probability that key trends and business opportunities will be missed.
Best Practice: A proper big data infrastructure such as Autonomy IDOL should be able to analyse all file types from as many relevant repositories as possible, including Hadoop, to perform the analysis.
Use case: Government agency sensitive document management
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 24
Re-insurance company
Real world: understanding risk Business need • Understand risk exposure across many different contracts based on a variety of
factors (i.e. geography, sector, relationships between entities)
• Information heavily fragmented across repositories / subsidiaries, not normalised, and details are in text files
Solution • Use IDOL to index data across structured and unstructured repositories
• Present data to analysts in a very intuitive information discovery interface
Business benefits • Reduced risk / increased profitability
• Increased employee productivity
© Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 24
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Demo – Autonomy Explore
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 26
Designed to tackle the multichannel / big data analytics
Autonomy Explore Connectivity to touch points across websites, contact centres and the social web drive broad user applications
IDOL
Autonomy Explore
Brand reputation
mgmt.
News Email Blog Voice Web Video Apps Review Survey
Cross channel optimisation
Next-gen speech
analytics
Voice of the
customer
Social media
monitoring
Customer interaction
survey
First contact
resolution
Customer experience analytics
Operational efficiency
IDOL
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 27
Return on Information How do you measure value?
Time
Data value
Delivery cost
= ROI Return on Information
Data sources
Data volumes
Depth of analytics
Role of users
Hardware Software Services Support
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 28
HP Autonomy IDOL – the OS for Human
Are You Ready for Big Data?
Key big data best practices • Legacy data clean-up
• Proper field handling & query syntax
• Automatic categorisation and intelligent sectioning of data
• Combine unstructured and structured data
• Optimised business outcomes
Drives these big data benefits • Enables collaboration and innovation
• Improves productivity
• Delivers better, faster decision making
• Enables you to predict and act on real-time information
• Optimises your business outcomes
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Thank you
Gary Palmer
Sales Manager UK- Unified Information & Access Analytics
gary.palmer@hp.com
HP Autonomy
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