the data science institute-cognitive solutions
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Enabling Agile and Adaptive Decision Making Through Knowledge Empowered Business Analytics Solutions
INSIGHTS|ANALYTICS|INNOVATIONS
Data Science & Big Data Practice
Cognitive Solutions
Cognitive Solutions combine the power of mathematical algorithms andcomputing in collaboration of digital knowledge reasoning to enableintelligent insights and actions.
Analyst prospective on
Cognitive Analytics
Drivers –• The proliferation in technology innovation across domains/channels• Growing usage of complex database that can be the major data source and
hold answers to complex business insights
• Emergence of computing platforms such as Cloud, Mobile, Big Data, Socialwhich holds the key to “closer to customer” insights
Implications –• Cognitive systems will emerge into a highly scalable entity and will
be delivered via any mobile device• It will be highly disruptive:
Business processes, domains and society will be transformed A revolution of business 360 is required – People, Process,
Technology, Culture and partner ecosystems A strong strategic intent among the business leaders are required to
stay tuned to the industry dynamismSources: Insights from Gartner research, IDC and McKinsey Research
Cognitive computing systems learn and interactnaturally with business users to extend whateither human or machines could do on their own.They help make better decisions by penetratingthe complexity of big data
Data Ingestion
Data / Pattern Mining
Hypothesis Generation / Testing
Experience based Learning
Interacting with users
Deduction / Reflection
Reasoning / Inference
Integrate virtual reality
Structured data, Text, Video, Images
AI, NLP, Video & Image Processing, Deep Learning
Answer to a query or asking more questions to provide the right answer
Iter
ativ
e P
roce
ss
Cognitive Computing FrameworkCognitive Across Verticals
Global financial services firm, turns to cognitivecomputing and advanced analytics to boost thebreadth and depth of its products and services
A leading retailer has implemented In-storecognitive apps to improve personalisation.Thinking apps go beyond the structuredconsumer profile data of age, location and pastpurchase history found in databases
A major cancer medical centre is co-creating acognitive system that uses cancer patienttreatment data to assist oncologists to diagnoseand treat patients based on the most currentavailable data
Cognitive System Characteristics
Cognitive systems differ from current computingapplications in that they move beyond tabulatingand calculating based on preconfigured rules andprograms.
Adaptive
Contextual
Iterative
Interactive
Data Proliferation
Bu
sin
ess
Dat
a D
isco
very Study and analyze
customer data touchpoints across information systems internal and external to the enterprise. Statistical and exploratory analysis of data.
Dat
a M
inin
g Advanced machine learning, augmented with cognitive knowledge graphs and business taxonomies to decipher semantic relationships and patterns in data.
Inte
llig
ence
Mo
del
lin
g Define the unified data model, linking entities and attributes across the business ecosystem –internal enterprise data and external data.
Imp
lem
enta
tio
n Integrate customer data points into a single platform and build a metadata abstraction layer for business service consumption and intelligent discovery.
Database
Documents
Disparate structured & un-structured data ingestion for discovery and exploratory analysis.
Data Mining using Ontology based semantic normalization, machine learning and sematic technology.
Design the unified data model andsemantic data map.
Implement the cognitive data modelPowered with semantic search and analytics.
• Business process automation• Recommendation
Engines• Segmentation• Customer Intelligence• Actionable Insights
• Continuous learning from new data.•Machine learning with
augmented intelligence
•Text Mining, NLP, Classification, Summarization, Entity Analysis• Neural Network, Deep
Learning, machine learning algorithms.•Knowledge Engineering,
Semantic Processing
•Multi-structured Data, Events, Logs•Social Media, Blogs, Web,
Communication logs• Enterprise Application
Data
Ingest Process
DeployLearn
Enterprise Knowledge Management Cycle
Our cognitive solutions aim towards enrichment of enterprise
information assets through intelligence augmentation from these
multi-structured data sources–
• External Public Data from the web – Social web, blogs,
websites
• External Private Data from 3rd parties – Cross-
functional and cross-domain analytics
• Domain Knowledge
• Business Process Knowledge
• Internal Data – Documents, Emails, Communication
Logs, Web Interaction Logs etc.
Processing these multi-structured data, and applying advanced
artificial techniques with cognitive science, we model and build an
Integrated Enterprise Knowledge layer for intelligence driven
business decision and action.
Insights Intelligence Action
• Sentiment Polarity – Positive, Neutral,
Negative
• Topics – Sports, Politics, Fashion, Comfort
etc.
• Emotion Analysis – Excited, Happy,
Passionate
• Digital and Social Footprint- clicks,
mentions, likes, machine data etc.
• Geo-spatial Insights – location, trends etc.
• Experience – Customer value chain
analysis
• Behavior – Event related behavioral
analysis
• Activity – events and activities across
subject areas
• Semantics and Content Discovery
• Business Research
• Market Intelligence
• Consumer Engagement and Intelligence
• Personalization of Offerings
• Target Campaigns and Ads
• Competitive Edge – Brand
Development
• Location Centricity
• Customer Centricity
• Content Classification
• Content Summarization
• 360 degree View
• Business Process Optimization
• Smart Solutions for machine
automation and intelligence
1
Personalization
• Deliver personalized service offerings based on consumer behavior and activity.
2
Unified View
• Single view of entities across all business units
3
Real Time Intelligence
• Event driven data linkage allows real time analysis and insights.
4
Intelligent Data
• Semantic empowered linked data unveils intelligence and knowledge across enterprise.
5
Revenue
• Establish optimized pricing. sales, marketing, campaigning strategies
6
Decision Making
• Cognitive solutions encompass collective intelligence for real-time focused decision making.
BusinessImpact
Call Recording Samples
Text Transcripts
Audio to Text
Text Mining/NLP
NLP
Cla
ssif
iers
Topics
Sentiment
Emotion
Personality
Relation
•
•
•
•
•
•
•
•
Business Expert
Interviews Knowledge GraphLinguistic Dictionary
Topic wise vector space graph of Customer and Agent Call logs
C1
C2
C3
A1
A2
A3
Topic A
Topic B
Topic C
Sentiment- 6Emotion – 7
Customers Agents
Topic and Intent Knowledge Graph
Semantic Query Engine
Sales force Training
Insights
Co
nv
ersi
on
rat
e (%
)
•
•
Experience
Perception
Express
Opinion
1. Natural language processing and text
representation
Real World Observed World
3. Topic mining and analysis
5. Text based prediction
2. Word association mining and analysis
4. Opinion mining & sentiment analysis
top related