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

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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

Transforming your Data Chromosome

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Call Recording Samples

Text Transcripts

Audio to Text

Text Mining/NLP

NLP

Cla

ssif

iers

Topics

Sentiment

Emotion

Personality

Relation

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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

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Topic and Intent Knowledge Graph

Semantic Query Engine

Sales force Training

Insights

Co

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ersi

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rat

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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

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Negative Positive

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Positive Campaign Not Sustained

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Competitive Edge

Behavior Pattern

Location Intelligence

INSIGHTS|ANALYTICS|INNOVATIONS