Views On Big Data
Views On Big Data
Views On Big Data
The three Vs
Big data in general has context in three Vs:
• Sheer quantity of data
• Speed with which data is produced, processed, and digested
• Diversity of sources inside and outside
.
1
Big Data: Key Concepts
An Internet Minute
2
Big Data: Key Concepts
The challenge of the “needle in a haystack”
Separating the signal from the noise1 becomes really relevant
1 http://techcrunch.com/2012/11/25/the-big-data-fallacy-data-≠-information-≠-insights/
3
Big Data: Key Concepts
Macro Trends
Many organizations carry out business based on insights gained from data analysis. There has been
a shift in the size, type, and form of data and in the way data is analyzed.
4
Trends Driving Fundamental Shifts (1/2)
Data volumes are growing, infrastructure is stressed to the breaking point and Big Data offers the
opportunity to address these challenges.
Bringing the Data to the Analytics Bringing the Analytics to the Data
• Focus on structuring data for storage • Focus on mobilizing data for analysis
• Serial approach to mobilizing new data • Immediate ingestion of new data sources
sources • Continuous data discovery
• Episodic analytics • Agile, self-service data visualization
• Pre-defined reports and dashboards • “Data trumps algorithms”
• Data sampling to fine tune algorithms • Data as a platform
• Data silos tethered to applications • Derive insight from structured and
• Quantitative vs Qualitative Data unstructured data
5
Trends Driving Fundamental Shifts (2/2)
Business IT
Traditional Approach Determine what Structures the data
Structured & Repeatable question to ask to answer that
Analysis question
IT Business
Big Data Approach
Delivers a platform Explores what
Iterative & Exploratory
to enable creative questions could be
Analysis
discovery asked
Big Data is the next generation of data warehousing, business analytics and business intelligence. It’s
poised to deliver top line revenues cost efficiently for enterprises based on new technologies (In-
database, MPP, In–memory,…), more agile analysis (runtime, on time,..) and more deep analytics ( new
data mining predictive algorithm, and optimization modeling)
Bring together a large volume and variety of data to find new insights
6
The Business Value of Big Data
The Value Tree
The business value drivers are beginning to follow familiar patterns – more data and better
insights create value
Value Driver Metric Analytics Capability Impacted driver Annual Benefit
Process
R&D Effectiveness Years to First Sales R&D Discovery Analytics
Efficiency Cost reduction
Reduce Cost potential
Product Portfolio Optimization/ $8 M - $14 M
Mfg. Cost Margin Dollars Product Lifecycle Mgmt COGS + FPDE
Product Profitability
7
The Transformation Journey
Barriers and Myths
There are many barriers to the adoption
of Big Data. Some causes technological Privacy, liability
disruptions while others may lead to Sensitivity
certain organization challenges, which IP
have to be overcome for the seamless
operations. Data science
Visualization
There are some interesting Big Data Solution Development
myths that need to be dispelled.
Converging
architectures
Compatibility,
Integration
Access and Availability
Ownership
Quality
Data structure &
Architecture (MDM)
Data-centricity
Incentives
Sharing and
collaboration
8
The Transformation Journey
The Convergent Data Architecture
9
The Transformation Journey
Accenture approach
Accenture’s Big Data Discovery service helps organizations identify Big Data opportunities and use
Getting Started
cases that are aligned with business stakeholder needs.
It helps organizations define a delivery road map and an actionable plan with clear business value
delivery goals by phase.
Through Discovery, the team defines a conceptual technical and solution architecture design and helps
to understand the total cost of ownership (TCO) of the technologies chosen.
Approach
10
The Business Value of Big Data
Impact on different Business Sectors
• Recent research has shown that companies, that use Big Data and analytics to make decisions, are
more productive and make more revenues. Here are some examples of certain business sectors that
utilized Big Data to gain advantage.
.
Telecommunication & Media Retail & Consumer Goods Financial
Financial Services
Services
Emerging Trends with Big Data Emerging Trends with Big Data Emerging Trends with Big Data
• Improve customer experience and • Large-scale clickstream analytics • Marketing partnerships to develop
retention • Event, location and behavior based enhanced profile of customer
• Tailored real-time recommendations targeting combining social media data • Targeted offers to cross sell and up-sell
during customer interactions • Sentiment analysis • Performance marketing – improve
• Monetization of data through value • Cross-selling, Market Basket Analysis promotion effectiveness
added services and Ad targeting • Leverage multiple sources of
• Enhance operational efficiencies by • Deep consumer segmentations unstructured data to improve 360 degree
detecting infrastructure bottlenecks real- • Merchandizing and Optimization view of customer
time • Supply-chain management and • Customer retention
• Network and security analytics, intrusion analytics • Manage credit risks
detection with a 360 degree view • New services such as price • Fraud detection and analysis
comparisons or virtual markets • Sales force productivity and effectiveness
• Operational transparency • Trade portfolio performance and
optimization
Uses:
Uses • Marketing Campaign Analysis Uses
• Ad Targeting • Sentiment Analysis • Risk modeling
• Network Data Analysis • Point of Sale • Customer attrition analysis
• Search quality • Trade surveillance • Recommendation engine
• Data Sandbox • Threat analysis (fraud detection)
11
The Business Value of Big Data
A real example in Media
Quality of Service is a key business demand for digital TV providers and presents a number of
technical challenges. Tracking infrastructure and client hardware components can generate a range of
unstructured data at huge scope and scale. Aggregate views reveal patterns that enable timely issue
resolution and enable new business opportunities
MongoDB and
MapReduce
High Quality of build aggregate views
Service - Session, Loc.,
Customers receive Timeline, CDN stat
Quick resolution of etc.
service issues
12
The Business Value of Big Data
A real example in Consumer Goods
13
The Business Value of Big Data
A real example in Financial Services (1/2) – Collecting Social Data
2.5 mln.
Demographic profiles
1.7 mln.
s (name, clients 300k profiles
birthdate) with high
matching
probability
14
The Business Value of Big Data
A real example in Financial Services (2/2) – Outcomes
Opinion leaders
16