The document discusses the technological tipping points of big data and blockchain, highlighting their importance for enterprises in adapting to rapid technological changes. It presents various use cases for big data across sectors such as social media analytics, finance, retail, and manufacturing, as well as explaining blockchain's role in enhancing transparency and efficiency in business operations. The document emphasizes the need for businesses to leverage these technologies for competitive advantage and outlines their potential future applications.

1. Technology Tipping Points:
Bigdata and Blockchain
BY
VINOD KUMAR NERELLA
31/12/2016

2. Agenda
• Introduction to Big Data and Block Chain
• Use cases with Big Data
• Use cases with Block chain
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3. Why we need to talk about tipping points ?
• Now a days, if you back to sleep another tech wave passes by.
• All enterprises are realized that doing nothing is not an option.
http://www3.weforum.org/docs/WEF_GAC15_Technological_Tipping_Points_report_2015.pdf
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4. • Big Data
• Block chain
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5. Big Data
• Volume
• Velocity
• Variety
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6. Social Media Analytics – Online Brand Management
•Identify market trends
and behaviors as they
surface to unlock new
business opportunities.
Market Research &
Insights
•Measure sentiment and
reputation to know how
consumers perceive
your brand.
Brand
Management •Discover every segment
of your audience to
build targeted outreach
and win new fans.
Customer
Segmentation
•Track consumer
response to new
campaigns and
offerings to ensure
positive feedback.
Product &
Campaign Launch •Detect and manage
crises before they
escalate to protect
brand reputation and
loyalty.
Crisis
Management
•See the complete view
of each customer by
connecting social data
to all your systems.
Customer
Management
Engage Listen Analyze Monitor
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7. Financial Services Use Case
ETL Augment, Retail Banking
& Capital Markets
•Mine Customer emails, CDRs to provide BI
functionality - CRM
•Range of use cases across Capital Markets
SingleView of
Customer
•Wealth Management
•Retail Banking
•Capital Markets
Risk Management
•Credit rating
• Fraud Detection
Digital
Transformation
•Real-time analytics
•Predictive analytics
•Customer Journey
•Micro & Macro persona
marketing
Data Products
•Cross Company Datalike
•Being leveraged across
mortgage banking
•More use cases
emerging
Risk Mgmt
Cyber
Security
Fraud
Detection
Predictive
Analytics
Data
Compliance
Digital Banking
360
degree
view
Data
Quality
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8. In Retail Industry
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9. Customer segmentation process
Portfolio
Digital
Transactions
Ancillaries
Preferences
Trade
Systems
Other
finance
systems
Customer
Master
Social
media data
Assign Customers
to Segments
• Ultra High net
worth
• Platimum
• Gold
• Silver
Discover Segments Visual Analytics
Pattern Discovery
Recommendations:
Calibration on Historical Data Incrementally add new Data
• Customer Realignment
• Design targeted
promotions to improve
performance in specific
markets
Data Sources Data Ingestion Data Processing Actionable Insights
Customer
Assignment Rules
Account
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10. Manufacturing – Big data use cases
Customer Experience &
Design
Supply Chain
Efficiency
Manufacturing Optimization
Top 3 Manufacturing Business Priorities Manufacturing Use Cases
 Connected Manufacturing
 Yield & Quality Optimization
 Control Quality proactively with Real-time Manufacturing data Insights
 Track Product Returns for Defects
 Predictive Equipment Maintenance to avoid manufacturing stoppages
 Energy Management
 Product Monitoring with Telemetry – Connected Products, Connected Equipment
 Customer Insights from Product Usage
 Single view of Customer / Product / Manufacturing Process
 Insights for Improved Product Design
 Granular n-tier Supply Chain Visibility, Serialization & ePedigree
 Assure Just-in-Time Delivery of Raw Materials
 Supply Chain Risk Management
 Connected Logistics
 Increase Operational Efficiency
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11. Yield & Quality Optimization, Predictive Maintenance
Data modeling
Predictive Analysis
Machine Learning
Dashboards
Dashboards and alerts
Internet of
Anything (IoA)

12. Technical Architecture
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13. Bigdata + Data science
• Big -Data - the storage tanks
• Data science
• Data-driven science
• Interdisciplinary field about scientific
processes and systems to extract
knowledge or insights from data in
various forms, either structured or
unstructured, which is a continuation of
some of the data analysis fields such as
statistics, machine learning, data
mining, and predictive analytics.
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14. Block Chain
KEY TO A VERY DIFFERENT FUTURE, AN OPEN SOURCE
SOFTWARE CODE AND DISTRIBUTED LEDGER TECHNOLOGY
THAT SUPPORTS CRYPTOCURRENCIES (BITCOIN) THAT
PROVIDE THE TOOLS TO DELIVER DIFFERENT BUSINESS
OPERATING MODELS AND OUTCOMES.
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15. Block Chain
• A serial set of blocks that transaction information data in the chain of blocks linked to
previous block.
• A shared ledger technology allowing any participant in the business network to see THE
system of record (ledger)
Business Networks, Markets & Wealth
• Any business network is collection of customers, supplies, banks
and partners. No business exists in isolation.
• Business Networks are cross geography & regulatory boundary
• Wealth is sum total of value of goods & services across business
network
• Flow goods & services across business network is a Market
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16. • Anything that is capable of being owned or controlled to produce value, is considered an asset
• A participant is a member of a business network
• A transaction is an asset transfer between two or more participants
• A contract is set of conditions under which transactions occur
Assets, Participants, Transactions & Contracts
$
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17. How it works
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18. Blockchain in a nutshell
Shared
Contract
CryptographyShared Ledger
Consensus
Ensuring secure,
authenticated & verifiable
transactions
Business terms embedded in
transaction database &
executed with transactions
All parties agree to network
verified transaction
Append-only system of
record shared across
business network
Broader participation, lower cost, increased efficiency
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19. Bitcoin
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20. Smart Contract
• Low barriers to entry for a supplier and a
buyer to conduct the transaction.
• The “reputation” of blockchain participants‘
performance on past smart contracts will
help the highest-performing companies to
demand premiums.
• Smart equipment can replace human
contracting parties for certain transactions,
as in our example of the vending machine.
• Devices on the IoT can communicate with
smart contracts to keep track of the status
and state of smart contracts for settlements.
• Smart shipping containers could, for
example, automatically sell their surplus
capacity.
• Faster settlements using cryptocurrencies
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21. Other Various use cases
• Governments AcrossTheWorld AreTurning use it
• P2P or Distributed systems
• New business models
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22. Some more news on Blockchain
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23. References
• http://www.ibm.com/blockchain/
• https://www.cognizant.com/whitepapers/blockchains-smart-
contracts-driving-the-next-wave-of-innovation-across-
manufacturing-value-chains-codex2113.pdf
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24. Contact
E-mail: vinod.nerella@gmail.com
LinkedIn: https://www.linkedin.com/in/vinodnerella
Thank You…!
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