Open-BDA Hadoop Summit 2014 - Mr. Krish Krishnan (Driving Business Value – Big Data Platforms)
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The document discusses the impact of big data on business and the necessary shift from traditional engagement models to data-driven analytics, particularly for the millennial and Gen Z consumers. It emphasizes the challenges organizations face in harnessing big data effectively and suggests that successful implementation requires ownership of big data programs, data discovery, and quality processes. Additionally, it highlights the evolving landscape of analytics and the importance of integrating various data sources to derive actionable insights.
Open-BDA Hadoop Summit 2014 - Mr. Krish Krishnan (Driving Business Value – Big Data Platforms)
- 1. Driving Business Value – Big Data Platforms Hadoop Summit Karachi, Pakistan Nov 18th 2014
- 2. Content and services via connected products Page 4 Hortonworks © 2014 New routes to market via intelligent objects Everything has a URL Remote sensing of objects and environment Augmented reality Building and infrastructure management Cameras and microphones widely deployed Over 50% of Internet connections are things: 2011: 15+ billion permanent, 50+ billion intermittent 2020: 30+ billion permanent, >200 billion intermittent Situational decision support Source: Gartner Keynote at Hadoop Summit 2013
- 3. Disruption: It's Not Just About Technologies Identity/Access Management Speech Recognition Computer- Brain Interface Truth Verification Object Identification Linux Wikis Grid Computing Tablet PC Information Extraction Location-Aware Services Semantic Web Service-Oriented Architecture Unified Communications Ultra Wide Band RFID Social Network Analysis Web-Services- Enabled Business Models Electronic Ink/ Digital Paper Web Services Instant Messaging VoIP Sensor Networks Smartphone Really Simple Syndication Augmented Reality 4G Wireless Blogging Podcasting IP Television Location Sensing Design Innovation Proactive Transparency Personalized Pricing Counterfeit Reality Collective Intelligence Perfect Recall Real-Time Enterprise Ubiquitous Access Smart Objects and Ambient Intelligence Privacy Redefined Global Sourcing Business Process Management Voice/Data Convergence Microcommerce Self-Sufficiency Greenfield Business Global Micro-Business Seamless Service to Self-service Feedback Society Semantic Connectivity Emerging Technologies Emerging Capabilities Emerging Business Models @copyright Sixth Sense Advisors 2014 3
- 4. From Transactional to Behavioral @copyright Sixth Sense Advisors 2014 The challenge facing the business today is the ability to influence the buyer decisions in a window of opportunity that does not last long. The analytics available at a personalization level drives the buyer whether it is choosing a Doctor or buying a Donut. To compete in this new era, businesses need to be driven by data and analytics, which are largely different from traditional transactions and campaigns The “Gen Z” and “Millinieal Generation” of buyers will not be swayed by traditional engagement models of selling products and services 4
- 5. A Growing Trend @copyright Sixth Sense Advisors 2014 5
- 6. Executive Ask •Why is our competition performing better in the same markets as us? •What is the real revenue impact to the organization? •Why do our campaigns not predict the accurate revenue lift? •How can we improve our brand and align to customer sentiment? •Who can help us get to the bottom of the data abyss? •When do we get the real insights from Analytics? @copyright Sixth Sense Advisors 2014 6
- 7. Forces Shaping Business @copyright Sixth Sense Advisors 2014 7
- 8. Business Evolution – Product to Customer Focus Shifts @copyright Sixth Sense Advisors 2014 Image source - internet 8
- 9. Decision Support – Now & Then @copyright Sixth Sense Advisors 2014 Customer Promotion Social Presence Behavior Analytics Competition Market Value Transactions Price Product Channel Sales Promotion Market Price Transactions Customers 9
- 10. Innovation as Way of Life @copyright Sixth Sense Advisors 2014 Old Brick New Brick 10
- 11. State of Data @copyright Sixth Sense Advisors 2014 11
- 12. Big Data •Data that cannot be processed using traditional data processing techniques due to size, scale and formats •Its beyond just that –Complexity –Ambiguity –Veracity @copyright Sixth Sense Advisors 2014 12
- 13. Noise vs Value @copyright Sixth Sense Advisors 2014 Is Big Data Noise or Value? Is Big Data a passing hype? Is there real value behind Big Data? Is there any measurable and actionable insight from Big Data? Is there a need to invest in this now? Image source - internet 13
- 14. @copyright Sixth Sense Advisors 2014 14
- 15. Example @copyright Sixth Sense Advisors 2014 Tweet: @jdoe – very disappointed with @united @checkin lousy svc, bad mgmt, long lines #fail. 20000 retweets. 4 hours ago IT Perspective Text of 140 chars will be stored as string. The data model for this will be a table with source, content, datetime. Business Perspective User – JDoe Brand – United Sentiment – Negative Process – Check-in Time – Waiting in long lines Impact – shared 20000 times in 4 hours 15
- 16. Why Does Big Data Differ @copyright Sixth Sense Advisors 2014 IT does not know data Business knows the intelligence to be applied to the data to derive value Business knows how to discover data patterns (manual and automated) Business understands the semantics better Business can perform data interrogation in an experiment and associate rules of engagement early on for data usefulness Business can sift the data to curate the context Big Data needs to be curated to be useful 16
- 17. @copyright Sixth Sense Advisors 2014 17 Source: McKinsey Presentation on Marketing
- 18. Big Data Challenges @copyright Sixth Sense Advisors 2014 Complex Ambiguous Formats / Availability Minimally Organized Complex Data Quality Issues Metadata / Semantics Needs Intervention Needs Discovery / Contextualization Needs Analysis 18
- 19. Perspective @copyright Sixth Sense Advisors 2014 Data Insights 19
- 20. The Paradigm Shift @copyright Sixth Sense Advisors 2014 IT •Facilitate •Maintain •Support •Manage Business •Driver •Budget Sponsors •Program Owner •Define & Consume IT •Driver •Program Owner •Budget Sponsor •Maintain •Support Business •User Data Warehouse Big Data 20
- 21. Analysis @copyright Sixth Sense Advisors 2014 21
- 22. Processing – The Details @copyright Sixth Sense Advisors 2014 Tag Categorize Classify Cleanse (Data Quality Rules) Semantic Integration Measure Visualize 22 Big Data Platforms
- 23. Future Visualization @copyright Sixth Sense Advisors 2014 23
- 24. Big Data Architecture @copyright Sixth Sense Advisors 2014 Big Data Sources Hadoop (and / or NoSQL) Traditional Data Sources ETL ELT CDC Staging Or ODS ETL ELT EDW BI Analytics Discovery Data Mining Algorithms Acquire Big Data Analytics 24
- 25. @copyright Sixth Sense Advisors 2014 25
- 26. Infrastructure Infrastructure Challenges & Solutions Challenges To Address Semantic Data Integration Compression & Storage High Capacity Warehouse Security and Governance Scripting and Development Tools Complex Event Processing Solutions Available Today Columnar Databases Workload Optimization Analytic Accelerators Hadoop / Map Reduce No SQL Engines Stream Computing @copyright Sixth Sense Advisors 2014 26
- 27. Big Data Analytics @copyright Sixth Sense Advisors 2014 Existing EDW Machine Learning Text Mining Analytics Coding & Learning Semantic Knowledge Base Metadata & Semantic Layer 27
- 28. 28 Dealing with Big “Data Problems” Data silos in disjointed systems Multiple data sources - overlapping, conflicting Timely processing of large volumes of data Partial, inaccurate, inconsistent.. data 28 Single Data Platform
- 29. Reports Analytical DBMS Analytics Cluster Data Asset Catalog Analytical DBMS Dashboards Data Discovery Interactive Queries Batch Queries Web Applications Activity Logs NoSQL Reference Data Device Apps Probes 3rd Party Device User Profile POI, Map Activity Sensor Data Intake ETL, data crunching, attribution, ML Algorithms Aggregation HDFS Analytical DBMS Big Data Analytics Platform Data Flows 29 @copyright Sixth Sense Advisors 2014 29
- 30. Analytics •Behavioral Analytics •Cohort Analytics •Collections Analytics •Competitive Analytics •Financial Services Analytics •Fraud Analytics •Marketing Analytics •Pricing Analytics •Sales Analytics •Risk Analytics •Supply Chain Analytics •Talent Analytics •Channel Analytics •Logistics Analytics @copyright Sixth Sense Advisors 2014 30
- 31. Trends 2015 •Business Users Drive Big Data Initiatives •Analytics is the “new” center stage •Data Discovery and Storyboard Patterns Emerge Stronger •Hadoop-Based Data Lakes / Swamps Unite with Data Warehouses •Predictive Analytics Lend Fresh Insight From Big Data Explorations •Prescriptive Analytics Bring New Insight to Current Business Processes @copyright Sixth Sense Advisors 2014 31
- 32. Measuring Value Increasing Revenue / Opportunity / Market Lowering Costs / Risks / Maintenance Value @copyright Sixth Sense Advisors 2014 32
- 33. Critical Success Factors @copyright Sixth Sense Advisors 2014 Business needs to own and execute the Big Data program Data collection and discovery is the most critical step Metadata is needed to process the data prior and post Data Warehouse integration Data quality can be processed by integrating Taxonomies Data visualization is needed to discover data Metrics and Metadata will be the bridge to integrate to the Data Warehouse 33
- 34. Questions @copyright Sixth Sense Advisors 2014 34
- 35. Thank You Contact rkrish1124@yahoo.com Twitter: @datagenius Images Source - Internet @copyright Sixth Sense Advisors 2014 35
- 36. References •Gartner •McKinsey •MIT Innovation Labs •Google •Facebook •LinkedIn @copyright Sixth Sense Advisors 2014 36