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Data monetization webinar

Sales Head Big Data Analytics um IBM
24. Oct 2018
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Data monetization webinar

  1. Karan Sachdeva IBM Asia Pacific karan@sg.ibm.com M- +65 9028 3694 Effective Data Monetisation Strategies
  2. 2 1. Unlimited and Complex 2. Blending and sharing 3. Valuable when Real time Data has been called “the new oil” However, I believe that data is more than the new oil. Data is- Data Monetization = Economic Value: Reducing Cost, Increasing Revenue and Managing Risks
  3. Data Monetization Maturity Model AI and Data Science is basis of data monetization Operational BI and Data Warehousing Self-Service Analytics New Business Models TRANSFORMATION Value MODERNIZATIONCOST REDUCTION INSIGHT-DRIVEN Most are here 83% of organizations view AI as a strategic opportunity 3Descriptive Analytics Predictive Analytics Prescriptive Analytics
  4. 4 Data Monetization Challenges are compounded by the ever increasing volume of data and the need for AI of data is either inaccessible, untrusted or unanalyzed80% of data scientists’ time is productively utilized – rest is spent finding, cleaning, organizing data20% only of organizations are able to get value from their data15% only AI Create a trusted analytics foundation COLLECT Make data simple & accessible ORGANIZE ANALYZE AUTOMATE Scale insights on demand TRUST Achieve trust & transparency Apply ML everywhere of enterprises do not yet understand the data required for AI algorithms 81% IBM Cloud / © 2018 IBM Corporation
  5. Top 5 Best Practices to do successful Data Monetization 2. Getting the foundation right- Infuse AI and Data Science 3. People: Data Engineers, Data Scientists, CDO and LOB Executives 4. Robust Business Model Construct- How will you charge back? 5. Trust and Ethics- Glorify in constraints of regulatory pressures and data protection/privacy. 1. Use Case Generation and Prioritization: Identifying your customers needs and aspirations Five Key Recommendations to Innovate with Machine Learning and Big Data
  6. 1. Use Case Generation and Prioritization Financial Services Insurance • Credit Scoring • Fraud /Risk Analytics • Compliance- GDPR, PDPA etc • Customer Segmentation • Customer Acquisition • Predictive credit card churn analytics • Customer Insights • Network Optimization • Data Partnerships • Localization • Predictive maintenance • Loyalty programs • Upsell/Cross sell • Agile Supply Chain • Next Best Offer/Action • Connected Store • Operational Data Store • IoT – Stores • Connected: Car, Plane, Equipment • Agile Supply Chain • Predictive Maintenance • IoT Data enabled “Smart Services” Manufacturing Industrial Automotive • Border Control • Public Safety / Intelligence • 360 Tax payer • Tax Optimization • Cyber Threat • Citizen Self Service • Social Services Fraud Telco Media Utilities Retail Ecommerce Government Public Sector Data Virtualization 360 view of all your data Enterprise Data Catalog Shop for Data Data Science Engine Collaborative Data Science
  7. 2. Integrated Modern Analytics Platform IBM Cloud Private for Data (Multi-Cloud) Business Users & Analysts Data Engineers App Developers Data Scientists Data Stewards Custom Extensions Enterprise Cloud Microservices Containerized Workloads Multi-Cloud Provisioning Data & AI Microservices Analyze Data Trust AI Infuse AIOrganize DataCollect Data 7
  8. 8 3. Get the people equation right Increases workforce productivity across the analytics lifecycle – governed seamlessly Architects data pipelines and ensures operability Gets deep into the data to draw insights for the business Works with data to apply insights to business strategy Plugs into analysis and code to build apps DEPLOY COLLECT Data Engineer Data Scientist Business Analyst App Developer Governs data and ensures regulatory compliance Data Steward CXO Sys Admin Access data Transform: cleanse Create and build model Evaluate Deliver and deploy model Communicate results Understand problem and domain Explore and understand data Transform: shape ANALYZE ORGANIZE
  9. 5 X R O I 4. Business Model- How will you charge back? 1. Start with estimating ROI for business. 2. Charge as-a-service to business units. 3. Sometimes it could be too strategic to put dollar value. 4. External monetization charge as per insights created
  10. 10 Manage fluid data with built-in protection and compliance (e.g., GDPR) Profile, cleanse, integrate and catalog all types of data AI-based Metadata Management and Data Lineage Persona-based experiences with built-in industry models Govern data lakes and data warehousing offloading 5. Trust & Ethics Create a trusted, business-ready analytics foundation Containerized Integrated End to End Analytics Platform Seamless hybrid and - multi-cloud support Ethical and Trusted Data IBM Cloud Private for Data Policy and business driven visibility, discovery and reporting
  11. Under the Hood of Data Monetization Architecture- IBM Cloud Private for Data 2 3 IBM Cloud Private 4 5 6 1. Leverages Open Ecosystem included but not limited to Tensorflow, Spark, Hadoop, kubernetes etc). 2. Role based Enterprise Collaborative AI Ready data platform 3. Connect to all data sources seamlessly with Data Virtualization 4. Use Intelligent machine learning based Governance Catalog 5. Manage and deploy Data Science and ML models 6. Run in any public cloud or private cloud
  12. Benefits of choosing IBM Cloud Private for Data based architecture 1) Deploys an information architecture for AI 2) Modernizes your data estate for a multi-cloud world 3) Makes your data ready for AI 4) Infuses AI everywhere, with confidence 5) Puts open source to work 12
  13. Enabling Data Monetization for leading businesses 13IBM Cloud / © 2018 IBM Corporation Transforming banking with HPaaS - Hybrid Platform as a Service Australia High performance Computing with IBM Cloud for VMWare Australia Australian Federal Government signs a $1B agreement for Cloud & AI Australia Award-winning visual effect company choses IBM Cloud (Bare Metal) India A big data platform to be more res- ponsive and lay the foundation for IoT Indonesia Industry-first intelligent chatbot build on Watson. Singapore Reinventing the shopping experience with AI Korea Empowering employees with expert knowledge with Watson Australia Changing their business model with IBM Cloud Private. Vietnam India Improved decision-making with self-service analytics Creating a digital enterprise by leveraging Cloud & Analytics India First of a kind “Data Science Sandbox as a Service” platform, built on IBM Cloud Private for Data Singapore
  14. IBM industry leadership The Forrester Wave Predictive Analytics & Machine Learning The Forrester Wave Machine Learning Data Catalogs The Forrester Wave Conversational Computing Platforms IBM IBM 14 IBM #1 in AI Market Share Industry Design Awards Reddot Design Awards IBMIBM
  15. Engage experts to monetize your data and get results in less then 4 weeks IBM’s Data Science Elite team IBM Cloud Private Experiences What do we offer? ü Free 14 days Sandbox for IBM Cloud Private for Data. ü Experience a 20 minute guided journey to build AI- powered applications ü Get hands-on with 14 days of free, hosted access and schedule 30 mins expert consultations ibm.biz/experienceICP4D Ibm.com/analytics/expert-advice Join us at APAC AI Council An exclusive community of like minded business and technology leaders to be the first to learn about a new ideas in AI, ML and data science space https://goo.gl/forms/Z4funOJnWf6OFKHz2 What do we offer? ü Free onsite engagement ü Identify use case(s) & Minimal Viable Products via discovery & design workshops ü Collaboratively build & evaluate data science and machine learning models ü Mentor & enable client teams hands-on www.ibm.com/analytics/ globalelite/ibm-analytics-data-science-elite-team
  16. Join IBM at Gartner Symposium/ITxpo from Nov 13th-16th in Goa, India Learn more- https://ibm.biz/GartnerSym_web
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