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In:Confidence 2019 - A foundation for Insight in a data-rich world


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Jason Perkins, Head of Data & Analytics Architecture, BT, talks about the BT data strategy on the In:Confidence 2019 main stage (April 4th at Printworks, London).

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In:Confidence 2019 - A foundation for Insight in a data-rich world

  1. 1. British Telecommunications plc 2017 Foundations for Insight in a Data Rich World In Confidence 2019 16h March 2019 – v2F Jason B Perkins 1 In Confidence
  2. 2. British Telecommunications plc 2017 A connected and converging World Device Data Internet of Things Engineering Data (CSP) Web / App analytics Customer Premise Equipment STB & TV Data Network Data Multi channel Digital Store JBP Calls Social media Web Chat External datasets Billing, Interactions Orders ‘The world is one Big Data problem.’ Andrew McAfee, MIT Digital The amount of data being generated every day is increasing exponentially. Evolving technology can generate insight & value from that data
  3. 3. © British Telecommunications plc 2017 Technology – Architecture & Strategy3 3 The strategy is being tested (and adjusted) through introducing a series of lighthouse cases. Our Pan IT data strategy is more than a technology play; we are fundamentally shifting to a human centred, insight driven & service oriented mind-set. It is made up of five key pillars: How does DARA fit into the Data strategy pillars for a Business IT transformation A Pan-BT data strategy Data vision & principles Data use case Catalogue Data & Analytics Reference Architecture (#Dara) Data Assets & Tech Roadmap Data Culture Future data skills plans Governance, Operating Model & Funding approach
  4. 4. © British Telecommunications plc 2017 Technology – Architecture & Strategy4 Pan-BT data strategy - Data Vision and Principles “An organisation where data and insight power and inform BT strategy, delivering differentiated customer experience, operational transformation and converged services.” Centre of excellence organisational model Exploratory and production environments High levels of re-use and automation Data democratisation and agility Data-sharing culture and best practice Effective and appropriate governance • Common data assets and services • Shared analytical capabilities • Metadata and marketplaces • Intelligent automation • Data democratisation – everyone empowered to use data and insight • Use case catalogue tailored to business need. • Data Security & Privacy by design foundation. • Migration to distributed from centralised / decentralised models • Clear accountability between hub and spokes • Ability to experiment easily with low cost of entry & elastic capacity • Ability to simplify productionisation • A Culture of sharing data assets. • Self-service / data democratisation • Effective use of scarce skills • Attitude to experimentation and failure • Clear governance • Clear funding model • Rationalisation programmes • Data quality programmes
  5. 5. © British Telecommunications plc 2017 A Data & Analytics Reference Architecture 5 “The most important thing is to never stop questioning.” Albert Einstein
  6. 6. © British Telecommunications plc 2017 Technology – Architecture & Strategy6 The DARA is an architecture blueprint, a representation of BT as a data platform BT Data & Analytics Reference Architecture • Data centric approach with common information assets based on a Business Information Model (BIM). • Speed up Time to insight. • Democratise access to information through Self- service. Data Security & Privacy by design foundation • A Service oriented architecture on an event based architecture • Freedom to experiment • A OMNI digital brain to drive richer experiences, decision automation and business efficiency.
  7. 7. © British Telecommunications plc 2017 Technology – Architecture & Strategy7 Organise – Data Privacy & Security Services Data & Analytics Strategy  Data Privacy & Data Security services provides capabilities to enable data democracy, insight identification and usage of data assets whilst protecting our data assets.  Enterprise single sign on for authorisation & authentication.  Enabled via a data policy service for data access.  Data Policy Engine – service to to apply rules and policies to anonymise data whilst retaining its analytical value. Linkage over time while offering options for reducing risk of data identification.  Audit Services: provision of audit trail  Principles  ‘Defence in depth’ applied with multiple layers relating to privacy and security of information.  Proactive not Reactive: Preventative not remedial  Privacy as the Default Setting  Privacy Embedded into Design  End to End security: Full lifecycle protection  Visibility & Transparency: Keep it Open  Respect for user privacy: Keep it individual and user-centric  Built to International Information Privacy & Security Standards. Person Identifiable Data Person Identifiable Derivations Pseudonymisation & Encryption Consent & Preferences Aggregation & Summarisation Virtual Data mart Data Policy Service Audit,DataWatermarking&Logging Data Access Service Authorisation & Authentication Role Based Access Control JBP
  8. 8. British Telecommunications plc 2017 Summary 8 ‘Data & Analytics are the No. 1 priority in CIO survey 12 out of last 13 years. Capability expected to most help business differentiate from their competitors.’ Gartner DA Summit
  9. 9. © British Telecommunications plc 2017 Technology – Architecture & Strategy9 Digital businesses treat data more centrally – with business models, propositions and experiences completely underpinned by data Data Strategy is more than a technology play; fundamental shift required to a human centred, insight driven & service oriented mind-set. Data Privacy and Data Security services are important foundations in order to democratise access to information Organise – Foundations for Insight in a Data Rich World Data & Analytics Strategy
  10. 10. © British Telecommunications plc 2017 Technology – Architecture & Strategy10 1. Data Strategy and the Enterprise Data Executive, by Peter Aiken and Todd Harbour. 2. Competing on Analytics, the new science of winning, by Thomas H. Davenport and Jeanne Harris 3. Sentient Enterprise – Evolution of Business Decision Making, by Oliver Ratzesberger & Mohanbir Sawhney 4. DW 2.0: The Architecture for the Next Generation of Data Warehousing, by W. H. Inmon and Derek Strauss. 5. Modernize the Data Warehouse: Designing An Architecture for Data and Analytics, Mark Madsen 6. The Active Data Warehouse: Where Agile Retailers Win by Capitalizing on Time 7. Governing the Data Lake: The critical importance of an Information catalog, Mike Ferguson 8. Logical Data Lake and Logical Data Warehouse, Rick F. van der Lans 9. Chief Data Officer Playbook, by Caroline Carruthers and Peter Jackson 10. Gartner End-to-End Data and Analytics Reference Architecture 11. Gartner Data Architecture: A How-to and Why-to Guide 12. 451 Research - Selecting a best execution venue for data in the cloud 13. Gartner Modern Data Management requires a Balance between Collecting Data and Connecting to Data 14. Gartner Data Catalogs Are the New Black in Data Management and Analytics 15. Gartner How to Enable Self-Service Analytics and Business Intelligence 16. Forrester The Dawn Of Digital Decisioning, By John R. Rymer & Mike Gualtieri 17. Pan BT IT Data Strategy roadmap briefing, By Rob Holtom & Jason Perkins, August 2018 18. BT GROUP Plc – Design Council Discussion Paper : Data Architecture, Phil Radley & Ian Walton, Jan 2015. 19. Cognitive Architecture : Models for Operation and Implementation, Simon Thompson & Rob Claxton, April 2018. Want to know more? References
  11. 11. Digital Transformation driven by Data & Analytics