Overview

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Digital business starts with data and ends with people. The recipe: combine data from the entire physical world with the information generated by every human interaction, whisk lightly, and serve. The result: delighted consumers and profitable businesses, algorithmically delivered. If only it were so simple, so delicious…The destination is desirable for some but dangerous for others. Digital transformation will create innovative opportunities for new business and the welcome reinvention of old business ways. From finance to fashion, telecommunications to transport, businesses that embrace digital will thrive. Those that ignore this major shift or fail to adapt will wither and die. Prosper or perish. AI-enabled business promises neural network nirvana, whilst threatening digital dystopia.  The journey is no less scary, edged on one side with insidious threats to existing IT systems, and exposed on the other to the wide, open uplands of artificially intelligent tools and cognitively enhanced actions. Miss the opportunities of AI and plunge to the depths of data-driven despair.  What are girly swots to do for business success? How are spotty IT nerds to win fair maidens? The answer, as to all such existential questions, is to learn from the failures and build on the successes of the past, aptly adapted for the present, and carefully crafted for the future.

Old masterpieces, such as BI and DW, are the foundation for a digital business but only table stakes for survival. Data lakes, predictive analytics, social media, and the Internet of Things are but stepping stones to the digital future; as they stand, they won’t guarantee a thriving transformation.  We need a new IT architecture that reintegrates all decision making and action taking across all the people, processes and information of the coming digital era. An architecture that incorporates all the technological advances in databases, NoSQL stores, data integration and delivery, as well as the old challenges of operational BI, spreadsheets, metadata, virtualisation, collaboration, and more. That provides a comprehensive structure for information and process integration—with speed and consistency—across the entire enterprise. Built on modern tools and techniques, from object stores to cognitive computing, from algorithms to neuroscience, from on-premises to hybrid cloud.

Building on thirty years of data warehousing experience and expanding from his comprehensive and well-respected “Business unIntelligence”architecture to include a host of emerging topics, from smart things to neural networks, Dr. Barry Devlin charts a creative but realistic path from data warehouses and lakes, BI and analytics, to show how to design and build a digital business from the existing systems running your enterprise today.  With the clear and enormous impact of digital transformation, now is the time to start building the skills, organisation and infrastructure in architecture, technology and planning to build out your BI environment with AI and other emerging techniques to create a successful digital business.

All public courses are available as in-house training. Contact us for more information.

Learning Objectives

  • The meaning and implications of digital business
  • Drivers, structure and components of digital business architecture including:
    • The Business unIntelligence conceptual and logical architectures
    • Data and information—the foundation for everything
    • Formal and informal business processes—getting from information to action
    • Data collection, preparation, integration, and use in a digital business
    • Business context and meaning in information use
    • People—action-oriented decision making and engaging innovation
  • Technological foundations of information processing, traditional and emerging:
    • Database and data management technologies
    • Data virtualization and preparation tools for integration across warehouses and lakes
    • BI tools, analytics and algorithms in support of decision making
  • A dive into artificial intelligence and cognitive computing:
    • A brief history and explanation of AI evolution, key concepts, and terminology
    • Understanding how IoT and social media enable AI as the new driver of business value
    • Approaches to applying AI to decisions and actions: augmentation vs. automation
    • Technology needed to build business applications and manage and govern data for AI
  • Planning and implementation—practical steps for building a digital business
  • Ethical, economic, and social considerations for your business and society

Course Outline

Digital Business—History and Emergence

  • A brief history of decision-making support—from BI to AI
  • Origins and meaning of digital business
  • Rationales pro and con digital business

The Why and How of a New Architecture

  • The emergence and impact of big data, the Internet of Things and artificial intelligence
  • New, future-proof hypotheses for a new architecture
  • A new approach beyond layering—Information, Process, and People
  • The pillars of a new architecture that supports multiple storage technologies

The Information Resource—the Foundation for Everything

  • New classes of information and data—human-sourced and machine-generated—and how they interact with the traditional process-mediated data stores of the business
  • Big data and data lakes—hype and reality, sources and types, business and IT implications
  • Key considerations—timeliness/consistency, structure/context, and reliance/usage
  • New conceptual and logical architectures for all information and data
  • Metadata as information—sources and stores, tools and techniques, data modelling
  • Relational database evolution—structures, software and hardware
  • NoSQL and NewSQL data stores, object stores, and more
  • What’s happening to Hadoop?

Artificial Intelligence—History and Foundations

  • A brief history and directions of AI
  • Overview of artificial neural networks and other techniques
  • Directions for development and use

The Processes—Getting from Data/Information to Decisions and Actions

  • Data preparation, ETL, data warehouse automation,wrangling, and data virtualisation
  • The new role of users in “application development”
  • Understanding adaptive, closed-loop business processes
  • Service Oriented Architecture and Microservices
  • A model for decision making and action taking—the adaptive decision loop
  • How pervasive mobile connectivity, processing and storage combine with the Cloud to reinvent business processes

Managing and Governing Data in an AI-Flavoured World

  • Data sources for AI use
  • Data/information preparation and governance from external sources
  • Conflicting and overlapping data, erroneous data
  • The role and importance of context in gathering, preparing and using data for AI
  • Governance, privacy and other ethical issues
  • From exploration to production across data lakes, warehouses and operational systems

The People—Understanding Needs and Engaging Innovation

  • Motivation and the workings of the human mind in business systems
  • Classes of BI—information-centric, process-centric and collaborative
  • BI, analytic and other decision support tools
  • Decision-making and action-taking in a closed-loop, real-time environment
  • Beyond rational choice theory and the role of emotions and social behaviour in decisions

Applying AI to Decision Making

  • AI in information use and decision making / action taking
  • Operational, tactical and strategic decision-making considerations
  • Automation vs. augmentation—the importance of understanding the difference
  • Centralisation vs distributed processing
  • Model management

Planning and Implementation

  • Evolution—not revolution
  • The Staged Implementation Roadmap
  • Organisational considerations; changes in IT culture and responsibilities
  • Selected possible first migration steps

Building the Digital Business—Overarching Considerations

  • Ethical considerations for data-based analytics and AI in business
  • Wider ethical concerns for society
  • The impact of AI on the economy and employment
  • Avoiding societal breakdown

Who It's For

  • Enterprise, Systems, Solutions and Data Warehouse Architects
  • Systems, Strategy and BI/Analytics Managers
  • Data Warehouse/Lake and Systems Designers and Developers
  • Data and Database Administrators
  • Tech-savvy Business Analysts

Speaker

Dr. Barry Devlin

Founder and Principal

9sight Consulting

Dr. Barry Devlin is among the foremost authorities on business insight and one of the founders of data warehousing, having published the first architectural paper in 1988. With over 30 years of IT experience, including 20 years with IBM as a Distinguished Engineer, he is a widely respected analyst, consultant, lecturer and author of the seminal book, “Data Warehouse—from Architecture to Implementation” and numerous White Papers. His 2013 book, “Business unIntelligence—Insight and Innovation beyond Analytics and Big Data” is available in both hardcopy and e-book formats.  As founder and principal of 9sight Consulting Barry provides strategic consulting and thought-leadership to buyers and vendors of BI solutions. He is continuously developing new architectural models for all aspects of decision-making and action-taking support. Now based in Bristol, Barry’s knowledge and expertise are in demand both locally and internationally.

Data Ed Week 2-day Course: Essentials of Data Warehouses, Lakes and BI in Digital Business – Live Streaming and Face to Face

Data Ed Week 1-day Course: From Analytics to AI: Transforming Decision Making in Digital Business – Live Streaming and Face to Face

Fees

  • 3 days
  • £1,295
  • £1,295 + VAT (£259) = £1,554
Group Booking Discounts
Delegates
2-3 10% discount
4-5 20% discount
6+ 25% discount

Venue

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