In this seminar, Dr Barry Devlin lays the architectural foundation to enable you to take advantage of AI and IoT data in the context of data warehouses and lakes, operational systems, analytics and business intelligence.
With the enormous growth of data from Internet of Things (IoT) devices and social media, as well as the reinvention of business through analytics and artificial intelligence (AI), the time has come to revamp your information architecture, expand your technology, and upskill your staff to support automated and augmented decision making and action taking in a fully digital business.
A digital business combines the traditional physical environment and the modern digital world in transformative ways. In the process, it creates innovative opportunities for success as well as insidious threats to old ways of doing business. From finance to fashion, telecommunications to transport, businesses that reinvent their processes to become pervasively digitalized will survive and thrive; those that ignore this major shift will wither and die.
Digital business is built on three pillars. The first is data and information from the external, physical environment, captured on social media and from billions of IoT sensors. Second is the business and IT processes that use such data to drive decisions and actions, increasingly augmented and/or automated by AI. The third pillar is the people—staff, partners, and customers—who are the sole reason the business exists. I created the conceptual and logical “Business unIntelligence” architecture to design, interconnect and build these pillars.
Of course, old approaches, such as BI and DW are not going away. They remain central to business management, but must be extended with data lakes, streaming, and other concepts. Business unIntelligence builds on the foundation of current systems to facilitate easier adoption of all modern technological advances in databases, NoSQL stores, and data integration, as well as the old challenges of metadata, distributed access, collaboration, and more. It provides a comprehensive structure for full enterprise IT integration, and directly addresses current issues, such as operational BI, strategic decision making, information discovery and enterprise-wide decision management.
A particular emphasis for this seminar is the combination of IoT and AI that is emerging as a central aspect of the digital business. Artificial Intelligence has had a long and chequered history. Multiple periods of over-optimism have been followed by “AI Winters” since the 1950s. Now, AI has come of age and is being embedded in mainstream technology from cars to call centres, and smartphones to IT systems, enabled in large part by IoT. With pervasive IoT data describing the world; deep learning algorithms and cognitive computing analysing it; and robotics and autonomous vehicles using it, this current “AI Summer” is not going to fade. Preparing for the growing importance of IoT and AI in the business / IT environment is now mandatory.
In this seminar, Dr Barry Devlin lays the architectural foundation to enable you to take advantage of AI and IoT data in the context of data warehouses and lakes, operational systems, analytics and business intelligence. He positions traditional and emerging technologies and BI tools in the practical application of IoT and AI in the business world. Extrapolating from the rapid growth of AI and IoT in the consumer world, he shows where and how it will drive business and likely impact IT. Based on new models of decision making at the organisational and personal levels, he examines where to apply augmentation and automation in the roll-out of AI and provides initial thoughts on implementation planning. Finally, he addresses the ethical and economic implications of widespread adoption of artificial intelligence and the Internet of Things.
What you will learn
- The meaning and value of digital business
- What is AI? Evolution, key concepts, and terminology
- Understanding the IoT and its importance to AI as the new driver of business value
- A comprehensive architecture spanning from traditional data warehousing and BI to AI
- Approaches to applying AI to decision making
- The importance of user context and roles in decision making and action taking
- The role of infrastructure technologies, including Hadoop, NoSQL, NewSQL, AI, etc.
- Using data virtualization and integration tools for IoT and other data types
- Practical steps to evolving from today’s BI toward a new AI- and IoT-inclusive architecture
- Ethical and economic considerations for your business and society at large
Who should attend
- Enterprise, systems, solutions and data architects in data warehouse, BI and big data
- Systems, strategy and business intelligence managers
- Data warehouse and systems designers and developers
- Tech-savvy business analysts