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View Course Highlights
Business Intelligence (BI) has made data the foundation of decision making since the 1990s. Today, digital business is fundamentally reinventing decision making, by putting information from every person and data from every sensor at decision makers’ fingertips. It challenges them to use it to address every aspect of business, to create anew every existing process, and to reinvent, not just decision making, but the entire enterprise.
Call it BI or analytics, serve it from a warehouse or a lake, it doesn’t matter. And now, with new patterns, such as data fabric, mesh, and lakehouse, the implications span the entire business and IT environments across the full breadth of the organisation.
Modern architectures, technologies, and methods in data management and analytics incorporate all today’s technological advances in databases, NoSQL stores, and data preparation, as well as SOA, metadata, distributed access, collaboration, etc. And they directly address current issues, such as operational BI and analytics, strategic decision making, analytics, information discovery, and enterprise-wide decision management.
Expanding from his comprehensive and respected book “Business unIntelligence” to the Digital Information Systems Architecture (DISA), including emerging topics such as the Internet of Things, algorithms, and artificial intelligence, Dr. Barry Devlin charts the essentials of data warehouses, data lakes, and beyond, as well as BI and analytics to build a digital business from the existing IT systems running enterprises today.
Drivers, structure and components of decision-making support architectures
Data and Information—for data warehouses, marts and lakes
Possibilities and challenges of new database and data management technologies
Formal and Informal processes—getting from information to action
The meaning and importance of data fabric, data mesh, and data lakehouse
Data virtualization and preparation tools for integration across warehouses and lakes
Positioning and using algorithms and analytics in support of decision making
People—action-oriented decision making
The importance of business context and user roles in decision processes
Planning and implementation—practical steps for building modern warehouses, lakes and BI
Course Outline
Digital Business—History and Emergence
A brief history of decision-making support
Origins and meaning of digital business
An architecture combining data warehouses, lakes, and emerging patterns
The emergence and impact of big data, the Internet of Things and artificial intelligence
A new layering approach—Information, Process, and People
The pillars of a new architecture that supports multiple storage technologies
The Information Resource—the foundation for everything
Information/data classes—human-sourced, machine-generated and process-mediated
Big data—hype and reality, sources and types, implications for business and IT
Key considerations—timeliness/consistency, structure/context, and reliance/usage
Metadata as information—sources and stores, tools and techniques
Relational database evolution—structures, software and hardware
New information resource patterns—data fabric and data lakehouse
NoSQL data stores, Hadoop-based databases, XML, JSON-based and other data stores
The Business Processes—getting from decisions to 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
A modern population and governance pattern—data mesh
Service Oriented Architecture and Microservices
A model for decision making and action taking—the adaptive decision loop
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
Augmenting and/or Automating decision making and action taking
The emergence and importance of artificial intelligence
Planning and implementation
Evolution—not revolution
The Staged Implementation Roadmap
Organisational considerations; changes in IT culture and responsibilities
Selected possible first migration steps
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, 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 (www.9sight.com), 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 returned to Europe, Barry’s knowledge and expertise are in demand both locally and internationally.
Essentials of Data Warehouses, Lakes and BI in Digital Business. 2-Day Virtual Course.