A serious, systematic, logical and quantified, value-driven ‘engineering’ approach to all data matters, as part of a larger systems engineering approach.
17:00 - Meet&Greet
17:10 - Introduction
17:15 - Tom Gilb - Real Data Engineering - part 1
18:00 - break
18:15 - Tom Gilb - Real Data Engineering - part 2
1. Data Engineering as a subset of 'systems engineering' (i.e. with hardware, netware, logicware, dataware, and peopleware),
2. Defining ‘engineering’ - properly. The Prof. Billy Koen approach.
3. The components of a systems engineering process, and a Data Engineering process:
a. quantified multidimensional qualities requirements, and resource-constraints, (quantify ’security’, ‘AI decision transparency’, 'Big Data Portability')
b. detailed-enough data architecture, in order to understand corresponding data attributes,
c. estimates of potential data-architecture impacts on multiple requirements. Side effects.
d. computable, dynamic, priority of implementation, (a values-to-costs, wrt risks, decision)
e. data architecture decomposition methods, (to prioritize critical results early)
f. measurement of incremental data-architecture effects. (to keep the ship on course)
g. dynamic design-to-cost, agile, architecture-process, like 'IBM Cleanroom', Quinnan
4. A systems-engineering (= data engineering) language (Planguage) for modeling data-engineering processes and problems.
5. Examples of how to always quantify all critical data architecture qualities requirements.
6. How can you learn to qualify as a real data engineer? (Universities do not teach it!)
7. Understanding data engineering stakeholders as a source of requirements.
Tom Gilb is currently a consultant, teacher, and author, known for the development of software metrics, software inspection, and evolutionary processes. He mainly helps multinational clients improve their organizations and methods by using 'evolutionary systems delivery'. His method is based upon the core ideas that all architecture focus has to be on delivering value to the stakeholders and that engineering principles and scientific methods must be used in planning and management of change projects using a formal engineering language. He has guest lectured at universities all over UK, Europe, China, India, USA, Korea – and has been a keynote speaker at dozens of technical conferences internationally.
Tom wrote a book 'Data Engineering' in 1976.