What is a Data Driven Mindset? Why does it matter to identify Data Driven concepts? Starting from the basics, Data Driven “means that progress in an activity is compelled by data, rather than by intuition or by personal experience.
Master Solutions Architect
Data Engineer
Backend Developer
Integrated Systems Engineer
Systems and Industrial Integration
Master Solutions Architect
Data Engineer
Backend Developer
Integrated Systems Engineer
Systems and Industrial Integration
What is a Data Driven Mindset? Why does it matter to identify Data Driven concepts? Starting from the basics, Data Driven “means that progress in an activity is compelled by data, rather than by intuition or by personal experience.
[updated May 17, 2018] DigitalTransformation.Engineer This www.DigitalTransformation.Engineer website and blog site is a personal creation; a personal labor-of-love project. Through…
The term Data Mining does not convey the different aspects of data mining / knowledge discovery. The basic types of Data Mining are: Descriptive data mining, and Predictive data mining.
I first considered aspects of artificial intelligence (AI) in the 1980s while working for General Dynamics as an Avionics Systems Engineer on the F-16.
The operations system designer should perform content analysis. Content analysis is both qualitative and quantitative.
Predictive analytics is a combination of statistical analysis, behavior clustering, and system modeling. No one piece of predictive analytics can exist in a vacuum; … (3-part series)
Real-Time data is a challenge to any process-oriented operation. But the functionality of the data is difficult to describe in such a way that team members not well versed in data management. … (3-part series)
The Data-Information Hierarchy is frequently represented as
Data –> Information –> Knowledge –> Understanding –> Wisdom.
Or it is sometimes shortened to 4 steps, omitting Understanding. But, in fact, there are two predecessor steps: chaos and symbol. … (3-part series)
Data is never ‘in balance’, data always carries uncertainty, and the process cannot stop. Operations personally have learned to perform their job while waiting … (3-part series)
Moving knowledge within the organization is perhaps the most challenging aspect of corporate knowledge. Knowledge handoff must occur laterally and temporally.