My Digital FootPrint

Source :  worth observing that this Dilbert was 1993 !!!!  Radar and sonar are incredible inventions as they allow us to perceive what cannot be actually seen with the naked eye.  As technology has advance and big data analysis has emerged we have gone from a simple echo to high-quality resolution.  However, the peak value for Radar is that it informs you something is there which requires low resolution and very little data.  As Radar resolution has improved we can get direction and speed which requires a little more time. This new information definitely adds value to any required reactive decision. The identification of what the actual object is through increased resolution has an incremental value but not as much as knowing it is there and what direction at what speed but such information can lead to a better decision but suddenly there is an economics of cost compared to the incremental improvement in outcome.  Knowing what type of bird by species or wh...

It is all about averages.  If you have a single dimension data set, say height, with a large data set, it is probable that one user will be the average of the entire set. In a two-dimensional data set, height and weight, it is probable that one user may have these two characters as the average of the entire set. In a three-dimensional data set, inside leg measurement, height and weight, it is tending toward impossible that one user may have the three average characters of the entire set. More data makes it more probable, but also more characteristics make average persons more improbable, as mean, mode or medium. Facial recognition uses about 80 nodal points, it is (im)possible that a single data subject in large data set will be average on all points.    The point is that we think more data will create a better understanding of our users. This is unlikely to be the case. What we need to determine are the boundary conditions where the data we have access to enables b...

Data Governance is somewhat easier to define using wiki on 17th March 2019 Data governance is a data management concept concerning the capability that enables an organization to ensure that high data quality  exists throughout the complete lifecycle of the data. The key focus areas of data governance include availability, usability, consistency [1] , data integrity and data security and includes establishing processes to ensure effective data management throughout the enterprise such as accountability for the adverse effects of poor data quality and ensuring that the data which an enterprise has can be used by the entire organization. Data governance encompasses the people, processes, and information technology required to create a consistent and proper handling of an organization's data across the business enterprise . It provides all data management practices with the necessary foundation, strategy, and structure needed to ensure that data is managed as an asset and tran...