At Sixfootfour we feel particularly strongly about the value of data. It is the foundation of a business. Without data you have no history and without history you have no business.

There are two types of data projects.

The first is a project where there is a known problem and the task is to determine causes for the problem. This generally requires analysis that is far deeper than the traditional root cause analysis workshop.

The second is where there is knowledge that the data stores have significant value and this value is not being accessed. The client will say to us "tell me what I don't know about my business".

The steps for addressing the above are similar, but the starting point is different.

 Sixfootfour is not a software sales company. We do have relationships with companies that sell best in class software that assists in the capture and analysis of data. Rather, our approach to data analysis is to deliver bespoke solutions tailored to the specific needs of our customers.

Our focus is on 

1. Pattern analysis is the use of algorithms to uncover significant patterns in the same or disparate data sets. This solution allows us to address the common issues of incomplete or dirty data. We also resolve the issues associated with the absence of a unique identifier, or common key between records. This issue is a major roadblock in data analysis projects when more than one database houses the data.

2. The 'So What' question is a key requirement for our consultants. Data analysis will turn up as many facts / findings as there are data points. The skill is knowing which finding is a nugget of coal and which is a nugget of gold. Our approach is to understand the business drivers and to use the 'so what' question to qualify if the finding influences one or more business drivers, or if it just an (interesting) finding.

Our experience is that once a company has implemented a data mining solution, then they tend to repeatedly review only the data provided by the toolset. The data mining project is reduced to a dashboard of KPIs. Our service offering extends this capability and uncovers the value data mining projects typically miss.

Our principal data analyst is Gordon Hume.

Gordon Hume has a background in Applied Mathematics and Physics, and graduated BSc(Hon1) from Sydney University (1993). His postgraduate work in Computational Fluid Dynamics, researching both algorithm design and experimental methods, was done at Sydney University (Australia) and Warwick University (UK). He has extensive experience in teaching at both University undergraduate and graduate level, and extensive software coding and design experience gained over several decades.