Looking at Large Datasets in many different ways allows relationships between the data to be identified. Some of these relationships may be obvious, but others are certainly not. Finding dependencies between different data leads to insights in what is happening within your dataset. TPL will use machine learning to help find dependencies, but we find that the best insights come with an understanding of why the identified dependencies exist.
Insights alone may improve understanding, but these insights must be leveraged into decision-making to have an impact on performance. TPL has the upstream Domain Expertise to translate Insights into business Opportunities.
We can also suggest optimal strategies to implement identified models into upstream technical processes.
Data Science as a discipline is technology agnostic i.e. the technology used is not "Data Science". The technology used is only a set of tools to assist in carrying out the scientific investigation.
TPL uses tools that are appropriate for each task. Some of these tools are: MS-Excel, MS-PowerBI, OpenRefine, R-Project, Orange3, Python, SageMath, Scikit-Learn.