My focus on data analysis comes from studying with SPSS and MATLAB in university studying Economics/Mathematics. Most of my professional experience comes mostly from SQL and Excel.
As a universally recognized tool across every business industry, proper data analysis can always make a difference. Delivering insight to market trends, customer satisfaction, resource allocation, effort optimization, goal realization, and product development- Data Analysis is a powerful tool when used accurately.
The varying focus of data analysis depends mostly on the industry. The obvious uses in finance/economics, sales analytics, data mining, or statistical modeling, but data analysis and algorithms are also heavily important for tech simulations, 3D modelling, and automation/movement. Each focus will carry it's own standard set of mathematic areas of concentration, but by nature data analysis should not be solely dictated by the norm.
Whether presenting data or visual reports, analysis should always be presented to highlight significant events without discretionary bias. It is understood that data analysis should properly identify trends and provide an accurate portrayal, but there are limitations to how far scientific data analysis will take you.
For one, the big achilles heel of data analysis is anything new. It is difficult to correctly assess anything for which no data exists. While there are always secondary sources of information, they shouldn't hold too much sway when moving into uncharted territory.
There are many different applications and tools at an analyst's disposal, but most tend to stick with the methods in which they were trained. As a dedicated data analyst one would become a specialist in pinpointing accurate data effectively and precisely. As a business consultant with a wide range of responsibilities I've worked with different aspects as needed to deliver the relevant results. The downside is lack of specialty, the benefit is a wide range of experience and the confidence of comfort for each ; this helps tremendously when understanding presented data analysis, if less with the legwork.