Data processes benefit from a multidisciplinarian approach across qualitative and quantitative skillsets. Assessing the research design, data collection, data cleaning, analysis, results and reporting steps are all important components of robust data processes. Sometimes a fresh perspective or third party consultant or coach can help shore up potential weaknesses in process.

There is a nearly endless supply of data opportunities. Awareness of potentially untapped resources often requires a research background beyond the specific field in question.

There are multiple platforms for collecting, organizing and analyzing data across different types of operations and infrastructures. The best fit for a particular use involves balancing cost, simplicity, data platform collection approaches, and technical capacity to use particular analytic methods.

There are numerous statistical analytic softwares and platforms capable of modeling and simulation based on known and variable inputs. Experience modeling these simulations helps to properly contextualize and dial results in order to apply and garner feedback useful to processes.

Secondary data sources publish research collected from academic, governmental, philanthropic, journalistic, medical and other sources to public, private, and academic channels. These secondary data sources can complement, replace, reshape, or enhance your research goals and approach.