Data collection involves gathering responses from a targeted population via an online survey, for the purpose of later analyzing this data to create actionable insights for your company’s success.

If you need to create and distribute an online survey, we will build a survey customized to your specific needs which will inform your business decisions. Our analysts are adept at creating surveys in Qualtrics XM, REDCap, Microsoft Forms, and Google Surveys, for business, public policy, and academic contexts.

Data wrangling involves cleaning, editing and/or reformatting raw data which has been gathered from one or more sources.

If you already have raw data you wish to turn into actionable insights, but it’s in need of professional care, look no further! Our analysts have over 11 years’ experience utilizing R, STATA, SAS, SPSS, Tableau, and Python, to clean, reformat, and merge multi-source datasets so that analyses can be conducted.

Data analytics involves creating visualizations and/or conducting statistical tests on numerical data. We help businesses create visualizations of data descriptives and analyses, and compute various types of statistical tests. By leveraging our knowledge of data visualization and statistics, business owners can efficiently identify and address areas for improvement in their company’s procedures.

​

We tailor the dashboards and/or statistical tests to your unique programmatic and funder's requirements, providing results that are reliable and pertinent to your specific context. In most circumstances, we can adapt to your software needs: our analysts are experienced in R, STATA, SAS, SPSS, Tableau, and Python (Please note that certain types of advanced statistical tests cannot be computed in SPSS). The exact types of statistical tests needed will be contingent upon each client’s unique needs; however, statistical tests with which we have over a decade of experience include, but are not limited to:

​

• ANOVA and MANOVA

• Confirmatory factor analysis (CFA)

• Correlations

• Odds ratios

• Regression (Curvilinear, linear and log)

• Structural equation modeling (SEM)

• Time series data modeling

• t-tests (Including affect size tests, Cohen’s d and Glass’ delta)