Data Science

Data science is a multidisciplinary approach to extracting knowledge and meaning from large volumes of data.

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Data Science

Data science is a multidisciplinary approach to extracting knowledge and meaning from large volumes of data. Data scientists cleanse, aggregate, and manipulate data to perform advanced analysis. Data scientists use the scientific method, math and statistics, and computational models in their analysis to reveal patterns and actionable insights buried in the data. More often than not, data scientists will visualize their findings so that stakeholders can use results from the in-depth analysis to make informed decisions.

Machine Learning

Machine learning (ML) is a type of artificial intelligence (AI) that comes in handy when you need to predict something rather than measure something as you would with typical data analysis. Machine learning algorithms use historical data as input to predict new output values. A 9b example of ML would be helping an organization predict where its services would be most effective in a particular geographical area.

Statistical Analysis

A component of data analysis, statistical analysis is the process of collecting and interpreting quantitative data in order to uncover patterns and trends. 9b uses statistical analysis to help organizations better understand social issues, conditions, or questions related to the communities they serve. Statistical analysis involves researching, modeling, and designing surveys and studies.


Python is 9b’s programming language of choice for our data science projects because it can handle everything that goes into the multidisciplinary approach: common scientific computing, visualizations, sharing code, machine learning, and many more tools. All of that is to say: Any organization can benefit from data science and we have the proficiency in Python to make it possible.

What does it do for me?

Purpose-driven organizations are taking on complicated, often systemic issues in order to effect change in their communities. The data surrounding these issues can be just as messy. Data science goes beyond data analytics to provide a level of clarity and depth required to make sense and take action.

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