Data Science

Research Centre

Through interdisciplinary collaborations, we strive to correlate data science research initiatives and the gaining of new knowledge to create related methodologies, education, and research disciplines that integrate well with a transformative inquiry, an inquiry into current discourses on the means to devise sustainable criteria to advance human development in the global contact.

DATA SCIENCE DISCIPLINES Provides
Support for key consultancy operations

challenges for scientific disciplines
that harbor major societal importance

Our work supports research in a variety of fields where incredible advances are being made through the facilitation of meaningful collaborations between internal/external researchers, data analysts, and others with expertise in historical analysis, issues in sustainable development, and societal challenges that relate to future prognosis. We make use of those methods researchers have developed and deployed as next-generation computational tools and techniques. Still others with advanced capability are being explored.

data science service center

Data Science Teams

In general, our data science teams operates within a decentralized reporting structure where data scientists report to various functionaries and/or units within the organization as needed to benefit the total operational experience.

Collaborative Partnership

Our data science Collaborative Partnership connects data analysis with current and emerging science and research communities to foster transformative sustainable criteria to advance human development in a global context. The partnership’s two major goals are to build sustainable relationships to foster community development, and devise innovations that move humanity from a fractured society to solidify that based on sustainable achievements.

Global Human Development

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from noisy, structured and unstructured data, and apply knowledge and actionable insights from data across a broad range of application domains; specifically to advance human development in a global context.

Framing Human Species Identity

AI is a perfect example of prescriptive analytics. AI systems consume a large amount of data, as it must be in a constant mode of learning in order to use information to support informed decisions. Well-designed AI systems can communicate these decisions, even putting them into action, and used for our operations when beneficial. For example, analysis of the Global Reach Initiative and TeamMx field unit operations. The importance of Blockchain technology will be considered.

Descriptive Analysis
Descriptive Analysis. This provides data insight into situations and conditions, the simplest and most commonly used. It answers the “what happened” by summarizing past data. It is used to track Key Performance Indicators (KPIs), i.e., how we are performing based on chosen benchmarks.
Diagnostic Analysis
Diagnostic Analysis. Having asked the fundamental question “what happened”, diagnostic analysis goes deeper to ask “why did it happen?”. It takes the insights found from descriptive analytics and drills down to find the causes of those outcomes. This type of analytics establishes more connections between data and identifies patterns of behavior and creates detailed information.
Predictive Analysis
Predictive analysis attempts to answer the question “what is likely to happen”. This type of analytic uses previous data to make predictions about future outcomes. It is a step up from the descriptive and diagnostic analyses because predictive analysis uses the data already summarized to make logical predictions of the outcomes of events. This analysis relies on statistical modeling, which requires added technology and human resources to forecast. It is also important to understand that forecasting is only an estimate; the accuracy of predictions relies on quality and detailed data.
Prescriptive Analysis
It would seem that prescriptive analysis is the most sought after, but they equip few organizations to perform it. This is because prescriptive analysis is the frontier of data analysis, combining the insight from all previous analyses to determine the course of action and decision to be made about a current problem. It uses state-of-the-art technology and data practices, requiring a vast amount of effort and resources. This feature is for future use when the consultancy develops to a greater capacity.
Blockchain Technology

A blockchain is a distributed database that is shared among the nodes of a computer network. As a database, a blockchain stores information in digital format and is best known for maintaining a secure and decentralized record of transactions. Blockchain guarantees the fidelity and security of a record of data and generates trust with no trusted third party.

Of note, is that blockchain technology has been used to project future living conditions and habitats for humans. It shows possibilities for providing elements, or ways for achieving sustainable goals. To design sustainable communities, it would do much as a support feature for our Global Reach Initiative and its field unit operation.

Operations Research
Operations Research is an applied science that is involved with quantitative decision problems that relate to the allocation and control of limited resources. For our purpose, an operations research analyst would be a problem formulator and solver. This person would develop and use mathematical and statistical models to help solve agency decision problems. Their work would require creating a mathematical model of a system and the analysis and prediction of the consequences of alternate modes of operating the system. The analysis may involve mathematical optimization techniques, probabilistic and statistical methods, experiments, and computer simulations.
education research

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Stanwood Community
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global reach initiative
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