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Data Science

Research Center

challenging scientific disciplines of societal importance

The Data Science Research Center uses a variety of data science disciplines to provide quality reporting of research and analysis on the current status of operations and with suggestions for future performance.

Data Analysis

Analysis of data is a vital part of our consultancy’s working groups. Its effective use it can lead to a better understanding of our previous performance to provide support for vital understandings and decision-making in the future. As we progress in our work, there are four types of data analysis available to us:

Data Science

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.

Artificial Intelligence (AI)

AI is a perfect example of prescriptive analytics. AI systems consume a large amount of data, as it must be in a constant learn mode in order to use information to support informed decisions. Well-designed AI systems can communicate these decisions, even putting them decisions into action. We could use AT when our operations are at a point where it would be beneficial, for example, where analysis of Global Reach and TeamMx field operations are of such an extent that would warrant it. At some point, Blockchain technology may 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.
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.
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.

DATA SCIENCE DISCIPLINES Provides

Support for key agency operations

Creative Intelligence

Receives information from advisories, support systems, academic institutions, and other sources that include special studies, research, data analysis, field operations.

Secretariat

Consolidates data received from all sources to complete a detailed summary with analysis of agency operations. It becomes the Executive Data Analysis Report.

Advisory Collective

Key advisory to the Directorate on matters of major importance, the primary center for internal collaborative interchange, guides unit research, analysis, and advisory duties.

Global Reach Advisory Board

Provides data to DSRC for analysis, and receives end results for planning and problem solving; to include the Global Reach Initiative and TeamMx field ops.

Project Central

An extensive and intensive research project that will test the nature and purpose of those willing to volunteer their time, effort, and abilities to take part this service.
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Trilateral Research Assessment

A key research opportunity to gain insight into the trilateral approach to problem solving, and the possibilities it provides to help advance the human condition.

Sustainable Achievements Through Justice & Sacrificial Endeavours

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Data Science Research

Key Advisory on Agency Activities

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