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What is a data mart?

04/13/2023 | By: FDS

A data mart is a part of a data warehousing system and refers to a specific subset of data relevant to a particular business unit or department within an organization. Unlike the comprehensive data warehouse, which contains all of the organization's data, a data mart is tailored to specific needs and requirements and contains only the data relevant to a particular group of users.

A data mart is typically smaller than a data warehouse and can be implemented more quickly and at a lower cost. It can also be more flexible because it is tailored to specific requirements, making it easier to customize. Data marts can also operate independently, allowing users to access the data that is relevant to them without having to search the entire data warehouse.

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What is actuarial science?

04/13/2023 | By: FDS

Actuarial mathematics is a branch of mathematics that deals with the application of mathematical methods and models to insurance and risk. The main goal of actuarial science is to quantify risks and develop insurance rates and products that are fair and profitable for customers and insurance companies.

An important aspect of actuarial science is loss analysis and forecasting. Here, mathematical models are used to calculate the probability of occurrence and the amount of losses. Based on this information, insurance companies can assess risks and calculate insurance premiums.

In addition, actuarial science deals with the modeling of insurance portfolios and the risk management of insurance companies. This involves the use of statistical methods and mathematical models to minimize the risk of losses and maximize the profitability of the insurance business.

Overall, actuarial science is concerned with the modeling of insurance portfolios and the risk management of insurance companies.

Overall, actuarial science is an important part of the insurance industry and helps ensure that insurance is fair and profitable for customers and companies alike.

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What is gender competence?

04/13/2023 | By: FDS

Gender competence refers to the ability to understand, promote, and implement gender equity in different contexts. It is about having an understanding of how gender roles and stereotypes operate in different areas such as education, the workplace, the family, and society, and how to remove these barriers and create a more inclusive and equitable environment.

Gender competence also includes understanding and being sensitive to the diversity of gender identities and sexual orientations that exist in our society, and being able to treat people with respect regardless of their gender. It is important that people working in educational, social, or counseling professions acquire gender competence in order to do more equitable and inclusive work and meet the needs of all people.

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What is diversity competence?

04/13/2023 | By: FDS

Diversity competence is the ability to deal effectively with diverse people and groups characterized by characteristics such as gender, age, culture, ethnicity, religion, sexual orientation, social status, or disabilities. It refers to the ability to recognize and appreciate differences and the ability to communicate and act in an inclusive and respectful manner.

A person with diversity competence is able to demonstrate empathy and understanding for others, shift perspectives, and understand cultural differences. He or she can deal with conflicts that may arise because of differences and has the ability to create an environment in which diversity is valued and utilized to achieve better results.

Diversity competency is important in many settings, such as businesses, educational institutions, government agencies, NGOs, and other organizations where people from different backgrounds work together. Through diversity competence, organizations can increase their effectiveness and create an inclusive work environment where everyone has the opportunity to reach their full potential.

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What is a forecast model?

04/13/2023 | By: FDS
A forecasting model is a statistical method or mathematical model based on historical data and trends to predict future events or developments. Such a model can be used to predict, for example, the demand for a product, the future value of a stock, or the outcome of an election or sporting event. Forecast models can be based on various techniques, such as time series analysis, regression analysis, artificial neural networks or decision tree methods. The quality of a forecasting model depends on how accurately it can represent past trends and developments and how well it is able to take into account unexpected events and changes that may affect future developments.
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