What Are Measures in Power BI?

Measures are custom calculations you can create and add to Power BI visuals. They are dynamic and adjust on-the-fly when you filter or slice your data.

They can perform row-level calculations and are used in a relationship with tables to establish a data model. Use calculated columns when you need static values or when results need to be pre-calculated on dataset refresh.

Definition

A measure is any quantity used to quantify an attribute. The process of measurement involves reducing uncertainty in a given data value and is considered to be a scientific process.

A measurement can be in the form of a ratio. Examples include weight, height and distance. Ratio variables can be added, subtracted, divided and multiplied. When a number can be divided by other numbers without a remainder, it is said to have a common measure, and a fraction having this property is called a measured fraction.

The term can also refer to a specific type of instrument, such as a ruler or tape-measure. Lastly, a measure can be the amount of liquid or other substance contained in a particular container. The term can also be used to describe a plan of action or policy. For example, he took measures to prevent crime. He also took steps to improve security at the bank. When someone says they’ve taken a lot of measures, they mean that they’ve done a lot to try and fix the problem.

Purpose

The purpose of measurement is to capture a quantity and express it in a standardized way. This allows the comparison of results from different sources and across time. In practice, this requires a high degree of strategic thinking about what you are trying to measure and how it will be used.

The concept of measure extends beyond geometrical measures (length, area and volume) to encompass a variety of quantitative concepts. It forms a key aspect of probability theory and integration theory, and can be generalized to incorporate negative values, such as electrical charge.

In Power BI Desktop, you can organize your measure fields into display folders by creating a special table that contains only those measures. This makes it easier to find them in the Fields list. Unlike calculated columns, measures provide static values that do not change as the filter context changes. Rather, they pre-calculate their value on dataset refresh. This makes them suitable for use in a wide range of scenarios.

Examples

A measure can be a single value, such as miles traveled or the number of employees. It can also be a ratio, such as total revenues divided by total costs. For example, exports as a percentage of revenue are one way to measure a company’s competitiveness in the global economy.

The concept of a measure is an important foundation of mathematics and the sciences. It is the basis of many mathematical theories, such as probability theory and integration theory. In physics, it is also used in the theory of relativity and quantum physics.

In Power BI Desktop, you can create measures using the Data Analysis Expressions (DAX) formula language to perform custom calculations for visualizations and reports. Unlike calculated columns, which are static values added to tables, measures are dynamic and adjust instantly based on user actions like filtering or slicing. This allows you to reuse the same measure across multiple visuals and report pages.

Limitations

Although human nature often drives us to hide flaws, attempting to conceal them within research erodes credibility. Instead, identifying and addressing limitations throughout a study allows researchers to strengthen arguments and curtail peer censure that may be based on overlooked mistakes.

For example, the pell-mell drive to formula shaped coupling of performance measures and Federal science funding objectives is fraught with a host of potential limitations such as: the reduction in assessment of complex, circuitously generated outcomes to single or artificially aggregated measures; the creation of spurious correlations among seemingly independent facets of research performance; and the distortion of incentive systems for scientists and agency personnel.

These and many other limitations can be largely mitigated by careful consideration of the underlying research design, implementation, and analysis. Limitations should be emphasized in a paper’s discussion section so that readers understand their impact on conclusions and interpretations. This should be done in a way that demonstrates an understanding of and responsibility for the limitations associated with a research study without diminishing its value as a whole.

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