What is meant by granular data?

Data granularity is a measure of the level of detail in a data structure. In time-series data, for example, the granularity of measurement might be based on intervals of years, months, weeks, days, or hours.

What is granularity of data example?

The granularity of data refers to the size in which data fields are sub-divided. For example, a postal address can be recorded, with coarse granularity, as a single field: address = 200 2nd Ave.

Why is granular data important?

Granular data is detailed data, divided into its lowest level. Granularity matters to marketers because it gives them the ability to distill huge chunks of marketing activity so that you can understand the smaller components.

What is a granular analysis?

highly detailed; having many small and distinct parts: data analysis on a granular level.

What is rough data?

Rough data is data with low resolution to reduce the amount of data and speed up processing.

What is metadata explain granular data?

Metadata is simply defined as data about data. The data that is used to represent other data is known as metadata. For example, the index of a book serves as a metadata for the contents in the book. In other words, we can say that metadata is the summarized data that leads us to detailed data.

What is low granularity data?

Granularity refers to “the level of detail or summarisation of the units of data in the data warehouse”. The low level of granularity contains high level of detail and the high level of granularity contains low level of detail. A diverse category of analytical processing uses various levels of granularity.

What is level of granularity?

Granularity refers to “the level of detail or summarisation of the units of data in the data warehouse”. The low level of granularity contains high level of detail and the high level of granularity contains low level of detail. The level of granularity affects database performances.

How do you calculate granularity?

When you identify the grain, you also decide on the level of detail you want to make available in the dimensional model. If more detail is included, the level of granularity is lower. If less detail is included, the level of granularity is higher. Identifying the level of detail.

What is granularity in statistics?

In a data warehouse, data granularity is the level of detail in a model or decision making process. It tells you how detailed your data is: Lower levels of detail equal finer, more detailed, data granularity (Ponniah, 2004; Bellahsène, 2008).

Which data is raw data?

Raw data (sometimes called source data, atomic data or primary data) is data that has not been processed for use. A distinction is sometimes made between data and information to the effect that information is the end product of data processing.

What is meant by “granularity of data”?

The granularity of data refers to the fineness with which data fields are sub-divided. For example, a postal address can be recorded, with low granularity, as a single field: Higher granularity has overheads for data input and storage.

What does ‘at a granular level’ mean?

(grăn′yə-lər) adj. 1. Composed or appearing to be composed of granules or grains: granular sugar; granular snow. 2. a. Having a high level of detail, as in a set of data: a more granular report that shows daily rather than weekly sales figures.

What does granular mean in business?

The level of detail considered in a model or decision making process. The greater the granularity, the deeper the level of detail. Granularity is usually used to characterize the scale or level of detail in a set of data.

What is another word for granular?

Synonyms for Granular: adj. •coarse (adjective) impure, rough-hewn, loose, lumpy, inferior, unpolished, unprocessed, coarse-grained, mediocre, grainy, harsh, unfinished, unpurified, homespun, poor quality, chapped, gritty, particulate, rough, rugged, crude.