It is not possible to be sure of the answer because the questioner has mentioned the following without there being anything that actually followed. However, based on experience, I would guess that the answer is the mean.
analyzing data
Granularity refers to the level of detail or summarization in the units of in the data warehouse (Inmon, WH 2002). For example, one of the dimension might be a date/time dimension which could be at the year, month, quarter, period, week, day, hour, minute, second, hundredths of seconds level of granularity. High granularity means that the data is at or near the transaction level, which has more detail. Low granularity means that the data is aggregated, which has less detail.
The sum of a set of data divided by the number of pieces of data is the average or mean.
5
data warehouse A data warehouse is the main repository of an organization's historical data, its corporate memory. It contains the raw material for management's decision support system. The critical factor leading to the use of a data warehouse is that a data analyst can perform complex queries and analysis, such as data mining, on the information without slowing down the operational systems. data mining The development of computational algorithms for the identification or extraction of structure from data. This is done in order to help reduce, model, understand, or analyze the data. Tasks supported by data mining include prediction, segmentation, dependency modeling, summarization, and change and deviation detection. Database systems have brought digital data capture and storage to the mainstream of data processing, leading to the creation of large data warehouses.
documentation
To convert data into information, you must perform some summarization, analysis, and interpretation. Data doesn't allow one to make decisions or inferences, but information does.
The mean and sode of a single number is the number itself.
A raw data graphic is a visual representation of unprocessed, unanalyzed data. It typically shows the individual values or observations without any summarization or manipulation. This type of graphic is useful for initially exploring and understanding the data before further analysis.
FILE, struct stat and struct tm are some examples.
The mean of a single number, such as 0892909492 is itself.
There are no "following" data!
The following will return true if the number provided is even: boolean isEven(int number) { return number % 2 == 0; } Repeat for other integral data types (such as long), and you have method overloading.The following will return true if the number provided is even: boolean isEven(int number) { return number % 2 == 0; } Repeat for other integral data types (such as long), and you have method overloading.The following will return true if the number provided is even: boolean isEven(int number) { return number % 2 == 0; } Repeat for other integral data types (such as long), and you have method overloading.The following will return true if the number provided is even: boolean isEven(int number) { return number % 2 == 0; } Repeat for other integral data types (such as long), and you have method overloading.
The following is not a registry data type: String Array.
DBMS can be classified in the following ways,1. Based on Data ModelRelational Data ModelObject Data ModelObject Relational Data ModelExtended Relational Data ModelXML ModelHierarchical Data ModelNetwork data Model2. Based on Number of UsersSingle User SystemMulti-User System3. Based on Number of SitesCenteralized systemsDistributed DBMSs(DDMSs)Homogeneous DDMSHetrogeneous DDMS
The standard deviation of a single number, as in this question, is 0.
Name of the school