To slice means to cut and to dice means to cut into very small uniform sections and the two actions are often performed sequentially. For example, a chef may first cut an onion into slices and then cut the slices up into dices.
What is the meaning of Slice and dice?
Definition: Slicing and Dicing Slicing and Dicing refers to a way of segmenting, viewing and comprehending data in a database. Large blocks of data is cut into smaller segments and the process is repeated until the correct level of detail is achieved for proper analysis. Likewise, is slice and dice an idiom? phrase.
What is slice and dice in OLAP?
What is slice and dice in OLAP? To slice and dice is to break a body of information down into smaller parts or to examine it from different viewpoints so that you can understand it better. In data analysis, the term generally implies a systematic reduction of a body of data into smaller parts or views that will yield more information.
How do you use slice in a sentence?
noun. a thin, flat portion of anything cut from it: a hunk of bread A slice of land is a segment, piece, or share of land. In Excel, how do I slice and split data? Two states have been selected to appear in this page filter for State. Then there’s Slicers. After that, choose the field you want to connect to the Slicer and click OK.
What is an example of slicing and dicing?
To slice and dice is to break a body of information down into smaller parts or to examine it from different viewpoints so that you can understand it better. For example, a chef may first cut an onion into slices and then cut the slices up into dices. Click to see full answer. Also know, what do you mean by slicing and dicing?
What mean slice and dice?
Definition of slice and dice chiefly US. : to divide something into many small parts especially to use the result for one's own purposes You can slice and dice the data any way you want.
What is slice and dice in data warehousing?
The main difference between slice and dice in data warehouse is that the slice is an operation that selects one specific dimension from a given data cube and provides a new subcube while the dice is an operation that selects two or more dimensions from a given data cube and provides a new subcube.
What is slice and dice in data analysis?
In data analysis, the term slice and dice generally implies a systematic method of reducing a complete set of data into smaller parts or views that will help to yield more information.
What is slice and dice in Cognos?
What Is Slicing And Dicing In Cognos? Data warehouse slice and dice are two different operations. Slices are operations that select one specific dimension from a given data cube and provide a new subcube, while dice are operations that select two or more dimensions from a given data cube and provide a new subcube.
What is data slice?
A data slice is a logical representation of the data that is saved in the partitions of a disk. The data slice contains pieces of each user database and table. The IBM® Netezza® system distributes the user data to all of the disks in the system by using a hashing algorithm.
What is dice operation?
Dice is a dimensional data operation that performs a slice on more than two dimensions of a data cube (or more than two consecutive slices). Dicing involves providing values for every dimension to locate a single value for a cube.
What is slicing and dicing in software testing?
Slicing or program slicing is a technique used in software testing which takes a slice or a group of program statements in the program for testing particular test conditions or cases that may affect a value at a particular point of interest.
What is slicing and dicing in STM?
Slicing and Dicing refers to a way of segmenting, viewing and comprehending data in a database. Large blocks of data is cut into smaller segments and the process is repeated until the correct level of detail is achieved for proper analysis.
What is a slice analysis?
The Slice Analysis panel lets you compute a range of measurements — including maximum, minimum, mean, and median values, as well as the variance and standard deviation — for each slice within an image stack and for the dataset as a whole.