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  2. Snowflake schema - Wikipedia

    en.wikipedia.org/wiki/Snowflake_schema

    The snowflake schema is in the same family as the star schema logical model. In fact, the star schema is considered a special case of the snowflake schema. The snowflake schema provides some advantages over the star schema in certain situations, including: Some OLAP multidimensional database modeling tools are optimized for snowflake schemas. [3]

  3. Determining the number of clusters in a data set - Wikipedia

    en.wikipedia.org/wiki/Determining_the_number_of...

    The average silhouette of the data is another useful criterion for assessing the natural number of clusters. The silhouette of a data instance is a measure of how closely it is matched to data within its cluster and how loosely it is matched to data of the neighboring cluster, i.e., the cluster whose average distance from the datum is lowest. [8]

  4. Key clustering - Wikipedia

    en.wikipedia.org/wiki/Key_clustering

    Key or hash function should avoid clustering, the mapping of two or more keys to consecutive slots. Such clustering may cause the lookup cost to skyrocket, even if the load factor is low and collisions are infrequent. The popular multiplicative hash [1] is claimed to have particularly poor clustering behaviour. [2]

  5. Snowflake Inc. - Wikipedia

    en.wikipedia.org/wiki/Snowflake_Inc.

    Snowflake Inc. is an American cloud-based data storage company. Headquartered in Bozeman, Montana , it operates a platform that allows for data analysis and simultaneous access of data sets with minimal latency . [ 1 ]

  6. Database index - Wikipedia

    en.wikipedia.org/wiki/Database_index

    This may improve the joins of these tables on the cluster key, since the matching records are stored together and less I/O is required to locate them. [2] The cluster configuration defines the data layout in the tables that are parts of the cluster. A cluster can be keyed with a B-tree index or a hash table. The data block where the table ...

  7. Automatic clustering algorithms - Wikipedia

    en.wikipedia.org/wiki/Automatic_Clustering...

    BIRCH (balanced iterative reducing and clustering using hierarchies) is an algorithm used to perform connectivity-based clustering for large data-sets. [7] It is regarded as one of the fastest clustering algorithms, but it is limited because it requires the number of clusters as an input.

  8. Clustering high-dimensional data - Wikipedia

    en.wikipedia.org/wiki/Clustering_high...

    Clustering high-dimensional data is the cluster analysis of data with anywhere from a few dozen to many thousands of dimensions.Such high-dimensional spaces of data are often encountered in areas such as medicine, where DNA microarray technology can produce many measurements at once, and the clustering of text documents, where, if a word-frequency vector is used, the number of dimensions ...

  9. Clustering - Wikipedia

    en.wikipedia.org/wiki/Clustering

    Data cluster, an allocation of contiguous storage in databases and file systems; Cluster analysis, the statistical task of grouping a set of objects in such a way that objects in the same group are placed closer together (such as the k-means clustering) In hash tables, the mapping of keys to nearby slots; In economics: