Introduction

Data warehouse is a repository which is often used to collect various amounts of data in it so that they can be used efficiently. The storage locations may be logical or physical. The main operations of a data warehouse include collecting information from various sources and collecting them.

A data warehouse can be used to increase the performance of the database applications. This is mainly done by the implementation of the Columnstore index. This implies the storage of the entire database entities in a single column. This is mainly done by storing each of the entities of a column as segments and then storing them as a separate BLOB.
The major reasons for the implementation of the columnstore index are the increased performance of the database applications and efficiency in updating the entities of the database. In addition, the presence of high compressed data using the VertiPaq algorithm for compressions reduces the input and output space requirements of the database. Moreover, the efficiency in updating the name of the entities is another advantage for adopting this process which reduces the need for relying upon the prebuilt aggregates to make it possible for batch processing.

References:

Cuzzocrea, A. (2013, July). Analytics over big data: Exploring the convergence of datawarehousing, OLAP and data-intensive cloud infrastructures. In Computer Software and Applications Conference (COMPSAC), 2013 IEEE 37th Annual (pp. 481-483). IEEE.

Cuzzocrea, A., Bellatreche, L., & Song, I. Y. (2013, October). Data warehousing and OLAP over big data: current challenges and future research directions. In Proceedings of the sixteenth international workshop on Data warehousing and OLAP (pp. 67-70). ACM.