ITMD 526 - Week 2 -Blog

Online Analytical Processing (OLAP) Introduction

Online Analytical Processing (OLAP) is computer processing that empowers a client to effortlessly and specifically extricate and see information from various perspectives. The OLAP term originates from customary data warehousing from times when "big data" would fit into your present portable workstation and it was tedious to prepare even that little sum contrasted with today's principles. OLAP permits clients to dissect database data from numerous database frameworks at one time. OLAP data is stored in multidimensional databases.

OLAP composes actualities into measurements which are ways that the truths can be separated. For example, total sales may have the capacity to be separated by geology. So also, total sales may likewise be separated by time. Measurements are additionally progressive systems of levels. For example, a geography measurement may contain the levels of nation, state, and area. Also, a period measurement may be separated by year, month, and day.

OLAP processing is often used for data mining. OLAP items are commonly intended for multiple‐user environments, with the cost of the software considering the quantity of clients.

The basic concepts of OLAP are:
  • ·        data cubes – multi-dimensional approach to data
  • ·        fast aggregation or pre-aggregation


An OLAP Cube is a data structure that allows fast analysis of data. The arrangements of data into solid shapes overcomes a constraint of social databases. It comprises of numeric truths called measures which are ordered by measurements. The OLAP cube comprises of numeric realities called measures which are ordered by measurements.

The different types of OLAP are:
  • -        Relational OLAP (ROLAP).
  • -        Multidimensional OLAP (MOLAP).
  • -        Hybrid OLAP (HOLAP).




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