MDDM(multidimensional data model) and OLAP server

Introduction

Online Analytical Processing Server (OLAP) is based on multidimensional data model. It allows the managers, analysts to get insight the information through fast, consistent, interactive access to information. In this chapter we will discuss about types of OLAP, operations on OLAP, Difference between OLAP and Statistical Databases and OLTP.

Types of OLAP Servers

We have four types of OLAP servers that are listed below.

• Relational OLAP(ROLAP)
• Multidimensional OLAP (MOLAP)
• Hybrid OLAP (HOLAP)
• Specialized SQL Servers

Relational OLAP (ROLAP)

The Relational OLAP servers are placed between relational back-end server and client front-end tools. To store and manage warehouse data the Relational OLAP use relational or extended-relational DBMS. ROLAP includes the following.

• Implementation of aggregation navigation logic.
• Optimization for each DBMS back end.
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• Additional tools and services.

Multidimensional OLAP (MOLAP)

Multidimensional OLAP (MOLAP) uses the array-based multidimensional storage engines for multidimensional views of data.With multidimensional data stores, the storage utilization may be low if the data set is sparse. Therefore many MOLAP Server uses the two level of data storage representation to handle dense and sparse data sets.

Hybrid OLAP (HOLAP)

The hybrid OLAP technique combination of ROLAP and MOLAP both. It has both the higher scalability of ROLAP and faster computation of MOLAP. HOLAP server allows storing the large data volumes of detail data. the aggregations are stored separated in MOLAP store.

Specialized SQL Servers

specialized SQL servers provides advanced query language and query processing support for SQL queries over star and snowflake schemas in a read-only environment.

OLAP Operations

As we know that the OLAP server is based on the multidimensional view of data hence we will discuss the OLAP operations in multidimensional data. Here is the list of OLAP operations.

Roll-up

• Drill-down
• Slice and dice
• Pivot (rotate)

ROLL-UP

This operation performs aggregation on a data cube in any of the following way:

By climbing up a concept hierarchy for a dimension

By dimension reduction.

Consider the following diagram showing the roll-up operation.

DRILL-DOWN

Drill-down operation is reverse of the roll-up. This operation is performed by either of the following way:

By stepping down a concept hierarchy for a dimension.

By introducing new dimension

SLICE

The slice operation performs selection of one dimension on a given cube and gives us a new sub cube. Consider the following diagram showing the slice operation.

PIVOT

The pivot operation is also known as rotation.It rotates the data axes in view in order to provide an alternative presentation of data.Consider the following diagram showing the pivot operation.