What are the efficient methods for data cube computation ?

-

 DATA CUBE COMPUTATION METHODS

Data cube computation is an essential task in data warehouse implementation. The pre-computation of all or part of a data cube can greatly reduce the response time and enhance the performance of OLAP, However, such computation is challenging because it may require substantial computation time and storage space. This section explores efficient methods for data cube computation which are as follows:

1. The multi-way array aggregation (Multi-Way) method for computing full cubes.

z. A method is known as BUC, which computes iceberg cubes from the apex cuboid downward.

3. TI,e Star-Cubmg method, which integrates top-down and bottom-up computation.

4. High dimension OLAP

Comments

Post a Comment

Popular posts from this blog

Explain E-Governance Project life cycle.

-
Image
E-Governance Project Lifecycle The diagram below presents an overview of the Lifecycle of an e-Governance project followed by a list of key activities performed at the phase of the Lifecycle. The diagram below lists the key activities performed at various phases of the e-Governance project Lifecycle. E-Governance detailed key activities and deliverables are given:-   Phase 1: e-Governance Strategy Development The table below lists key activities performed in e-Governance Strategy Development phase and illustrative deliverables. Key Activities   • Needs Assessment • Define clear vision & objectives • Prioritization of services and projects • Incorporate domestic and global learning’s • Identify institutional structures & capacities for implementation • Define funding requirements • Define monitoring and evaluation approach… Deliverable • e-Governance vision • e-Governance Objectives • e-Governance Strategy Phase 2: Current State Assessment The key activities performed i...
Read more

Explain the architecture of data mining system with block diagram./Describe the Data Mining Architecture with figure.

-
Image
Data Mining Architecture The process of extracting information to identify patterns, trends, and useful data that would allow the business to take the data-driven decision from huge sets of data is called Data Mining. The data mining process involves several components, and these components constitute a data mining system architecture. The significant components of data mining systems are a data source, data mining engine, data warehouse server, the pattern evaluation module, graphical user interface, and knowledge base. The major component of a data mining system architecture is as follows:- Database, Data Warehouse, or Other Information Repository:  This is one or a set of databases, data warehouses, spreadsheets, or other kinds of information repositories. Data cleaning and data integration techniques may be performed on the data. Database or Data Warehouse Server: It fetches the data as per the users’ requirement which one needs for data mining task. Knowledge Base:  ...
Read more

Explain CORBA architecture briefly.

-
Image
  ARCHITECTURE OF CORBA The major components that make up the CORBA architecture include the: Interface Definition Language (IDL), Object Request Broker (ORB), The Portable Object Adaptor (POA), Naming Service, and Inter-ORB Protocol (IIOP). Interface Definition languages: CORBA uses the concept of an interface Definition language to implement the services. IDL is a neutral programming language method of defining how a service is implemented. The syntax of this language is independent of any programming language. IDL is used to define an interface, which describes the methods that are available and the parameters that are required when a call is made for a remote object. Object Request Broker (ORB): The foundation of CORBA architecture is based on the Object Request Broker (ORB). The ORB is prime mechanism that acts as a middleware between the client and the server. It provides a heterogeneous environment in which a client can remotely communicate with the server irrespective of t...
Read more