Building XML data warehouse based on frequent patterns in user queries

[Abstract]: With the proliferation of XML-based data sources available across the Internet, it is increasingly important to provide users with a data warehouse of XML data sources to facilitate decision-making processes. Due to the extremely large amount of XML data available on web, unguided warehousing of XML data turns out to be highly costly and usually cannot well accommodate the users’ needs in XML data acquirement. In this paper, we propose an approach to materialize XML data warehouses based on frequent query patterns discovered from historical queries issued by users. The schemas of integrated XML documents in the warehouse are built using these frequent query patterns represented as Frequent Query Pattern Trees (FreqQPTs). Using hierarchical clustering technique, the integration approach in the data warehouse is flexible with respect to obtaining and maintaining XML documents. Experiments show that the overall processing of the same queries issued against the global schema become much efficient by using the XML data warehouse built than by directly searching the multiple data sources

Building a Data Warehouse step by step

Data warehouses have been developed to answer the increasing demands of quality information required by the top managers and economic analysts of organizations. Their importance in now a day business area is unanimous recognized, being the foundation for developing business intelligence systems. Data warehouses offer support for decision-making process, allowing complex analyses which cannot be properly achieved from operational systems. This paper presents the ways in which a data warehouse may be developed and the stages of building it.data warehouse, data mart, data integration, database management system, OLAP, data mining

Code generator for integrating warehouse XML data sources.

XML---the extensible Markup Language, has been recognized as the standard for data representation and exchange on the world wide web. Vast amounts of XML data are available on the web. Since the information on the web is stored on separate web pages, it is very hard to combine pieces of information for decision support purposes. Data warehouse data integration provides a solution for integrating the different XML source data into a unique format with meaningful information for decision support systems. A data warehouse is a large integrated database organized around major subjects of an enterprise for the purpose of decision support querying. Many enterprises are creating their own data warehouse systems from scratch in different varying formats, making the issue of building a more efficient, more reliable, cost-effective and easy-to-use data warehouse system important. Building a code generator for creating a program that automatically integrates XML data sources into a target data warehouse is one solution. There is little research showing the use of the newest XML techniques in code generator for data warehouse XML data integration. This thesis proposes a Warehouse Integrator code generator for XML (WIG4X), which integrates XML data sources into a target data warehouse by first generating Java programs for data extracting, cleaning and loading XML data into the data warehouse. WIG4X system also generates the programs for creating XML views from the data warehouse. XML schema mapping strategy is employed for structural integration of each XML data source to data warehouse using a first order logic-like-language similar to that used in INFOMASTER. The content integration is handled through XML data extraction, conversion constraints, data cleaning and data loading. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2001 .L57. Source: Masters Abstracts International, Volume: 40-06, page: 1549. Adviser: Christie Ezeife. Thesis (M.Sc.)--University of Windsor (Canada), 2002

A Survey on Data Integration in Data Warehouse

Data warehousing embraces technology of integrating data from multiple distributed data sources and using that at an in annotated and aggregated form to support business decision-making and enterprise management. Although many techniques have been revisited or newly  developed in the context of data warehouses, such as view maintenance and OLAP, little attention has been paid to data mining techniques for supporting the most important and costly tasks of data integration for data warehouse design

DESIGN OF AN INTEGRATED AGRARIAN DATA DIMENSIONAL DATA WAREHOUSE

The concept of the Data warehouse was developed to provide a single access point to data from a variety of sources. There isa need to have a single location for the storage and sharing of data that users can easily utilize to make effective and qualitybusiness decisions, rather than trying to traverse the multiple data sources that exist today. Although many frameworks havebeen developed to integrate these sources into a single database, a reliable framework has yet to be developed. A majorhindrance to achieving a reliable warehouse is the poor quality of data obtained from the data transformation stage in theextract, transfer and load process. This poor quality of data contributes to inaccurate and unreliable results and if this data isused for decision making, unforeseen critical business errors can occur. This work reviews the data integration andtransformation process in dimensional data warehouses and proposes a dual structure for data integration and metadata ofmulti-formatted data used for the design of dimensional data warehouse using Agrarian data collected from Ondo State,Nigeria as a case study.Keywords: Data Warehouse, Data Integration, Metadata, Agrarian data