An ETL Metadata Model for Data Warehousing

Metadata is essential for understanding information stored in data warehouses. It helps increase levels of adoption and usage of data warehouse data by knowledge workers and decision makers. A metadata model is important to the implementation of a data warehouse; the lack of a metadata model can lead to quality concerns about the data warehouse. A highly successful data warehouse implementation depends on consistent metadata. This article proposes adoption of an ETL (extracttransform-load) metadata model for the data warehouse that makes subject area refreshes metadata-driven, loads observation timestamps and other useful parameters, and minimizes consumption of database systems resources. The ETL metadata model provides developers with a set of ETL development tools and delivers a user-friendly batch cycle refresh monitoring tool for the production support team

Classification of Metadata Categories in Data Warehousing - A Generic Approach

Using appropriate metadata is a central success factor for (re)engineering and using data warehouse systems effectively and efficiently. The approach presented in this paper aims to reduce the effort in developing and operating data warehouse systems and thus to increase the ability and acceptance of a data warehouse. To achieve these objectives identifying the appropriate metadata is an important task. To avoid processing the “wrong” object data and thus compromising the acceptance of a data warehouse system, a systematic approach to categorize and to identify the appropriate metadata is essential. This paper presents such a generic approach. After investing and structuring problem situations, that can occur in data warehousing, metadata categories are identified to solve a given problem situation. A use case illustrates the approach

SISTEM DATA WAREHOUSE PADA RUMAH SAKIT HUSADA

SISTEM DATA WAREHOUSE PADA RUMAH SAKIT HUSADA - data warehouse, skema bintang, metadata, et

PERANCANGAN SISTEM METADATA UNTUK DATA WAREHOUSE DENGAN STUDI KASUS REVENUE TRACKING PADA PT. TELKOM DIVRE V JAWA TIMUR

Data warehouse merupakan media penyimpanan data dalam perusahaan yang diambil dari berbagai sistem dan dapat digunakan untuk berbagai keperluan seperti analisis dan pelaporan. Di PT Telkom Divre V Jawa Timur telah dibangun sebuah data warehouse yang disebut dengan Regional Database. Di Regional Database memerlukan sebuah komponen penting dalam data warehouse yaitu metadata. Definisi metadata secara sederhana adalah "data tentang data". Dalam penelitian ini dirancang sistem metadata dengan studi kasus Revenue Tracking sebagai komponen analisis dan pelaporan pada Regional Database. Metadata sangat perlu digunakan dalam pengelolaan dan memberikan informasi tentang data warehouse. Proses - proses di dalam data warehouse serta komponen - komponen yang berkaitan dengan data warehouse harus saling terintegrasi untuk mewujudkan karakteristik data warehouse yang subject-oriented, integrated, time-variant, dan non-volatile. Karena itu metadata juga harus memiliki kemampuan mempertukarkan informasi (exchange) antar komponen dalam data warehouse tersebut. Web service digunakan sebagai mekanisme pertukaran ini. Web service menggunakan teknologi XML dan protokol HTTP dalam berkomunikasi. Dengan web service, setiap komponen yang ada dalam data warehouse dapat bertukar informasi melalui metadata. Implementasi web service dalam sistem metadata menggunakan Framework Microsoft .NET. Dalam tugas akhir ini dilakukan ujicoba terhadap sistem metadata yang dibuat dengan membuat aplikasi yang memanfaatkan metadata. Dengan sistem metadata ini dapat dibentuk aplikasi sistem pendukung keputusan yaig lain seperti aplikasi OLAP dan sistem pengelolaan metadata. Kata kunci : data warehouse, metadata, exchange, web service, xm

Using Reference Models for Data Warehouse Metadata Management

Based on experience from applying the Common Warehouse Metamodel to metadata management at a large Swiss bank, the applicability of metadata reference models in complex application domains is analyzed. In order to explain the context of the case, the state-of-the-art of the Common Warehouse Metamodel and its application for data warehouse management are summarized. Based on the project experience documented in this paper, benefits of the reference model approach are described and recommendations for future developments of the Common Warehouse Metamodel are proposed

HANDLING DATA, METADATA AND DESIGN FOR GLOBAL DATA WAREHOUSE

Data ware house modeling is a complicat e d task, which involves knowled g e of business process, as well as familiarity with operatio n al information system structure and beha v ior. While it is universally recognized that a DW leans on multi dimensional model, there is suggested to contract a data ware house conce p tual model, My analysis of these methods indicate that they are limited in their applic a bility to model large scale systems, as they require acqu a intance with the business process and ability to s elect relevant transaction al eliminate the technic a l and reporting difficulties experienced with the classic star schemes and snow flake. The objective of Meta data strategy is to provide a blueprint that will enable efficient stronger , mainten a nce, and delivery of timely and accurate business and technic a l Meta data of the organiz a tion in buildi n g a ro b ust data warehouse environme n t ,meta data is considered to be a critical success factor .This work will address meta data requirement and a proposed solution for effective metadata mana g ement and deploy m ent /delivery at organiz a tion .The purpose of data quality method o logy is to validate the quality of specific business applic a tion includi n g the source of these business applic a tion and the process that feed the business applic a tion of the EDW environme n t applic a tion are worthless .Business applic a tion vend o rs have great produ c ts to sell ,offering simplified access to complex comput a tion models and enormo u s stores of corporate data, yet they often deliver below expectati o ns. This work will help to overcome t h is limitation

Executive Information System and Data Warehouse

Hal terpenting dalam suatu data warehouse adalah bahwa data warehouse tersebut dapat memuat semua informasi bisnis yang diperlukan oleh para penggunanya dengan akses yang cepat dan dapat diintegrasikan secara mudah dengan sistem yang lainnya. Sebelum merencanakan pembuatan suatu data warehouse, maka akan sangat diperlukan suatu konsep yang tepat dalam pembuatannya. Konsep tersebut akan memuat banyak hal, diantaranya adalah: operasionalisasi database, para pengguna, proses koneksinya, metadata, dan lain sebagainya. Adapun executive information system (EIS) sendiri adalah suatu sistem informasi yang berdasarkan pada penggunaan data warehouse sebagai landasan dasar untuk sistem informasi manajerialnya. EIS ini sendiri dalam prakteknya sangat membantu pihak manajemen tingkat atas dalam penganalisaan data melalui pengaksesan data warehouse

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