Data seldom create value by themselves. They need to be linked and combined from multiple sources, which can often come with variable data quality. The task of improving data quality is a recurring challenge. In this paper, we use a case study of a large telecom company to develop a generic process pattern model for improving data quality. The process pattern model is defined as a proven series of activities, aimed at improving the data quality given a certain context, a particular objective, and a specific set of initial conditions. Four different patterns are derived to deal with the variations in data quality of datasets. Instead of having to find the way to improve the quality of big data for each situation, the process model provides data users with generic patterns, which can be used as a reference model to improve big data quality.
Abstract-Big data has been acknowledged for its enormous potential. In contrast to the potential, in a recent survey more than half of financial service organizations reported that big data has not delivered the expected value. One of the main reasons for this is related to data quality. The objective of this research is to identify the antecedents of big data quality in financial institutions. This will help to understand how data quality from big data analysis can be improved. For this, a literature review was performed and data was collected using three case studies, followed by content analysis. The overall findings indicate that there are no fundamentally new data quality issues in big data projects. Nevertheless, the complexity of the issues is higher, which makes it harder to assess and attain data quality in big data projects compared to the traditional projects. Ten antecedents of big data quality were identified encompassing data, technology, people, process and procedure, organization, and external aspects.
3_45 Important note To cite this publication, please use the final published version (if applicable). Please check the document version above.
Organizations are looking for ways to gain advantage of big and open linked data (BOLD) by employing statistics, however, how these benefits can be created is often unclear. A reference architecture (RA) can capitalize experiences and facilitate the gaining of the benefits, but might encounter challenges when trying to gain the benefits of BOLD. The objective of the research to evaluate the benefits and challenges of building IT systems using a RA. We do this by investigating cases of the utilization of a RA for Linked Open Statistical Data (LOSD). Benefits of using the reference architecture include reducing project complexity, avoiding having to "reinvent the wheel", easing the analysis of a (complex) system, preserving knowledge (e.g. proven concepts and practices), mitigating multiple risks by reusing proven building blocks, and providing users a common understanding. Challenges encountered include the need for communication and learning the ins and outs of the RA, missing features, inflexibility to add new instances as well as integrating the RA with existing implementations, and the need for support for the RA from other stakeholders.
Pada Program Kemitraan Masyarakat (PKM) ini, mitra kami adalah UKM Batik Tulis Amri Jaya (M. Zainal Arif) dan UKM Batik Tulis Namiroh (Ratna Tuty Mufida), yang merupakan salah satu sentra industri seni dan kerajinan dari Kampoeng Batik Jetis, Desa Sidoklumpuk, Kelurahan Lemah Putro Kecamatan Sidoarjo Kabupaten Sidoarjo. Berdasarkan hasil pengamatan dan wawancara, ternyata kedua mitra memiliki masalah yang sama, yaitu; 1). Tidak ergonomisnya beberapa peralatan yang digunakan dalam proses membatik, 2). Masih sederhananya manajemen administrasi produk harian, 3). Belum memiliki katalog produk, 4). Penjualan yang masih konvensional dan 5). Belum optimalnya pengawasan hasil produksi. Berikut ini solusi yang ditawarkan antara lain: 1) Penerapan konsep ergonomi untuk melakukan inovasi pada beberapa peralatan membatik (Meja Pengeblat Pola, Kursi Pembatik, Modifikasi Kompor LPG dan Saringan Lilin), 2. Melaksanakan pelatihan dan pendampingan, 3). Membuat katalog produk berciri khas Kampoeng Jetis serta 4). Pemasaran secara online. Dari permasalahan dan solusi yang ditawarkan tersebut, maka pendekatan yang akan diterapkan adalah membentuk program kerja sama berkelanjutan agar tercipta suasana kekeluargaan dan pemahaman terhadap masalah yang dialami mitra adalah masalah yang harus diselesaikan bersama sesuai tingkatan tanggung jawabnya. Setelah berlangsungnya kegiatan, tim PKM berharap semua pihak dapat memperoleh manfaat yang diharapkan, berupa peningkatan: 1). Produktivitas setelah diterapkannya inovasi beberapa peralatan membatik, 2). Manajemen usahaagar efektif, efisien dan kompetitif, 3). Pengetahuan dan wawasan pembatik, 4). Omzet penjualan, dan 5). Daya saing sehingga tercapai kemandirian pengrajin dan kesejahteraan bagi masyarakat sekitar
Organizations become more data-intensive and companies try to reap the benefits from this. Although there is a large amount of data available, this data has often different qualities which hinders use. Creating value from big data requires dealing with the variations in quality. Depending on their quality, data need to be processed in various ways to prepare this data for use. Although the processes vary, dealing with certain levels of data quality is a recurring challenge for many organizations. By developing generic process patterns organizations can reuse each other solutions. In this paper, process patterns for dealing with various levels of data quality are derived based on a case study of a large telecom company that employs all kinds of data to create operational value. The process patterns can possibly be used by other organizations.
Abstract Bridge inspection aims to determine the condition of the bridge, so that the bridge manager can determine the appropriate action. Bridge inspection using the INVI-J application makes it easy to implement and store data, but requires a quality assurance and quality control. In this study, data from questionnaires and interviews were used to complete the quality assurance and quality control of bridge inspections with the INVI-J application in the regions of Central Java and the Special Region of Yogyakarta. The results of the evaluation of the audit report data showed 95% for completeness of the data, 33% for the suitability of the documentation, and 78% for the suitability of the examination results. Evaluation of the field inspection gives a conformity value of 47% at level 1 and 40% at level 2. Evaluation of the inspection report data provides a higher level of conformity than the evaluation of independent inspection data. Keywords: bridge inspection; INVI-J application; quality assurance; quality control. Abstrak Pemeriksaan jembatan bertujuan untuk mengetahui kondisi jembatan, sehingga pengelola jembatan dapat menentukan tindakan yang tepat. Pemeriksaan jembatan menggunakan aplikasi INVI-J memudahkan pelaksanaan dan penyimpanan data, tetapi memerlukan suatu Quality assurance dan quality control. Pada studi ini, data hasil kuesioner dan wawancara digunakan untuk melengkapi quality assurance dan quality control pemeriksaan jembatan dengan aplikasi INVI-J di wilayah-wilayah Jawa Tengah dan Daerah Istimewa Yogyakarta. Hasil evaluasi terhadap data laporan pemeriksaan menunjukkan capaian 95% untuk kelengkapan data, 33% untuk kesesuaian dokumentasi, dan 78% untuk kesesuaian hasil pemeriksaan. Evaluasi terhadap pemeriksaan lapangan memberikan nilai kesesuaian 47 % pada level 1 dan 40% pada level 2. Evaluasi terhadap data inspection report memberikan tingkat kesesuaian yang lebih tinggi dibandingkan dengan evaluasi terhadap data independent inspection. Kata-kata kunci: pemeriksaan jembatan; aplikasi INVI-J; quality assurance; quality control.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.