Designing business intelligence (BI) for production, distribution and customer services: a case study of a UAE-based organization

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammed T. Nuseir
Keyword(s):  
United Arab Emirates ◽  
Business Process ◽  
Business Intelligence ◽  
Data Retrieval ◽  
Online Analytical Processing ◽  
Content Type ◽  
Production Distribution ◽  
Analytical Processing ◽  
Business Needs ◽  
Customer Services

PurposeBusiness intelligence (BI) is a strategic approach that can use analytical tools to collect and integrate information, apply business rules and ensure the appropriate visible output of organizational information. This study aims to present the design and implementation of BI in areas of business process improvement for production, distribution and customer services.Design/methodology/approachThis study highlights the process of BI in the production, distribution and customer services based on the National Food Products Company (NFPC) in the United Arab Emirates (UAE). This study discusses the step-by-step development process of BI and refers to graphical illustrations of the business needs and the organization's target key performance indicators (KPI).FindingsBased on the business needs and chosen KPIs to maximize production and improve distribution and customer services the BI tool shows that the “star scheme” is the most appropriate one. Relational Online Analytical Processing (ROLAP) based on Mondrian system is employed as Online Analytical Processing (OLAP) architecture since the NFPC's technological infrastructure was better adapted to this vision. The analysis starts with data retrieval from two databases' customer' and production and distribution databases. Finally, visualization and reporting processes that respect the end-users improve the NFPC's decisions.Practical implicationsThe study will help other organizations, BI developers, data warehouses (DW) developers and administrators, project managers as well as academic researchers understand how to develop a successful BI framework and implement BI based on business needs.Originality/valueThis is a unique and original study on the BI experience from a UAE-based organization and will encourage other organizations to apply BI in their business process.

Data Mining in Franchise Organizations

2008 ◽  
pp. 2722-2733 ◽  
Author(s):  
Ye-Sho Chen ◽  
Robert Justis ◽  
P. Pete Chong
Keyword(s):  
Data Mining ◽  
Growth Strategy ◽  
Online Analytical Processing ◽  
Pertinent Data ◽  
Analytical Processing ◽  
Customer Services ◽  
Internal Operations ◽  
Comprehensive Framework ◽  
Franchise Organizations

Franchising has been used by businesses as a growth strategy. Based on the authors’ cumulative research and experience in the industry, this paper describes a comprehensive framework that describes both the franchise environment — from customer services to internal operations — and the pertinent data items in the system. The authors identify the most important aspects of a franchising business, the role of online analytical processing (OLAP) and data mining play and the data items that data mining should focus on to ensure its success.

scholarly journals Analisa In Depth Online Analytical Processing (OLAP) Business Intelligence (BI) dengan Filter Inheritance pada Distribusi Sosial di Kecamatan Setiabudi

2020 ◽  
Vol 5 (3) ◽  
pp. 300
Author(s):  
Alhadi Alhadi ◽  
Iskandar Fitri ◽  
Andrianingsih Andrianingsih
Keyword(s):  
Business Intelligence ◽  
Social Service ◽  
Census Data ◽  
Social Assistance ◽  
Online Analytical Processing ◽  
Government Agencies ◽  
Intelligence System ◽  
The Social ◽  
The Family ◽  
Analytical Processing

A lot of census data in the sub-district is very useful and helps the social service to provide social assistance in a sub-district. With this Business Intelligence system, it can help analyze information on providing social assistance with the help of using the Tableau Tools so that the information is more detailed and displays a graphic / dashboard visualization. This research is to analyze how certain people who receive social assistance for residents of Setiabudi sub-district, and each provision of social assistance will be collected from the sub-district and submitted to each sub-district to be able to data with certainty, using the number of data on the head of the family registered in Setiabudi District.Keywords:Business Intelligence, Tableau Tools, OLAP, Government Agencies.

H-SPOOL

2016 ◽  
Vol 12 (3) ◽  
pp. 359-378 ◽  
Author(s):  
Takahiro Komamizu ◽  
Toshiyuki Amagasa ◽  
Hiroyuki Kitagawa
Keyword(s):  
Linked Data ◽  
Design Methodology ◽  
Query Language ◽  
Numerical Data ◽  
Online Analytical Processing ◽  
Data Sets ◽  
Content Type ◽  
Related Information ◽  
Analytical Processing ◽  
The Web

Purpose Linked data (LD) has promoted publishing information, and links published information. There are increasing number of LD datasets containing numerical data such as statistics. For this reason, analyzing numerical facts on LD has attracted attentions from diverse domains. This paper aims to support analytical processing for LD data. Design/methodology/approach This paper proposes a framework called H-SPOOL which provides series of SPARQL (SPARQL Protocol and RDF Query Language) queries extracting objects and attributes from LD data sets, converts them into star/snowflake schemas and materializes relevant triples as fact and dimension tables for online analytical processing (OLAP). Findings The applicability of H-SPOOL is evaluated using exiting LD data sets on the Web, and H-SPOOL successfully processes the LD data sets to ETL (Extract, Transform, and Load) for OLAP. Besides, experiments show that H-SPOOL reduces the number of downloaded triples comparing with existing approach. Originality/value H-SPOOL is the first work for extracting OLAP-related information from SPARQL endpoints, and H-SPOOL drastically reduces the amount of downloaded triples.

scholarly journals ANALISIS VISUALISASI DAN PEMETAAN DATA TANAMAN PADI DI INDONESIA MENGGUNAKAN MICROSOFT POWER BI

2018 ◽  
Vol 4 (2) ◽  
pp. 156
Author(s):  
Ridho Darman
Keyword(s):  
Business Intelligence ◽  
Online Analytical Processing ◽  
Analytical Processing

Tanaman padi merupakan tanaman yang paling penting karena merupakan sumber makanan pokok masyarakat Indonesia. Pertumbuhan penduduk di Indonesia dan diikuti dengan tingkat produksi padi yang tidak merata tentu menjadi masalah serius bagi Indonesia dalam mencukupi kebutuhan pangan nasional. Informasi kebijakan pemerintah dalam pengembangan komoditas padi sangatlah penting karena komoditas ini memiliki peran penting dalam menjaga stabilitas kebutuhan pangan nasional. Badan Pusat Statistik adalah lembaga yang memiliki berbagai data sensus dan survei dalam ukuran yang sangat besar. Agar data tersebut dapat diolah menjadi informasi yang lebih bernilai dibutuhkan sebuah aplikasi business intelligence yang dapat memvisualisasikan data-data tersebut sehingga dapat menampilkan informasi daerah dengan produksi dan produktivitas padi yang tinggi maupun yang rendah. Pengelompokan data ini bertujuan untuk mempermudah pengguna dalam mendapatkan informasi mengenai produksi dan produktivitas tanaman padi di setiap daerah di Indonesia sehingga dapat menjadi acuan bagi Kementerian Pertanian dalam perumusan dan penetapan kebijakan di bidang penyediaan prasarana dan sarana pertanian, peningkatan produksi padi dan pertanian lainnya. Pada penelitian ini digunakan salah satu business intelligence software untuk dapat mengelompokkan data tanaman padi serta visualisasinya dalam bentuk informasi grafik dan peta kartogram area dengan metode Online Analytical Processing (OLAP).

scholarly journals Analisis Data Penjualan Perusahaan Detergen XYZ dengan Aplikasi Zoho Reporting Menggunakan Metode OLAP (Online Analytycal Processing)

2017 ◽  
Vol 3 (1) ◽  
pp. 71
Author(s):  
Ricky Akbar ◽  
Elsha Yuliani ◽  
Qisty Mawaddah ◽  
Fikri Ardhana
Keyword(s):  
Business Intelligence ◽  
Online Analytical Processing ◽  
Sales Channel ◽  
Analytical Processing

Sales Channel atau saluran penjualan merupakan salah satu hal yang harus diperhatikan oleh perusahaan. Sales channel yang beragam memungkin perusahaan untuk memperbesar keuntungan mereka, sales channel online misalnya dengan sales channel ini perusahaan dapat memperluas lokasi pemasaran keseluruh negara-negara di dunia. Perusahaan yang memiliki sales channel yang banyak dan memproduksi barang yang biasa digunakan sehari-hari, memiliki data pelanggan yang sangat besar diberbagai belahan dunia. Prediksi jumlah penjualan produk di masing-masing negara berdasarkan sales channel yang digunkan perusahaan merupakan Business Intelligence (BI) yang sangat penting untuk melihat negara mana yang berpotensi memberikan pelanggan yang besar untuk penjualan produk perusahaan. Dari penelitian dengan menggunakan metode OLAP (Online Analytical Processing) dan aplikasi Zoho Reporting, dapat membantu pihak pengambil keputusan dalam menemukan pelanggan dari negara mana yang nantinya berpotensi memberikan keuntungan besar bagi perusahaan. Kata kunci— business intelligence, online analytical processing, sales channel, prediksi.

Data Mining in Franchise Organizations

2011 ◽  
pp. 217-229 ◽  
Author(s):  
Ye-Sho Chen ◽  
Robert Justis ◽  
P. Pete Chong
Keyword(s):  
Data Mining ◽  
Growth Strategy ◽  
Online Analytical Processing ◽  
Pertinent Data ◽  
Analytical Processing ◽  
Customer Services ◽  
Internal Operations ◽  
Comprehensive Framework ◽  
Franchise Organizations

Franchising has been used by businesses as a growth strategy. Based on the authors’ cumulative research and experience in the industry, this paper describes a comprehensive framework that describes both the franchise environment — from customer services to internal operations — and the pertinent data items in the system. The authors identify the most important aspects of a franchising business, the role of online analytical processing (OLAP) and data mining play and the data items that data mining should focus on to ensure its success.

Online Analytical Processing for Business Intelligence in Big Data

Big Data ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 501-518
Author(s):  
Jigna Ashish Patel ◽  
Priyanka Sharma
Keyword(s):  
Big Data ◽  
Business Intelligence ◽  
Online Analytical Processing ◽  
Analytical Processing

scholarly journals Business Intelligence Implementation To Analyze Perfect Store Data Using the OLAP Method

SinkrOn ◽  
2019 ◽  
Vol 3 (2) ◽  
pp. 103
Author(s):  
Afik Maulana ◽  
Dewi Ayu Nur Wulandari
Keyword(s):  
Data Processing ◽  
Marketing Strategy ◽  
Business Intelligence ◽  
Business Development ◽  
Online Analytical Processing ◽  
Business Strategies ◽  
Audit Report ◽  
Product Assortment ◽  
Analytical Processing ◽  
The Right

Perfect store is one of the business strategies owned by PT. Unilever where a store provides an appropriate product assortment and ensures visibility by displaying products in accordance with the planogram, and placed in the right position by taking into account the habits of the buyer and using the right display tools. This perfect store strategy aims to increase sales in the context of business development. To find out whether the perfect store strategy has been applied in all existing areas, a perfect store audit is needed. The method used to audit perfect store data is OLAP (Online Analytical Processing). The results of data processing with OLAP are in the form of a perfect store audit report that is accurate, relevant and timely which is presented in the form of an analysis chart that will be used by PT. Uniliver to see which areas have increased sales from the perfect store strategy that has been implemented so that PT Uniliver can determine the right marketing strategy.

scholarly journals Um Survey sobre a utilização de técnicas de Data Mining e Data Analytics por agências de investigação criminal do Brasil

2017 ◽  
Author(s):  
Rafael Santos ◽  
Fábio Nunes ◽  
Manoela Oliveira ◽  
Methanias Júnior
Keyword(s):  
Data Mining ◽  
Business Intelligence ◽  
Data Analytics ◽  
Online Analytical Processing ◽  
Analytical Processing

Em investigações criminais complexas, os envolvidos lidam com uma quantidade enorme e complexa de dados que necessitam de recursos computacionais especializados na extração de informações e correlações relevantes para o processo investigativo. Neste cenário, é necessário que haja apoio computacional, desde a etapa de armazenamento e integração entre diferentes bases de dados, até a etapa de análise estatística e descoberta de padrões. Este artigo discute os resultados de um Survey aplicado aos principais órgãos de combate ao crime organizado, tais como as agências de Inteligência de Segurança Pública – ISP, os Laboratórios de Tecnologia de Combate à Lavagem de Dinheiro – LABLDs e os Grupos de Atuação Especial de Repressão ao Crime Organizado – GAECO. O objetivo principal foi o de conhecer o cenário atual da utilização de ferramentas de análise de dados nessas agências, projetando as necessidades de pesquisa e investimentos nesta área. Entre os resultados encontrados, observou-se que 40% dos pesquisados não conhecem e 15% não utilizam soluções de ETL (Extract, Transform and Load), apesar de todos (100%) declararem possuir pelo menos uma ferramenta de Data Mining no seu local de trabalho, bem como também declararem (100%) possuir pelo menos uma ferramenta de OLAP/BI (Online Analytical Processing/Business Intelligence). Por fim e com proeminente destaque, apenas 2,77% dos pesquisados utilizam diretamente algum algoritmo de Mineração de Dados para extração de conhecimento. Este cenário evidencia, inicialmente, que a maior parte dos órgãos especializados em investigação do Brasil ainda não aplica efetivamente as técnicas de Data Mining e de Data Analytics em suas atividades.

scholarly journals Analisis Penerapan Model Business Intelligence pada Aplikasi Payment Point Online Banking dalam Meningkatkan Strategi Pemasaran (Studi Kasus: Aplikasi ApotikKuota)

2020 ◽  
Vol 7 (1) ◽  
pp. 1-10
Author(s):  
Altesa Yunistira ◽  
Dhomas Hatta Fudholi
Keyword(s):  
Business Intelligence ◽  
Marketing Mix ◽  
Online Banking ◽  
Online Analytical Processing ◽  
Analytical Processing ◽  
Online Bank

Perkembangan bisnis era digital saat ini membuat stakeholder aplikasi ApotikKuota menyadari besarnya tantangan dalam dunia bisnis. Saat ini, data merupakan hal yang berharga dan memiliki nilai penting sehingga membuat stakeholder ApotikKuota memiliki fokus pada penanganan data yang baik. Data tersebut antara lain berupa transaksi penjualan, pelanggan, serta data lainnya yang akan berguna dalam pengambilan keputusan dalam penerapan strategi pemasaran. Selama ini, penanganan pemasaran didasarkan pada intuisi stakeholder tanpa melihat manfaat dari proses analisis data yang ada. Business intelligence menjadi solusi bagi perusahaan atau organisasi untuk menganalisis dan menyediakan akses ke data guna membantu mengambil keputusan secara lebih baik. Dalam penelitian ini, peneliti merancang dan membangun model business intelligence untuk mendukung strategi pemasaran pada bisnis payment point online bank. Penelitian ini dilakukan untuk mengkaji penerapan business intelligence dengan membuat dashboard pelaporan dan online analytical processing untuk membantu stakeholder mengambil keputusan. Hasil penelitian ini berupa penyajian informasi yang dibutuhkan oleh stakeholder dalam proses pengambilan keputusan dengan mengacu pada penerapan strategi bauran pemasaran (marketing mix) yang memiliki komponen 4P, yaitu price, product, place, dan promotion. Kata Kunci: business intelligence, dashboard, payment point online bank, strategi pemasaran, pengambilan keputusan

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