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"Between the high-level concepts of business intelligence and the nitty-gritty instructions for using vendors’ tools lies the essential, yet poorly-understood layer of architecture, design and process. Without this knowledge, big data is belittled, projects flounder, are late and go over budget. Business intelligence guidebook : from data integration to analytics shines a bright light on an often neglected topic, arming you with the knowledge you need to design rock-solid business intelligence and data integration processes. Practicing consultant and adjunct BI professor Rick Sherman takes the guesswork out of creating systems that are cost-effective, reusable and essential for transforming raw data into valuable information for business decision-makers.After reading this book, you will be able to design the overall architecture for functioning business intelligence systems with the supporting data warehousing and data-integration applications. You will have the information you need to get a project launched, developed, managed and delivered on time and on budget, turning the deluge of data into actionable information that fuels business knowledge. Finally, you’ll give your career a boost by demonstrating an essential knowledge that puts corporate BI projects on a fast-track to success."

"Social data analytics is the first practical guide for professionals who want to employ social data for analytics and business intelligence (BI). This book provides a comprehensive overview of the technologies and platforms and shows you how to access and analyze the data. You'll explore the five major types of social data and learn from cases and platform examples to help you make the most of sentiment, behavioral, social graph, location, and rich media data. A four-step approach to the social BI process will help you access, evaluate, collaborate, and share social data with ease."

"Closed Circuit TeleVision (CCTV) cameras have been increasingly deployed pervasively in public spaces including retail centres and shopping malls. Intelligent video analytics aims to automatically analyze content of massive amount of public space video data and has been one of the most active areas of computer vision research in the last two decades. Current focus of video analytics research has been largely on detecting alarm events and abnormal behaviours for public safety and security applications. However, increasingly CCTV installations have also been exploited for gathering and analyzing business intelligence information, in order to enhance marketing and operational efficiency. For example, in retail environments, surveillance cameras can be utilised to collect statistical information about shopping behaviour and preference for marketing (e.g., how many people entered a shop; how many females/males or which age groups of people showed interests to a particular product; how long did they stay in the shop; and what are the frequent paths), and to measure operational efficiency for improving customer experience. Video analytics has the enormous potential for non-security oriented commercial applications. This book presents the latest developments on video analytics for business intelligence applications. It provides both academic and commercial practitioners an understanding of the state-of-the-art and a resource for potential applications and successful practice."

"It is beyond a doubt that the business landscape is constantly changing with every small business looking for the next competitive advantage. In Understanding the New Business Paradigm in Eastern Europe, Kozielski presents a universal model for building a successful business in these hectic times. His four-tiered model is based on lessons learned from both developed and emerging markets across Eastern Europe, and is neither limited to one type of organization or a market, nor has any geographical borders. Called the "four-leaf clover," Kozielski's model features the experiences of such companies as mBank (part of Commerzbank), Aflofarm, Atlas, Redan, Sphinx and more. This work will be of interest to academics and professional who are looking for a holistic and systematic approach to successful small business management."

"Asuransi merupakan industri yang berbasiskan pada layanaan produk baik asuransi jiwa maupun asuransi umum. Pembuatan produk sangat mengandalkan prediksi untuk penentuan tarif premi, khusus untuk asuransi jiwa prediksi mencakup: prediksi mortalitas, morbiditas, tingkat investasi dan biaya-biaya yang diambil dari premi yang dibayarkan nasabah. Volume data yang besar dan berada pada tempat yang terpisah menyulitkan untuk proses analisis dan membutuhkan waktu yang relatif lama. Untuk membantu melakukan analisis dan prediksi diatas salah satunya dengan menggunakan Business Intelligence yang merupakan salah satu tools untuk melakukan prediksi dibantu dengan analisis dari data mining yang sumber datanya diambil dari data warehouse berbasis model dimensional dan merupakan kumpulan data operasional yang terintegrasi. Pemodelan data warehouse sendiri tidak terlepas dari analisis proses bisnis dan analisis data operasional yang tersimpan. Untuk analisis proses bisnis digunakan tehnik value chain yang dapat menggambarkan aktifitas utama organisasi dan aktifitas pendukungnya dibantu dengan tehnik analisis balanced scorecard untuk menentukan indikator-indikator utamanya. Data yang digunakan terdiri dari analisis dimensi produk asuransi yang dijual, polis yang diterbitkan dan klaim yang terjadi, selanjutnya dibantu dengan visualisasi pola yang dihasilkan data mining dapat diambil kesimpulan mengenai pola-pola yang terjadi dimasa mendatang tentang penjualan produk, klaim dan polis yang terbit.Insurance is one of industries which is based on product services, life insurance and general insurance. Products are created rely on prediction in determining prime cost. Especially for life insurance, the prediction consists of that is contains of mortality rate, morbidity rate, investment rate and cost earned from customers prime. In insurance industry, data volume is big and located in separated systems. This condition will make product services analysis difficult and need a lot of time. To help enhance the analysis and prediction, Business Intelligence. It could be used as a tool which do the prediction with data mining analysis which source came from data warehouse. The data warehouse is based on dimentional model and it is a set of integrated operational data. Data warehouse?s model itself was unseparated from business process analysis and stored operational data analysis. The value chain technique was used to analyze business process that can describe organizations general activity and its supported activity. Balanced scorecard was used to determine the main indicators. Data used in this study came from the result of sold insurance product dimension analysis, published policy and claim. Next, data mining is used for classification visualization resulted. The result of analysis was integrated-data that was individual life, group life dan health onto data warehouse. The integrated data was classified with predictive value technique that created sold-product model, claim model, and published policy model."

"Business Intelligence merupakan salah satu trend teknologi dalam mendukung analisis dan pengambilan keputusan yang strategis di organisasi. Banyak organisasi yang menyatakan berhasil melakukan adopsi BI, banyak pula yang melaporkan kegagalan pasca adopsi. PT Taspen Persero memiliki permasalahan terhadap penggunaan BI, trend penggunaan BI menunjukkan penurunan hingga mencapai 16 di akhir tahun 2015. Berdasarkan fakta tersebut perlu dilakukan analisis mengenai faktor-faktor yang memengaruhi kelangsungan penggunaan BI di Taspen. Penelitian ini menggunakan pendekatan kuantitatif melalui penyebaran kuisioner kepada para pengambil keputusan dan pengguna BI di Taspen. Dari hasil pengumpulan data, didapatkan responden penelitian sejumlah 195 responden yang kemudian dianalisis dengan menggunakan Covariance Based SEM CB-SEM dengan bantuan perangkat lunak IBM Amos v22. Penelitian ini mengajukan sebuah model kerangka pemikiran dengan mengkombinasikan faktor Eksternal External Stimuli, Internal Internal Stimuli Afektif Affective Response, dan Kognitif Cognitive Response terhadap kelangsungan penggunaan BI Behavioral Response. Hasil dari penelitian ini menunjukkan Information Integration merupakan faktor yang paling signifikan dari sisi eksternal dalam membentuk pengaruh terhadap kelangsungan penggunaan, selain itu faktor yang paling signifikan dalam membentuk pengaruh terhadap kelangsungan penggunaan BI dari sisi perceive of usefulness yaitu increase productivity. Faktor relatedness dan trust juga memiliki pengaruh terhadap kelangsungan penggunaan continuance use BI, namun faktor organisasi yang diwakili oleh influence organization dan influence peers tidak memiliki pengaruh terhadap kelangsungan penggunaan continuance use BI. Hasil dari penelitian ini juga diharapkan dapat mendukung studi terkait kelangsungan penggunaan BI dan menjadi rekomendasi perbaikan program kerja BI pada ITMP Taspen 2015-2016.

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Business Intelligence BI is a technology trend that support the analysis and strategic decision making in an organization. Many organizations are declared successful adoption of BI, many also report the failure of post adoption. PT Taspen Persero has an issue related to the continuance usage intention of BI. BI usage trend showed a decrease of up to 16 at the end of 2015. Based on these facts, need to do a study of the factors influencing BI continuance usage intention at Taspen. This study uses a quantitative approach through the distribution of questionnaires to decision makers and users of BI. The questionnaires consisting of 38 items were distributed online and offline, and 195 responses were collected and analyzed. The results of this study indicate information integration and perceive of usefulness factors were the most influencing factor on the continuance usage intention of BI, Relatedness and trust factors also have an influence on the continuity of use continuance use BI, but organizational factors represented by the organization and peers influence have no effect on thecontinuance use of BI. The study proposed a model that combines external factors, internal factors, affective response, and cognitive response of BI. The results of this study shows integration of information, increasing productivity, and advanced reporting as factors that have strong influence to the continuance usage intention of BI. It is expected to support related studies, provide recommendations for improvements of BI, and evaluate BI work program on ITMP Infromation Technology Master Plan ."

"Salah satu tantangan yang dihadapi industri akomodasi di Indonesia adalah sulitnya melakukan pengambilan keputusan berdasarkan data dan informasi yang dapat diandalkan. Saat ini, Indonesia belum memiliki data usaha pariwisata yang komprehensif dan belum ada pusat informasi kepariwisataan berskala nasional yang dapat digunakan oleh para pemangku kepentingan. Untuk memperoleh data, mayoritas pengelola akomodasi masih melakukan praktik information sharing secara manual dan belum menggunakan sistem terintegrasi. Penelitian ini bertujuan untuk mengembangkan arsitektur dan prototipe (front-end) sistem business intelligence (BI) berbasis information sharing untuk mendukung proses revenue management di industri akomodasi di Indonesia. Pendekatan penelitian yang digunakan adalah Design Science Research yang menghasilkan solusi sesuai kebutuhan pemangku kepentingan di sektor akomodasi. Kajian pustaka dilakukan dengan metode Systematic Literature Review. Pengolahan dan analisis data wawancara menggunakan metode thematic analysis. Pengumpulan data pada penelitian ini dilakukan melalui observasi data pariwisata, observasi data pada online travel agent, wawancara kepada stakeholders (regulator, asosiasi hotel, akademisi, pengelola hotel, online travel agent, dan wholesaler), serta observasi terhadap sistem BI yang telah ada. Penelitian ini menghasilkan tiga hasil penelitian utama. Untuk memahami konteks ekosistem industri akomodasi, penelitian ini mengkaji penelitian terdahulu dan menghasilkan model downstream supply chain industri akomodasi di Indonesia saat ini. Untuk memahami permasalahan implementasi sistem BI, penelitian ini juga mengkaji dan menghasilkan analisis hambatan menggunakan kerangka kerja Technology Organization Environment (TOE) serta pemetaan tindakan yang dapat dilakukan. Berdasarkan kedua hasil tersebut, penelitian ini mengembangkan sebuah arsitektur dan prototipe high-fidelity sistem BI. Prototipe yang dihasilkan masih berupa front-end berbasis web dan belum sampai kepada pengembangan back-end. Evaluasi arsitektur dilakukan melalui wawancara kepada tujuh narasumber ahli serta pengujian inter-rater reliability kepada 18 responden yang menghasilkan tingkat persetujuan yang sangat baik (koefisien Fleiss-Kappa 0,933). Evaluasi prototipe dilakukan melalui wawancara serta survei System Usability Scale (SUS) yang menghasilkan nilai 74,5 (baik), dan Usability Testing yang menghasilkan nilai 70 (baik). Hasil penelitian ini bermanfaat sebagai panduan bagi regulator dan pelaku industri akomodasi dalam mengembangkan sistem BI yang mendorong kolaborasi data melalui information sharing untuk mendukung proses revenue management di industri akomodasi di Indonesia. Sebagai saran pengembangan, penelitian berikutnya dapat mempelajari aspek-aspek non-fungsionalitas serta mengimplementasikan back-end dan komponen-komponen yang sudah diidentifikasi di dalam arsitektur sistem BI ini.

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One of the challenges faced by the accommodation industry in Indonesia is the difficulty of making decisions based on reliable data and information. Currently, Indonesia does not have comprehensive tourism business data and there is no national-scale tourism information center that can be used by stakeholders. To obtain data, the majority of accommodation managers still practice information sharing manually and have not used an integrated system. This research aims to develop an architecture and prototype (front-end) of information sharing-based business intelligence (BI) systems to support the revenue management process in the accommodation industry in Indonesia. The research approach used is Design Science Research which produces solutions according to the needs of stakeholders in the accommodation sector. Literature review is carried out using the Systematic Literature Review method. Processing and analysis of interview data is carried out using thematic analysis method. Data collection in this study was carried out through observation of tourism data, observation of data on online travel agents, interviews with stakeholders (regulators, hotel associations, academics, hotel managers, online travel agents, and wholesalers), as well as observation of the existing BI system. This study produced three main research results. To understand the context of the accommodation industry ecosystem, this study examines previous research and produces a downstream supply chain model, especially for the current accommodation industry in Indonesia. To understand the BI system implementation problems, this study also examines and produces a barrier analysis using the Technology Organization Environment (TOE) framework as well as mapping actions that can be taken to implement and run the BI system. Based on these two results, this research developed an architecture and prototype of a high-fidelity BI system. The prototype is still a web-based front-end and has not yet reached the back-end development. The architectural evaluation was conducted through interviews with seven experts and inter-rater reliability testing to 18 respondents which resulted in a very good approval rate (Fleiss-Kappa coefficient 0.933). Prototype evaluation was conducted through interviews as well as a System Usability Scale (SUS) survey which resulted in a score of 74.5 (good), and Usability Testing which produced a value of 70 (good). The results of this study are useful as a guide for regulators and accommodation industry players in developing a BI system that encourages data collaboration through information sharing to support the revenue management process in the accommodation industry in Indonesia. Future research can study non-functionality aspects and implement back-end and components that have been identified in this BI system architecture."

"Managing extreme financial risk addresses the need for better management strategies in light of increased market risk and volatility in financial institutions' revenue models. Top officials from the financial and regulatory industries point to real corporate issues, showing how institutions react to financial crises. From first-hand experiences, they explain how effective sustainability management does not just prevent being blindsided; it also leads to proactive solutions that enhance an institution's strength to weather a sudden financial crisis, add significant shareholder value, and reduce systemic risk. Readable, coherent, and logical, managing extreme financial risk shows how extreme risk needs to be handled when the cost of being wrong means the difference between life and death of the institution."