Big Data

The aim of this article is to recover one of the most interesting ecological thoughts of the last century, that of Félix Guattari, and to insert it in time and counter-time in a reflection that shows how, on the one hand, he makes an anticipation of the themes of the Anthropocene while, on the other hand, is already able to suggest a "third way", which moves away from the fideistic attitude adopted both by "deep ecologists" towards nature, and by the "geo-constructivists” with regard to technology. In the desire to overcome this dichotomy and its oppositional plan, but still maintaining a distinction, Guattari inaugurates an entirely original ecological thought.

El Big Data está tomando un papel cada vez más importante en el ámbito educativo. Las nuevas herramientas tecnológicas y el análisis masivo de datos favorecen el diseño de sistemas educativos mejor adaptados a las exigencias del mundo actual.

Artificial intelligence (AI) is a hot topic in digital health, as automated systems are being adopted throughout the health care system. Because they are still flexible, emerging technologies can be shaped significantly by media representations as well as public engagement with science. In this context, we examine the belief that negative news media coverage of AI—and specifically, the alleged use of imagery from the movie Terminator—is to blame for public concerns about AI. This belief is identified as a potential barrier to meaningful engagement of AI scientists and technology developers with journalists and the broader public. We name this climate of risk perception the “Terminator Syndrome”—not because of its origins in the movie of the same name per se, but because such unchecked beliefs can terminate broad public engagement on AI before they even begin. Using both quantitative and qualitative approaches, this study examined the hypothesis that the news media coverage of AI is negative. We conducted a sentiment analysis of news data spanning over six decades, from 1956 to 2018, using the Google Cloud Natural Language API Sentiment Analysis tool. Contrary to the alleged negative sentiment in news media coverage of AI, we found that the available evidence does not support this claim. We conclude with an innovation policy-relevant discussion on the current state of AI risk perceptions, and what critical social sciences offer for responsible AI innovation in digital health, life sciences, and society.

Este libro ha sido coeditado en el marco del programa Mestizajes, que dirige Gustavo Ariel Schwartz en el Donostia International Physics Center. Ha sido el resultado de la colaboración entre un físico y un humanista durante dos años, y de las contribuciones de casi noventa investigadores y creadores de las más diversas procedencias y disciplinas. Este libro ha surgido de un mestizaje intenso e irrepetible que ha permitido pensar transversalmente algunas preguntas fundamentales del contacto entre distintos ámbitos del saber.

Makalah ini bertujuan untuk mengembangkan alat untuk memprediksi Informasi arus lalu lintas yang akurat dan tepat waktu. Lingkungan Lalu Lintas melibatkan segala sesuatu yang dapat mempengaruhi lalu lintas yang mengalir di jalan, baik itu rambu lalu lintas, kecelakaan, unjuk rasa, bahkan perbaikan jalan yang dapat menyebabkan kemacetan. Jika kami memiliki informasi sebelumnya yang sangat mendekati perkiraan tentang semua hal di atas dan banyak lagi lebih banyak situasi kehidupan sehari-hari yang dapat memengaruhi lalu lintas, seorang pengemudi atau pengendara dapat membuat keputusan yang tepat, ini membantu dalam
masa depan kendaraan otonom. Dalam beberapa dekade saat ini, data lalu lintas telah  menghasilkan secara eksponensial, dan kami telah bergerak menuju konsep big data untuk transportasi. Prediksi yang tersedia metode arus lalu lintas menggunakan beberapa model prediksi lalu lintas dan masih belum memuaskan untuk menangani aplikasi dunia nyata. Fakta ini menginspirasi kami untuk mengerjakan masalah perkiraan arus lalu lintas yang dibangun data dan model lalu lintas. Sulit untuk memperkirakan lalu lintas mengalir secara akurat karena data tersedia untuk transportasi sistem sangat besar. Dalam pekerjaan ini, kami berencana menggunakan mesin pembelajaran, genetika, komputasi lunak, dan algoritma pembelajaran mendalam untuk menganalisis data besar untuk sistem transportasi dengan kompleksitas yang jauh berkurang, algoritma Pemrosesan Gambar adalah sangat terlibat dalam pengenalan rambu lalu lintas, yang pada akhirnya membantu untuk pelatihan yang tepat dari kendaraan otonom.

Kata kunci—Lingkungan Lalu Lintas,Deep Learning, Machine Learning, Algoritma Genetika, Komputasi Lunak, Big Data, GambarPengolahan.

In this research, we compared the accuracy of machine learning algorithms that could be used for predictive analytics in higher education. The proposed experiment is based on a combination of classic machine learning algorithms such as Naive Bayes and Random Forest with various ensemble methods such as Stochastic, Linear Discriminant Analysis (LDA), Tree model (C5.0), Bagged CART (treebag) and K Nearest Neighbors (KNN). We applied traditional classification methods to classify the students’ performance and to determine the independent variables that offer the highest accuracy. Our results depict that the data with the 11 features using random forest generated the best accuracy value of 0.7333. However, we revised the experiment with ensemble algorithms to reduce the variance (bagging), bias (boosting) and to improve the prediction accuracy (stacking). Consequently, the bagging random forest outperformed other methods with the accuracy value of 0.7959.

Information security breaches pose a growing threat to organizations and individuals, particularly those that are mainly associated with the e-commerce industry. Data security within an organization is important as Information systems are susceptible to cyber-attacks and usage of Information systems is increasing dramatically in every sector whether it is the FMCG sector or education sector. An information security breach can have a major impact on the financial standing of the breached company and its competitors.

Disusun untuk memenuhi tugas mata kuliah Sistem Informasi Manajemen kelas E Disusun Oleh : Satrio B. Haryanto 12010113140245 PROGRAM STUDI MANAJEMEN FAKULTAS EKONOMI DAN BISNIS UNIVERSITAS DIPONEGORO SEMARANG 2015 KATA PENGANTAR Puji syukur penulis panjatkan kepada Allah SWT karena dengan anugerah inspirasi yang diberikan Allah SWT sungguh menjadi sumber pengetahuan bagi penulis dalam menyelesaikan penulisan makalah resume Perilaku Organisasi yang berjudul "BIG DATA". Resume ini disusun sebagai tugas kelompok mata kuliah Sistem Informasi Manajemen kelas E Selesainya penyusunan makalah ini adalah berkat dukungan dan bimbingan dari dosen pengampu yaitu Idris, SE., MSi dan I Made Sukresna, SE., MSi Semoga makalah ini dapat memberi manfaat dan sumber informasi bagi penulis dan pembaca. Semarang Penyusun BAB I PENDAHULUAN 1.3 Tujuan Penulisan Makalah

Nous sommes entrés dans l’ère de l’information exponentielle. Selon IBM, l’année 2020 devrait être marquée par un taux de doublement de nos « connaissances » toutes les douze heures. Pour appréhender cette croissance gigantesque, il suffit de la comparer avec celle qu’avait estimé R. Buckminster en 1945. Selon ce dernier, les connaissances doublaient en accord avec un cycle de vingt-cinq ans. Nos capacités à produire des données, qui, rappelons-le, ne peuvent pas toujours être considérées comme des connaissances, se sont donc retrouvées multipliées au-delà du raisonnable.

Dès lors, nos nations, entreprises, chercheurs et plus trivialement nos concitoyens se retrouvent submergés par des ressources infinies lorsqu’elles sont prises à l’échelle individuelle. Il devient très vite tentant de conduire des projets d’ampleur prométhéens dans les domaines constituant nos sociétés. Pour autant, la greffe prendra-t-elle entre ces systèmes et sociétés - nés de périodes où la quantité d’information était à dimension humaine - et ces nouvelles ressources ? Plus important encore, si cette « union » aboutie, quels en sont et seront les coûts ?

Il serait incongru d’approcher cette révolution de la connaissance avec pessimisme et inquiétude, toutefois, il demeure important de (re)créer des garde-fous adaptés à l’ « âge de la connaissance » (Idriss ABERKANE). Pour reprendre les dires de Isaac ASIMOV, relayés par Idriss ABERKANE (Docteur en neuroscience), « Une civilisation qui produit beaucoup de connaissance et peu de sagesse est vouée à l’extinction. ». L’idée même de cette citation ainsi que son sous-jacent prennent une importance cruciale dans une période où la science des données et plus vulgairement l’Intelligence Artificielle connaissent un regain d’intérêt pour des entités gouvernementales et privées. Comme l’a souligné Vladimir POUTINE lors d’une intervention télévisée, la nation qui deviendra le leader en termes d’intelligence artificielle, sera maître du monde.

Au-delà des propos, somme toute légèrement catastrophistes, prononcés par le dirigeant russe, nous percevons que la science des données représentent un réel enjeu et ce sur de nombreux plans (santé, militaire, industries et bien d’autres). Les opportunités sont et seront nombreuses, tout comme les menaces.

Le sujet de la science des données et plus largement de la connaissance sont bien trop large et mouvant pour être pleinement exploités dans ce mémoire. C’est pourquoi je concentrerai ce travail sur la mesure dans laquelle la science des données et plus particulièrement la branche de l’intelligence artificielle entraîne une refonte de la discipline du marketing. Ce mémoire s’inscrit dans un sujet où les connaissances évoluent de jour en jour. Mon ambition est donc de partager avec vous un « état de l’art », si éphémère soit-il, des apports de technologies de science des données au sein de la discipline du marketing. J’insiste sur le fait que ce devoir s’inscrit dans un contexte dynamique dans la mesure où comme le souligne le célèbre chercheur en intelligence artificielle (I.A) Yann LECUN, les experts dans ce domaine seront amenés à changer radicalement de paradigme pour maintenir la pérennité de l’I.A. En somme, les « connaissances » exposées dans ce mémoire ainsi que les travaux sur lesquelles je m’appuie sont le fruit d’un paradigme donné qui, je l’espère pour le dynamisme de la recherche en I.A, évoluera.

La construction de mon devoir se veut simple et vise à fournir une définition claire de la science des données, à explorer les technologies utilisées dans ce domaine et enfin à appréhender les différents cas d’usages possibles de ces dernières en marketing. Bien entendu, ce mémoire explore également une composante primordiale de la science des données : La question de l’Homme. En effet, au-delà de la découverte du « Marketing à l’ère de l’I.A » (Harvard Business Review, 2019) et de ses avantages indéniables, nous explorerons les questions éthiques soulevées par ces disciplines et découvrirons les écueils à éviter et les chemins souhaitables d’emprunter.

En somme, vous pouvez considérer, pragmatiquement, ces écrits comme une initiation, non technique, à la science des données et à ses applications possibles au sein de la discipline du marketing. Toutefois, le fil rouge de ce devoir réside dans l’objectif de créer, pour reprendre le néologisme « neurosagesse » mis en en avant par I. ABERKANE, un mémoire de « datasagesse ».

In the modern era of advertising, the role of marketing has increased exponentially. The marketing strategies of big brands nowadays highly rely on digital media. A new method of marketing known as digital marketing has evolved more than the rest of the marketing strategies. Digital marketing has now become the need of the hour for various brands and e-commerce platform. The proposed system will help such brands to reach out to the end user more efficiently and frequently. The proposed system is based on the implementation of Robotic Process Automation (RPA) which is a method used for deployment of software-based robots that mimic the functionalities of human operating a machine.

Massive datasets of communication are challenging traditional, human-driven approaches to content analysis. Computational methods present enticing solutions to these problems but in many cases are insufficient on their own. We argue that an approach blending computational and manual methods throughout the content analysis process may yield more fruitful results, and draw on a case study of news sourcing on Twitter to illustrate this hybrid approach in action. Careful combinations of computational and manual techniques can preserve the strengths of traditional content analysis, with its systematic rigor and contextual sensitivity, while also maximizing the large-scale capacity of Big Data and the algorithmic accuracy of computational methods.

There is an inevitable ethnocentrism currently at play in debates about the power of data and the power over data. ‘Global’ data problems and solutions are conceived as beginning and ending in regions with meaningful and enforceable data protection regulation, namely the US, the EU and a small group of other OECD countries tightly bound to these regions by trade, such as Canada. This chapter assesses the problems posed by regulating data markets outside high-income countries, and proposes several directions in which to look for solutions.

The social networking sites are storming with vast amount of information is produced and processed. This production of enormous amount of data from different microblogging platforms needs to be stored and processed by Big data approach. The data generated in peta bytes from social media platforms is called big data. Most of the world populations are sharing their opinion and feedback every day on micro blogging sites, the opinion and behavior of the user on microblogging site is tedious. Number of devices, laptops, iPad, Tabs, MacBook and distinct IOT data gadgets produced enormous amount of data. The processing and retrieving of this huge amount of data becomes a very complicated task. Nowadays social media is playing a crucial rule in our day to day life. The social media platforms have been greatly used for expressing human opinions for the item and verities of services. The business of different organizations is based on the feedbacks and rating of millions of the microblogging site uses can be used to extract their opinion, attitudes and sentiment towards the products. This feedback information on social media used for the future market of the business improvement and analysis of the product performance. The extracting the user's opinion from the social media platforms is a difficult task; it can be redefined into various ways. In this paper, an open source approach is presented, and data is collected from tweets from twitter API, analyzed and visualized these tweets using python. To analyze sentiments of tweets we have used K-Means clustering algorithm and implemented with Python programming language. This sentiment analysis is based on the tweets data retrieval from different sources and then classifying the user perspectives in different classifications accuracy and two unique sentiments (positive and negative).The process of sentiment analysis is the computational procedure that deciding the output by the proposed method is positive or negative. In this paper, an endeavor has been modelled to prefer analysis method for sentiment of twitter dataset. In the proposed technique polarity of each tweet is calculated to differentiate whether the tweet is neutral, positive or negative. The sentiment sentence's polarity is the emotions of user such as angry, sad, happy and joy. The proposed entire research work processed and implemented using Python.

The need to access to the information in a fast and reliable way has become an inevitable and urgent requirement within the scope of technological advances. Both the need of accessing to the information and the necessity to protect the information from malware and attackers, emphasize once more that the information security and cyber defense should be underlined with great attention. Today, the number of the systems, which do not interact with IT infrastructure, is quite insignificant. Critical infrastructures are managed centrally by using IT infrastructure. Security of critical infrastructures has become a main problem on its own. The notion of cyber-attacks is generally perceived as premeditated disruptive activities against computer networks, computer programs and data to create chaos and impair functioning infrastructures. Despite significant investment in technology and infrastructure, cyber-attacks represent one of the greatest challenges in information security. Cyber-attacks primarily pose threats to Internet-based applications and can disable a country’s power or other assets, which are connected to the Internet. By penetrating computer systems that control the energy and other basic services in a country, cyber-attacks can bring down a national service, causing serious cascading effects to create chaos and destabilize a country. Cyber-attacks do not pose a direct threat to infrastructures that are completely isolated from the internet but these infrastructures may be vulnerable to cyber sabotage (e.g. manual importing of virus). With this article, importance of the information and critical infrastructure security and cyber defense will be discussed by proposing solutions against cyber-attacks and possible cyber-attacks regarding the preventive enterprise applications and security of critical infrastructures like power generation and SCADA systems.

This article examines the growing entanglements between the
digital and the world of food while suggesting that food is a
particularly generative space through which to understand the
evolving but often hidden role of the digital in our everyday lives.
The article starts by examining food photography on social media
before discussing the role of ordinary people as participants in
online food culture via video-sharing platforms such as YouTube.
Mapping the shift from web 2.0’s dreams of creativity and sharing
to the monetisation of digital food communities, section 3 focuses
on food politics, and ‘the antinomies of connectivity’. The final
section discusses big food players and their use of social media in
an era of dataveillance and big data. It argues that ‘food citizens’
need to have an awareness of the commercial logics that support
the communicative ecologies in which we increasingly engage with
food and lifestyle practices.

Third Edition - Springer
This book is designed to be suitable for an introductory course at either undergraduate or masters level. It can be used as a textbook for a taught unit in a degree programme on potentially any of a wide range of subjects including Computer Science, Business Studies, Marketing, Artificial Intelligence, Bioinformatics and Forensic Science. It is also suitable for use as a self-study book for those in technical or management positions who wish to gain an understanding of the subject that goes beyond the superficial. It goes well beyond the generalities of many introductory books on Data Mining but—unlike many other books—you will not need a degree and/or considerable fluency in Mathematics to understand it.

En el presente artículo se realiza una discusión teórica en torno a los discursos que han rondado en la literatura sobre Internet y los medios digitales, avocándonos particularmente en la pregunta por cómo han impactado estos en la construcción de nuestras identidades. En particular, se revisa las publicaciones de Sherry Turkle, contrastando los trabajos iniciales con el giro que presenta en sus trabajos más contemporáneos en donde termina por fetichizar la cultura predigital. Se da revista a la noción de “yo proteico”, en que al igual que el Dios Proteo, según Turkle íbamos a poder explorar múltiples y fragmentadas identidades en el ciberespacio. Pero esta idea deviene en mito aproximarnos desde una mirada que dé cuenta de la producción multifactorial detrás de la identidad. Después, se plantea que ante la creciente rastreabilidad y vigilancia de las personas y la formación del denominado Big Data por parte de terceros, se puede caer ahora en una fetichización de la cultura digital. Esto nos llevaría a un mito inverso, el de un “yo identificado” y cuantificado, al asociar por completo al individuo a su data digital. Ambos mitos presentan en términos discursivos, atribuciones inversas del concepto de autenticidad que dan cuenta de lo maleable y contingente que se vuelve la relación entre las tecnologías mediales y la identidad enactada con ellas.

L'enjeu de cette thèse de philosophie des sciences était de répondre à un problème pratique, qui s'est présenté à moi alors que je travaillais comme analyste sur des données massives chez un éditeur de logiciel : comment produire des connaissances valides en manipulant de grandes masses de données que je n'ai pas constituées et qui ne sont pas le fruit d'une méthode scientifique reconnue ?

En m'appuyant sur mon expérience de terrain, je propose un paradigme méthodologique pour la construction, l'exploration et l'interprétation des données massives. Par paradigme méthodologique, on entend un cadre théorique et pratique qui fournit autant de clés pour développer une méthode adaptée aux données et au projet épistémique envisagés. En faisant la part du mythe des big data et des pratiques effectives, je montre comment les données numériques, toujours déjà manipulables, sont construites techniquement et épistémologiquement à partir des traces laissées par les individus et leurs médiations sur les supports informatiques. Cette construction s'appuie sur une logique de constitution qui requiert un cadre interprétatif et une continuité épistémique entre la donnée et les connaissances que l'on cherche à produire. Les sciences de la culture fournissent ainsi un cadre nécessaire, mais pas suffisant, à assurer cette continuité. Le calcul, incarné par les sciences des données et l'intelligence artificielle, actualise et instrumente cette continuité au prix du renoncement à s'envisager comme fin en soi. Ni le cadre théorique, ni le calcul, ne suffisent toutefois à rendre intelligibles les connaissances ainsi produites : c'est la médiation de l'interprétation, du récit et de la conception logicielle (ou design) qui matérialise, donne à voir et contextualise les connaissances ainsi produites. Ces dernières, enfin, ne sont pas légitimées par leur pur caractère véridictionnel, mais par leur capacité à proposer ou faciliter des décisions d'action, bien souvent en entreprise, elles-mêmes productrices de nouvelles traces numériques manipulables.

Undersea communication cables are the core critical infrastructure of the digital age. 99% of all transoceanic digital communication-financial transactions, emails, or voice messaging-is transported through undersea fiber-optic cables. The global submarine cable network is a critical infrastructure that does not receive the analytical attention it deserves. We argue that cable security is a core dimension of current and future international security governance. We present the first systematic survey of the academic discourses that investigate the politics, governance, and protection of submarine data cables. Three rather narrow literatures, study the cables 1) as under threat from hybrid warfare and terrorism, or treat the cable network narrowly as a 2) technical or 3) regulatory problem. We demonstrate the need for broadening out the research agenda and addressing key questions of security governance and geopolitics of this increasingly critical infrastructure.

This work presents the influence of ergonomics on the productivity of a workplace, and how ergonomic measures can facilitate a better working environment in the organization. The various interactions between an employee, and his immediate environment, and how ergonomic interventions can help reduce the physical and physiological stress on the individual have also been studied. The current roles and focus of the Human Resource management function of an organization to help improve the work-life balance of the employees is dealt with. Suggestions for how ergonomic interventions can help achieve this work-life balance have been provided

For over forty years, relational databases have been the leading model for data storage, retrieval and management. However, due to increasing needs for scalability and performance, alternative systems have emerged, namely NoSQL technology. The rising interest in NoSQL technology, as well as the growth in the number of use case scenarios, over the last few years resulted in an increasing number of evaluations and comparisons among competing NoSQL technologies. While most research work mostly focuses on performance evaluation using standard benchmarks, it is important to notice that the architecture of real world systems is not only driven by performance requirements, but has to comprehensively include many other quality attribute requirements. Software quality attributes form the basis from which software engineers and architects develop software and make design decisions. Yet, there has been no quality attribute focused survey or classification of NoSQL databases where databases are compared with regards to their suitability for quality attributes common on the design of enterprise systems. To fill this gap, and aid software engineers and architects, in this article, we survey and create a concise and up-to-date comparison of NoSQL engines, identifying their most beneficial use case scenarios from the software engineer point of view and the quality attributes that each of them is most suited to.

Internet of Things (IoT) & Big Data are considered as one of the big benefits for business. So, many types of organisations use IoT and big data technology for various purposes not limited to business automation, business intelligence and marketing. IoT and big data can play a great role in restaurant industry. But these technologies are not widely used in the restaurant industry. This paper proposes an IoT and big data based system customized for restaurants and evaluates its opportunities, benefits and challenges. It also explains how the system can be integrated to the operations of restaurant.

This article presents results from the first statistically significant study of cost escalation in transportation infrastructure projects. Based on a sample of 258 transportation infrastructure projects worth US$90 billion and representing different project types, geographical regions, and historical periods, it is found with overwhelming statistical significance that the cost estimates used to decide whether such projects should be built are highly and systematically misleading. Underestimation cannot be explained by error and is best explained by strategic misrepresentation, that is, lying. The policy implications are clear: legislators, administrators, investors, media representatives, and members of the public who value honest numbers should not trust cost estimates and cost-benefit analyses produced by project promoters and their analysts.

This introduction is divided into two main sections. In the first section, the pars denstruens, the three spectres (technological instrumentalism, functionalism, and technological determinism), and the five fallacies (spatial dualism, one-medium fallacy, technological presentism, technological visibility, and alternativeness) of the communicative reductionism that plagues the media/movement literature are critically assessed. In the second section, the pars construens, the case studies, and the methods on which the book relies are illustrated, and a new conceptual vocabulary is proposed in order to restore the communicative complexity of social movements. The conceptual lenses of media practices, ecologies, imaginaries, and algorithms are introduced and illustrated, along with an outline of the sections and the chapters composing the book.

Title: The future of audit: Examining the opportunities and challenges stemming from the use of Big Data Analytics and Blockchain technology in audit practice

Seminar Date: 29.05.2017

Course: BUSN79 Degree Project in Accounting and Finance

Authors: Nikola Kostić, Xiao Tang

Supervisor: Rolf G. Larsson

Examiner: Peter Jönsson

Key Words: Audit, Big Data Analytics, Blockchain, Distributed Ledger, Innovation

Thesis Purpose: The purpose of this thesis is to contribute to the extant knowledge and further research regarding the effects of Big Data Analytics (BDA) and blockchain (BC) technology on the future of the audit profession and to provide a framework grounded in existing theoretical research which would explore ways in which BDA and BC technology could be integrated into the audit procedures of the future.

Methodology: A qualitative approach has been chosen and mainly inductive reasoning has been used to answer the research questions. First, a systematic literature review has been performed. Second, a case study has been conducted using semi-structured interviews at KPMG Luxembourg and PwC Malmö.

Theoretical Perspective: The theoretical perspective is an aggregation of the most relevant findings from the Systematic Literature Review (SLR) and the Case Study (CS), which represents the underlying theoretical foundation for this thesis. Moreover, a theoretical framework is built upon those results.

Empirical Foundation: The empirical data for this thesis has been collected through semi-structured interviews with one employee at PwC in Malmö and five employees at KPMG Luxembourg. Furthermore, internal and external reports have been collected to derive conclusions.

Conclusions: The body of research relating to BDA and BC technology has been growing at an increasing rate in the last three years. Increased standardisation of audit procedures and use of BDA could enable and foster the implementation of BC technology, which will change the audit profession. Semi- or full automation of time consuming but simple audit tasks will lead to more effectiveness and efficiency; and ultimately to cost-savings. The CS showed that contextual factors have an impact on interviewees' perception regarding the challenges and the future of their profession. However, they acknowledge that BDA and BC technology will play a big role in the future of audit. Furthermore, this thesis provides a theoretical framework which could enable audit firms to integrate BDA and the BC technology into future audit procedures.

( Alternatif Link download Buku Analisis Big Data: https://bit.ly/2x8ta9S )

Alhamdulillahhi robbil alamin, puji syukur kehadirat Allah SWT atas segala rahmat dan karunia-Nya dengan terselesaikannya penulisan buku ini dengan judul “Analisis Big Data”. Buku ini merupakan uraian untuk memudahkan pemahaman konsep, tingkat dasar sampai lanjut dalam sistem cerdas dan penerapannya melalui pemanfaatan teknologi Big Data, dengan mengedepankan keterampilan dalam pembuatan dan hasil implementasi dengan berbagai kombinasi algoritma berbasis sistem cerdas maupun dengan perpaduan berbagai macam tools untuk membangun ekosistem analisis Big Data yang powerfull. Konsep sederhana Analisis Big Data mencakup Volume, Velocity, dan Variety (3V), dan pengembangannya ada yang menyebut (7V) termasuk Volume, Velocity, Variety, Variability, Veracity, Value dan Visualization, atau 10V bahkan lebih dari itu, tetapi sebaiknya tidak membatasi pemahaman Big Data ini hanya dengan sedikit banyaknya istilah dari huruf V yang digunakan :). Kemudian dengan adanya ekosistem tersebut, jika dibutuhkan analisis sederhana maupun yang lebih kompleks, maka harapannya tidak akan ada kendala dari besarnya data yang diolah. Adanya kemajuan teknologi dalam hal penyimpanan, pengolahan, dan analisis Big Data meliputi (a) penurunan secara cepat terhadap biaya penyimpanan data dalam beberapa tahun terakhir; (b) fleksibilitas dan efektivitas biaya pada pusat data dan komputasi awan untuk perhitungan dengan konsep elastisitas dan penyimpanannya; serta (c) pengembangan kerangka kerja baru seperti Hadoop ecosystem (salah satu peluang bisnis yang besar untuk developer untuk saat ini dan ke depannya dalam rangka membangun ekosistem analisis Big Data yang sangat powerfull sekelas Cloudera, Hortonworks, etc), yang memungkinkan pengguna untuk mengambil manfaat dari sistem komputasi terdistribusi, misal untuk menyimpan sejumlah data yang besar melalui pemrosesan parallel, dukungan database NoSQL, dan komputasi berbasis streaming. Sehingga kemajuan teknologi ini telah menciptakan beberapa perbedaan yang sangat signifikan, misal dalam hal kecepatan maupun ketepatan dari hasil yang didapatkan antara analisis tradisional dengan tools yang bukan dengan konsep Big Data versus analisis modern untuk saat ini dan masa depan dengan membangun ekosistem Big Data yang sangat powerfull.
Penulis mengucapkan terimakasih yang sebesar-besarnya kepada kedua orang tua penulis, spesial kepada Istriku tercinta “Alfun Lailatul Musabbikha”, bapak ibu mertua, dik Wiwik, dik Ganda, kak Mat, kak Deri, Bude Gi, Pakde Dul, Bude Gani, Pak Abu, mbak Nik, dik Andre, Mbak As, Mbak Lia, Mas Mualif, Mbak Lis, Pakde Naji, Bulik Yul, Pakde Tasrun, Pakde Zen, Pakde Zud, Paklik Fiq, mas Bowo dan semua sanak saudaraku yang tak bisa kusebutkan seluruhnya, serta beberapa pihak yang telah membantu penyelesaian buku ini:
1. Para penulis artikel Analisis Big Data di forum, web, blog dan buku yang menjadi referensi buku ini untuk memberikan masukan yang sangat berharga sekali untuk perbaikan dan penyelesaian buku ini.
2. Mbak Efi Riyandani, yang telah banyak membantu penulisan buku, dan mahasiswa-mahasiswa terbaik saya semester Ganjil 2016/2017, yaitu: Maryamah, Moh. Fadel Asikin, Daisy Kurniawaty, Selly Kurnia Sari, Nanda Agung Putra, Ardisa Tamara Putri, Dhimas Anjar Prabowo, Listiya Surtiningsih, Raissa Arniantya, Brillian Aristyo Rahadian, Diva Kurnianingtyas, Dyan Putri Mahardika, Tusty Nadia Maghfira.
3. Mahasiswa-mahasiswa terbaik saya semester Ganjil 2017/2018, yaitu: Yessica Inggir F., Kholifaul K., Ni Made Gita D. P., Ema Agasta, Retiana Fadma P. Sinaga, Fachrul Rozy Saputra Rangkuti, Yunita Dwi Alfiyanti, Dyah Ayu Wahyuning Dewi, Annisaa Amalia Safitri, Sarah Aditya Darmawan, Danastri Ramya Mehaninda, Eka Novita Shandra, Fakharuddin Farid Irfani, Rio Cahyo Anggono, Robih Dini, Yulia Kurniawati, Novirra Dwi Asri, Muhammad Vidi Mycharoka, Vania Nuraini Latifah, Olivia Bonita, Eka Miyahil Uyun, Cusen Mosabeth, Evilia Nur Harsanti, Ivarianti Sihaloho.

Semoga kontribusi kalian menjadi ilmu yang barokah dan bermanfaat. Aamiin. :). Tidak ada gading yang tak retak. Maka penulis memohon kritik dan saran untuk perbaikan dan penyempurnaan buku ini. In Syaa Allah pada edisi berikutnya, kami akan memberikan manualisasi Map Reduce, Spark, etc. dari setiap algoritma pada setiap contoh kasusnya. Selamat membaca buku ini dan semoga bermanfaat.

Malang, 19 Juli 2016-24 Mei 2018

Penulis

Communication and design are dynamic sectors with regard to career opportunities. This is due to their involvement in the digital world and the new interactive technologies, among other reasons. By analyzing job offers published in Domestika, the principle specialized web portal in the sector, we have carried out a diagnosis of the most highly demanded and best paid professional profiles as well as the requirements for these types of profiles. This study reveals that in the area of communication, the digital world is the leader in employment offers, although a higher salary is not always implied by this situation. There are professional profiles linked to social networks, an activity that we usually identify as a digital trend, which have a lower remuneration than would be expected. However, the best paying jobs are those linked to big data, user experience (UX), and digital marketing and design department coordination. The full-stack profile and its integrated perspective from the user’s experience to the infrastructure that supports services, is a reality among these types of higher-paying jobs.

We propose that digital technologies and related data become increasingly prevalent and that, consequently, ethical concerns arise. Looking at four principal stakeholders, we propose corporate digital responsibility (CDR) as a novel concept. We define CDR as the set of shared values and norms guiding an organization's operations with respect to four main processes related to digital technology and data. These processes are the creation of technology and data capture, operation and decision making, inspection and impact assessment, and refinement of technology and data. We expand our discussion by highlighting how to managerially effectuate CDR compliant behavior based on an organizational culture perspective. Our conceptualization unlocks future research opportunities, especially regarding pertinent antecedents and consequences. Managerially, we shed first light on how an organization's shared values and norms regarding CDR can get translated into actionable guidelines for users. This provides grounds for future discussions related to CDR readiness, implementation, and success.

Gesellschaft erwachsen (vgl. Ellul 1964: 170). Heute, über 60 Jahre später, in Zeiten von BigData ist das, was damals noch den Charakter theoretischer Spekulation hatte, Realität und Gegenstand der allgemeinen soziologischen Debatte (vgl. Apprich 2017: 55). Dabei nimmt Ellul nicht nur wesentliche Erkenntnisse vorweg, sondern ist in zahlreichen Aspekten auch heute noch relevant, fruchtbar und damit anschlussfähig an die aktuelle technikethische und techniksoziologische Debatte. Die Interpretation Elluls als einen idealtypischen Vertreter eines Technikdeterminismus, worunter man Vertreter solcher Theorien versteht, die von Technik und Sozialem als getrennten ontologischen Kategorien ausgehen, die der Technik -als eigenständiger ontologischer Kategorie -bestimmte intrinsische Gesetzmäßigkeiten, das heißt eine Eigenlogik zuschreiben, welche als aktiver Motor gesellschaftlichen Wandels fungiert, bestimmt bis heute die soziologische Rezeption seines Werks (vgl. Passoth 2008: 126). Diese Vorwürfe veranlassten Ellul bereits 1964, im Vorwort zur überarbeiteten Ausgabe der amerikanischen Edition, zu einer Stellungnahme, in der er explizit auf die gegen ihn geäußerte Kritik eingeht und Missverständnisse klarstellt (vgl. Ellul 1964: xxvii-xxxvi). Die Tatsache, dass Ellul den Einwand, er verträte einen Technikdeterminismus, vehement zurückweist, hat jedoch seine Kritiker seit jeher nicht davon abgehalten, ihn als idealtypischen Vertreter eines solchen zu behandeln. Die Kritik, welche gegen ihn angeführt wurde und wird, ist daher in den meisten Fällen eine solche, die sich gegen das widmet, was man als Technikdeterminismus definiert hat. In der Form wie der Technikdeterminismus definiert wird, als Erklärungsmuster, welchem axiomatisch die Unterscheidung zwischen Technik und Sozialem als eigenständigen ontologischen Kategorien sowie das Postulat einer intrinsischen Eigenlogik der Technik als Motor gesellschaftlichen Wandels zugrunde liegt (vgl. Passoth 2008: 50f.), gilt als widerlegt. Neuere, empirisch ausgerichtete, sozialkonstruktivistische Ansätze untersuchen den sozialen Konstruktionsprozess, in dessen kontingenten Verlauf sich ein bestimmter Interpretationskonsens herausdestilliert, wobei unterschiedlichste Faktoren neben rein technischen Kriterien eine Rolle spielen. Allerdings -und dies ist die These dieser Arbeit -ist die Einordnung Elluls als Vertreter eines Technikdeterminismus nicht haltbar. -Dafür spricht nicht nur die Tatasche, dass Ellul selber, wie bereits erwähnt, technikdeterministische Vorwürfe zurückweist. Forschungsfrage dieser Arbeit ist daher: Ist die Einordnung der Soziologie Elluls, wie sie von ihm in seinem Werk The Technological Society ausgearbeitet wurde, in die Kategorie des Technikdeterminismus haltbar? Sollte sich herausstellen, dass diese Frage negativ beantwortet werden muss, so eröffnet dies die Möglichkeit einer Reinterpretation Elluls und einer erneuten,

The relational databases have shown their limits to the exponential increase in the volume of manipulated and processed data. New NoSQL solutions have been developed to manage big data. These approaches are an interesting way to build no-relational databases that can support large amounts of data. In this work, we use conceptual data modeling (CDM), based on UML class diagrams, to create a logical structure of a NoSQL database, taking account the relationships and constraints that determine how data can be stored and accessible. The NoSQL logical data model obtained is based on the Document-Oriented Model (DOM). to eliminate joins, a total and structured nesting is done on the collections of the document-oriented database. Rules of passage from the CDM to the Logical Oriented-Document Model (LODM) are also proposed in this paper to transform the different types of associations between class. An application example of this NoSQL BDD design method is realised to the case of an organization working in the e-commerce business sector.

In this era of technologies, where due to the advancement in several web technologies and frequent growth of portable devices, and sensors linked over the web are resulting to the huge amount of data. Due to this rapid increase of well-structured, semi-structured and other types of unstructured data called Big Data, traditional database systems are facing several difficulties.Since forty years, traditional databases are the leading model for several data manipulation tasks such as data storing, data retrieving and managing the data. However, because of growing requirements for better scalability and higher performance, other alternative database technologies, namely NOSQL andNewSQL technology have emerged. In order to overcome the challenges faced by traditional database system, there are numerous NOSQL and NEWSQL databases in the industry. It becomes challenging to select appropriate database solution for Big Data Management. This research work will present the comparative analysis and performance evaluation of most popular NOSQL and NEWSQL databases on the basis of several criteria. In this survey paper, there are mainly five sections: first section comprises of basic introduction and background of research in this field. In further sections, there is a brief introduction about adopting nosql and newsql technologies. Finally, there is a literature survey and survey report of this field.

The term Big Data is often used loosely to designate the palette of algorithms, technology and systems employed for collecting data of unprecedented volume and variety, and extracting value from them by massively parallel computation of advanced analytics. The sources of Big Data are many and diverse. Distributed multimedia sensors on the Internet of Things, mobile telecommunication devices and networks, distributed business processes, and Web-based applications are all candidate data providers/generators. As Big Data usage has increased over the years, the various algorithms, technologies, and systems are gradually reaching a level of development and maturity suitable for widespread adoption.

Digital footprints of the consumers are an invaluable resource for the digital advertising industry. First and third-party data collectors track these digital footprints to predict the needs and expectations of consumers based on their online activities and deliver them personalized content and targeted advertising. However, pervasive personal data collection leads to privacy violations. With the aim of understanding data privacy issues in digital advertising, this chapter provides an assessment of the following topics: The current state of personal data collection for commercial purposes, current data privacy regulations, possible scenarios for the future of web tracking and targeted advertising, and the destructive impact of corporate surveillance and commodification of personal information on the right to privacy.

Das Feld von Self-Tracking wird theoretisch abgesteckt und gesellschaftlich kontextualisiert. Entlang aktueller Untersuchungen wird die empirische Nutzung von Self-Tracking-Devices und-Apps durch Jugendliche skizziert, um schließlich mögliche Hindernisse und methodische Ansätze in der medienpädagogischen Jugendarbeit zu benennen. Obwohl Self-Tracking gegenwärtig keine herausragende Bedeutung für jugendliche Mediennutzung zukommt, bündeln sich darin für Jugendliche relevante Fragestellungen.

As designing computationally efficient distributed algorithms is very important for analyzing big data this paper presents the current state-of-the-art research in designing distributed algorithms of big data analytics. More specifically, this papers presents a comprehensive survey on existing distributed algorithms of big data analytics – present working principle of existing algorithms, their advantages, limitations and also compare these algorithms in terms of several features. This paper also presents issues and research challenges that may arise to design an efficient distributed algorithm for big data analytics and proposes some solutions to address such challenges. Our research find that these algorithms support parallel processing and designed based on the MapReduce paradigm of big data for a particular application.

This article explores the dream of the universal library in Gottfried Wilhelm Leibniz’s Theodicy, Jorge Luis Borges’s “The Library of Babel,” and Wim Wenders’s Wings of Desire. Scholars have overlooked the dream of the total library perhaps because this theme appears in works that transcend literary, aesthetic, and philosophical genres. I argue that the dream of the total library morphs from Leibniz’s assured hierarchy of knowledge in which God is at the apex to Borges’s and Wenders’s more anxious post-enlightened epistemic regimes in which knowledge, decentered and leveled, becomes data, or worse, noise. Taken together, their dreams of a total library constitute a central episode in the great romance of the pursuit of encyclopedic knowledge.

One of the main computer characteristics is the possibility to save large amount of data
and different information organized in the most appropriate form in order to find data quick and
easy. In the mediums for data saving it is possible that by using appr
opriate commands the
organized data can be placed and used in different ways, depending on the needs of the user and
the program. However, for the needs of complicated unions data related, rules and methods have
been developed, whereby efficient utilizatio
n is enabled and maintenance of complex unions of
data. 

One of the basic concepts in development of nowadays solutions is the database, without
which it would be
very difficult solve some problems where we have to do with more data, or
solutions that are completed in the management and organization of those data. For this reason a
database is defined as a self
-descriptive collection of integrated rows. The description of data is
known as database catalog
(eng. systcm catalog) or data dictionary (eng. data dictionary or metadata).


This description of Database, where the definition of the data is separate from program
application, is similar to description of the development of modern software, where an internal
definition of an object and a division of an
external definition are provided. The users of an
object only see the external definition and don’t know how the object is defined and how it
works.

An advantage of this description is known as data abstraction (eng. data abstraction), so
we can change t
he internal definition of an object without touching the users of the object, the
security of the external definition remains the same.

On the same way the database is described too, the division of the data structure from the
applied program, as well as t
heir saving within the database.