What Every Woman Should Know About Sharia Law, Before It's Too late! is an eye-opening expose of the brutal mistreatment of women and children under Islamic sharia law.Women (and males) across the USA will be stunned to learn that the Quran, the Holy Book of Islam, counsels men to beat their wives to keep them obedient. And that's just the tip of the iceberg.Islamic men, under sharia law can beat, or butcher the female members of their families, up to and including murdering them for disobedience. This is known as 'honor killings', a misnomer if there ever was one.With the threat of punishment for displeasing the men in their lives, women and girls may be , beaten, burned by fire or acid, have an extremity or their nose cut off, even be burned or buried alive with NO repercussions to the male involved.Because male-female relationships in the Islamic world are so strict, rape is commonplace in Islamic countries, and usually unpunished. Girls are often forced to marry their rapist or go to jail themselves.Women in Western societies need to realize that they are being targeted for recruitment to Islam, and why. This book explains why this recruitment has been so successful.Some of the topics covered in What Every Woman Should Know About Sharia Law, Before It's Too Late! are:• the Cinderella Complex• the Mystique of the Sheik• sharia law in the USA• Islamic goals for world Domination• taqiyya and kitman• honor killings• polygamy• child brides• bacha• female genital mutilation• and a host of other important topics.This is a book that every woman should read and then share with every woman she knows and loves.
This is a book that every woman should read and then share with every woman she knows and loves.
The best-selling author of Big Data is back, this time with a unique and in-depth insight into how specific companies use big data. Big data is on the tip of everyone's tongue. Everyone understands its power and importance, but many fail to grasp the actionable steps and resources required to utilise it effectively. This book fills the knowledge gap by showing how major companies are using big data every day, from an up-close, on-the-ground perspective. From technology, media and retail, to sport teams, government agencies and financial institutions, learn the actual strategies and processes being used to learn about customers, improve manufacturing, spur innovation, improve safety and so much more. Organised for easy dip-in navigation, each chapter follows the same structure to give you the information you need quickly. For each company profiled, learn what data was used, what problem it solved and the processes put it place to make it practical, as well as the technical details, challenges and lessons learned from each unique scenario. Learn how predictive analytics helps Amazon, Target, John Deere and Apple understand their customers Discover how big data is behind the success of Walmart, LinkedIn, Microsoft and more Learn how big data is changing medicine, law enforcement, hospitality, fashion, science and banking Develop your own big data strategy by accessing additional reading materials at the end of each chapter
In this book you find out succinctly how leading companies are getting real value from Big Data – highly recommended read!" —Arthur Lee, Vice President of Qlik Analytics at Qlik
Big Data in Banking: With Applications in Finance, Investments, Wealth & Asset Management gives you a deeper understanding of the economics and the technology behind big data applied within the world of Finance, Investments, Wealth and Asset Management, the theories behind it, as well as potential future uses. This book assists you to understand all the buzz and excitement around these innovative technologies. Part I introduces the background of Big Data in non-technical terms, and complements it with general applications within a company (e.g. Human Resources). Part II focuses on the technology and makes comparisons to High Frequency Trading and Trading Strategy development, Data Mining and Risk Management issues and opportunities. Part III covers Client Behaviour, Client Acquisition and retention strategies, as well as Robo Advisors and Investment Processes. Part IV, zooms in on Intellectual Property and Transfer Pricing. Mention is also made of the tension between Ethics, Privacy, Transparency and Trust. It Includes cutting edge proposals to create a Big Data Strategy, how to deal with Applications (build vs. buy). This part concludes by discussing potential future uses of Big Data, Digitization and Data Analytics. A small appendix with basic statistics is provided for people that need more information about this area.
Clear and concise, this accessible guide consolidates a wealth of information into a non-technical overview of the issues and opportunities Big Data brings to the banking industry.
Big Data Imperatives, focuses on resolving the key questions on everyone's mind: Which data matters? Do you have enough data volume to justify the usage? How you want to process this amount of data? How long do you really need to keep it active for your analysis, marketing, and BI applications? Big data is emerging from the realm of one-off projects to mainstream business adoption; however, the real value of big data is not in the overwhelming size of it, but more in its effective use. Big Data Imperatives describes the complementary nature of traditional data warehouses and big-data analytics platforms and how they feed each other. This book aims to bring the big data and analytics realms together with a greater focus on architectures that leverage the scale and power of big data and the ability to integrate and apply analytics principles to data which earlier was not accessible. This book can also be used as a handbook for practitioners; helping them on methodology,technical architecture, analytics techniques and best practices. At the same time, this book intends to hold the interest of those new to big data and analytics by giving them a deep insight into the realm of big data.
At the same time, this book intends to hold the interest of those new to big data and analytics by giving them a deep insight into the realm of big data.
This book provides a comprehensive summary of the latest academic research on the important topic of too-big-to-fail (TBTF) in banking. It explains TBTF from various perspectives including the range of regulatory measures proposed to counter TBTF, most notably the globally accepted regulation of global-systemically important banks (G-SIBs) and its main tool of capital surcharges. The empirical analysis quantifies the shareholder value of the G-SIB attribution by using quarterly observations from more than 750 global banks between Q2 2008 and Q3 2015. The main finding is that G-SIBs are confronted with a substantial relative valuation discount compared to non-G-SIBs. From the end of 2011 until the end of 2015, a stable discount of 0.6x–0.8x price-to-tangible common equity (P/TCE) is statistically highly significant. The results suggest that the G-SIB designation effect, which positively impacts G-SIBs’ share prices because of funding benefits from IGGs, is dominated by the regulatory G-SIB burden effect, which negatively impacts G-SIBs’ share prices because of lower profitability due to capital surcharges and other regulatory requirements placed on G-SIBs. The findings re-open the debate about whether breaking up G-SIBs would unlock shareholder value and whether G-SIBs are regulated efficiently.
11.4.1 Database Requirements This empirical study requires two types of micro data for banks: 1. Market data is necessary for share prices, i.e., for the P in the dependent variable. 2. Fundamental data, in particular balance sheet and ...
This handbook brings together a variety of approaches to the uses of big data in multiple fields, primarily science, medicine, and business. This single resource features contributions from researchers around the world from a variety of fields, where they share their findings and experience. This book is intended to help spur further innovation in big data. The research is presented in a way that allows readers, regardless of their field of study, to learn from how applications have proven successful and how similar applications could be used in their own field. Contributions stem from researchers in fields such as physics, biology, energy, healthcare, and business. The contributors also discuss important topics such as fraud detection, privacy implications, legal perspectives, and ethical handling of big data.
Big Data alchemy: How can banks maximize the value of their customer data? Cap Gemini Consulting. Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4), ...
Agile is a set of values, principles, techniques, and frameworks for the adaptable, incremental, and efficient delivery of work. Big Data is a rapidly growing field that encompasses crucial aspects of data such as its volume, velocity, variety, and veracity. This book outlines a strategic approach to Big Data that will render a business Agile. It discusses the important competencies required to streamline and focus on the analytics and presents a roadmap for implementing such analytics in business.
Although A-Bank is a hypothetical bank described here to demonstrate the application of BDFAB, a comparison with and a ... The staff are eager to capitalize on the advanced technologies of Big Data to obtain and build on corresponding ...
Analisis Big Data sangat diperlukan bagi masyarakat dalam perkembangan zaman saat ini dikarenakan big data memberikan kemudahan dan kecepatan akses pada aliran data transaksi. Dengan menggunakan big data, akuntan dalam suatu organisasi dapat mengakses informasi transaksi dengan lebih cepat dan dapat bekerja dalam transaksi berskala besar.
Contoh Kasus Big Data Dalam Industri BANK BRI Bank BRI adalah salah satu bank milik pemerintah terbesar di Indonesia. Bank BRI hadir untuk memberikan pelayanan yang terbaik kepada Masyarakat Indonesia, menjangkau dari yang tak ...
With the proliferation of devices connected to the internet and connected to each other, the volume of data collected, stored, and processed is increasing every day, which brings new challenges in terms of information security. As big data expands with the help of public clouds, traditional security solutions tailored to private computing infrastructures and confined to a well-defined security perimeter, such as firewalls and demilitarized zones (DMZs), are no longer effective. New security functions are required to work over the heterogenous composition of diverse hardware, operating systems, and network domains. Security, Privacy, and Forensics Issues in Big Data is an essential research book that examines recent advancements in big data and the impact that these advancements have on information security and privacy measures needed for these networks. Highlighting a range of topics including cryptography, data analytics, and threat detection, this is an excellent reference source for students, software developers and engineers, security analysts, IT consultants, academicians, researchers, and professionals.
Different big data technologies are introduced in many areas of banking right from mobile banking, revealing the signs of fraudulent happenings in internet banking, to the management of cash. These technologies contribute to a higher ...
