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"Data warehouse diimplementasikan di bank XYZ pada tahun 1999. Sejalan dengan perkembangan waktu, kebutuhan user di bank XYZ semakin meningkat. Peningkatan kebutuhan user diakibatkan oleh perkembangan bisnis dari bank XYZ itu sendiri. Sebagian peningkatan kebutuhan ini masih bisa diakomodasi oleh sistem data warehouse yang ada sekarang, dan sebagian lainnya user melakukan penyesuaian secara manual dengan bantuan spreadsheet untuk memenuhi kebutuhan pelaporan untuk manajemen. Berangkat dari kondisi ini, dalam Proyek Akhir ini dilakukan pengkajian ulang terhadap system data warehouse di bank XYZ, dengan melakukan perancangan ulang terhadap sistem data warehouse yang lama dan menggali kembali kebutuhan-kebutuhan user secara khusus. Sistem data warehouse yang baru menggunakan database berbasis Oracle 9i dengan sistem operasi Unix. Sistem data warehouse tersebut dapat menghasilkan multi dimensional reports dan sesuai dengan kebutuhan user.

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A data warehouse system was implemented at Bank XYZ in 1999. As time goes by, user requirement grows quickly at Bank XYZ. The growth of the user requirement is a consequence of the growth of Bank XYZ's business itself. A part of the user requirement can be accommodated by the existing data warehouse and some other part of it can be adjusted manually using a spreadsheet for producing a final report for the management board. Because of this condition, this final project has developed a new data warehouse system for Bank XYZ. The old data warehouse system is redesign to take into account and the specific user requirement. The new data warehouse system runs under Oracle 9i database and Unix operating system. It can produce multi dimensional reports that comply with the user requirement."

"CD-ROM contains: Tutorials to familiarize yourself with all major processes."

"This book constitutes the refereed proceedings of the 14th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2012 held in Vienna, Austria, in September 2012. The 36 revised full papers presented were carefully reviewed and selected from 99 submissions. The papers are organized in topical sections on data warehouse design methodologies, ETL methodologies and tools, multidimensional data processing and management, data warehouse and OLAP extensions, data warehouse performance and optimization, data mining and knowledge discovery techniques, data mining and knowledge discovery applications, pattern mining, data stream mining, data warehouse confidentiality and security, and distributed paradigms and algorithms."

"Big data analytics will assist managers in providing an overview of the drivers for introducing big data technology into the organization and for understanding the types of business problems best suited to big data analytics solutions, understanding the value drivers and benefits, strategic planning, developing a pilot, and eventually planning to integrate back into production within the enterprise."

"Data warehousing in the age of the big data will help you and your organization make the most of unstructured data with your existing data warehouse.As big data continues to revolutionize how we use data, it doesn't have to create more confusion. Expert author Krish Krishnan helps you make sense of how big data fits into the world of data warehousing in clear and concise detail. The book is presented in three distinct parts. Part 1 discusses big data, its technologies and use cases from early adopters. Part 2 addresses data warehousing, its shortcomings, and new architecture options, workloads, and integration techniques for Big Data and the data warehouse. Part 3 deals with data governance, data visualization, information life-cycle management, data scientists, and implementing a big data–ready data warehouse. Extensive appendixes include case studies from vendor implementations and a special segment on how we can build a healthcare information factory."