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Microsoft SQL Server 2012 with Hadoop
This book will be a step-by-step tutorial, which practically teaches working with big data on SQL Server through sample examples in increasing complexity.Microsoft SQL Server 2012 with Hadoop is specifically targeted at readers who want to cross-pollinate their Hadoop skills with SQL Server 2012 business intelligence and data analytics. A basic understanding of traditional RDBMS technologies and query processing techniques is essential.
Learning Microsoft Azure
If you are a developer interested in building systems for Microsoft Azure, with an understanding of efficient cloud-based application development, then this is the book for you.
Learning Hadoop 2
If you are a system or application developer interested in learning how to solve practical problems using the Hadoop framework, then this book is ideal for you. You are expected to be familiar with the Unix/Linux command-line interface and have some experience with the Java programming language. Familiarity with Hadoop would be a plus.
Inteligensi Bisnis SQL Server 2014
Banyak perusahaan yang sudah menerapkan Inteligensi Bisnis, yaitu menggunakan informasi yang telah tersedia di perusahaannya untuk membantu pengambil keputusan membuat keputusan yang lebih baik, tepat, dan cepat. Salah satu penyedia teknologi Inteligensi Bisnis adalah Microsoft SQL Server 2014. Pembahasan dalam buku mencakup: - Pengantar Inteligensi Bisnis - Integration Services - ETL dengan Integration Services - Reporting Services dengan Report Builder - Reporting Services dengan Data Tools - Analysis Services Model Multidimensional - Analysis Services Model Tabular - Data Mining - Data Mining Lanjutan
Mastering SQL Server 2014 Data Mining
If you are a developer who is working on data mining for large companies and would like to enhance your knowledge of SQL Server Data Mining Suite, this book is for you. Whether you are brand new to data mining or are a seasoned expert, you will be able to master the skills needed to build a data mining solution.
New Paradigm in Decision Science and Management
This book discusses an emerging area in computer science, IT and management, i.e., decision sciences and management. It includes studies that employ various computing techniques like machine learning to generate insights from huge amounts of available data; and which explore decision-making for cross-platforms that contain heterogeneous data associated with complex assets; leadership; and team coordination. It also reveals the advantages of using decision sciences with management-oriented problems. The book includes a selection of the best papers presented at the International Conference on Decision Science and Management 2018 (ICDSM 2018), held at the Interscience Institute of Management and Technology (IIMT), Bhubaneswar, India.
Cognitive Informatics and Soft Computing
The book presents new approaches and methods for solving real-world problems. It offers, in particular, exploratory research that describes novel approaches in the fields of Cognitive Informatics, Cognitive Computing, Computational Intelligence, Advanced Computing, Hybrid Intelligent Models and Applications. New algorithms and methods in a variety of fields are also presented, together with solution-based approaches. The topics addressed include various theoretical aspects and applications of Computer Science, Artificial Intelligence, Cybernetics, Automation Control Theory and Software Engineering.
Advanced Data Mining Tools and Methods for Social Computing
Advanced Data Mining Tools and Methods for Social Computing explores advances in the latest data mining tools, methods, algorithms and the architectures being developed specifically for social computing and social network analysis. The book reviews major emerging trends in technology that are supporting current advancements in social networks, including data mining techniques and tools. It also aims to highlight the advancement of conventional approaches in the field of social networking. Chapter coverage includes reviews of novel techniques and state-of-the-art advances in the area of data mining, machine learning, soft computing techniques, and their applications in the field of social network analysis. - Provides insights into the latest research trends in social network analysis - Covers a broad range of data mining tools and methods for social computing and analysis - Includes practical examples and case studies across a range of tools and methods - Features coding examples and supplementary data sets in every chapter
