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"Data management systems"
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Business modeling and data mining
Business Modeling and Data Mining demonstrates how real world business problems can be formulated so that data mining can answer them. The concepts and techniques presented in this book are the essential building blocks in understanding what models are and how they can be used practically to reveal hidden assumptions and needs, determine problems, discover data, determine costs, and explore the whole domain of the problem. This book articulately explains how to understand both the strategic and tactical aspects of any business problem, identify where the key leverage points are and determine where quantitative techniques of analysis -- such as data mining -- can yield most benefit. It addresses techniques for discovering how to turn colloquial expression and vague descriptions of a business problem first into qualitative models and then into well-defined quantitative models (using data mining) that can then be used to find a solution. The book completes the process by illustrating how these findings from data mining can be turned into strategic or tactical implementations. · Teaches how to discover, construct and refine models that are useful in business situations· Teaches how to design, discover and develop the data necessary for mining · Provides a practical approach to mining data for all business situations· Provides a comprehensive, easy-to-use, fully interactive methodology for building models and mining data· Provides pointers to supplemental online resources, including a downloadable version of the methodology and software tools.
eBook
Advanced Database Systems
This book provides an in-depth study of the advanced concepts and technologies in database systems. It covers topics such as distributed databases, object-oriented databases, data mining, and big data analytics. The book is written for students and professionals in the field of computer science who want to enhance their knowledge and skills in advanced database technologies. This book will provide you with a solid understanding of the latest developments in database systems and their applications.
eBook
Internet-based customer value management : developing customer relationships online
Customer value management is a managerial approach in which customers are perceived as the company?s asset, the value of which may be measured and increased through the organization of processes around customer relationships. This book deals with the topic of managing customer lifetime value on the internet, and more specifically on including the role of the internet in customer value proposition to enhance stakeholder and shareholder value. This book also discusses the possibilities of internet-based customer value management and presents a model describing the process leading to it. Its uniqueness lies in presenting a managerial approach to customer relationships rather than offering just another tool of e-marketing. The author?s approach is not limited by branches or sectors ? differences in customer value management approaches are perceived through a prism of relationships between the company and its customers.
Book
Big data, data mining and machine learning
With big data analytics comes big insights into profitability
Big data is big business. But having the data and the computational power to process it isn't nearly enough to produce meaningful results. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners is a complete resource for technology and marketing executives looking to cut through the hype and produce real results that hit the bottom line. Providing an engaging, thorough overview of the current state of big data analytics and the growing trend toward high performance computing architectures, the book is a detail-driven look into how big data analytics can be leveraged to foster positive change and drive efficiency.
With continued exponential growth in data and ever more competitive markets, businesses must adapt quickly to gain every competitive advantage available. Big data analytics can serve as the linchpin for initiatives that drive business, but only if the underlying technology and analysis is fully understood and appreciated by engaged stakeholders. This book provides a view into the topic that executives, managers, and practitioners require, and includes:
* A complete overview of big data and its notable characteristics
* Details on high performance computing architectures for analytics, massively parallel processing (MPP), and in-memory databases
* Comprehensive coverage of data mining, text analytics, and machine learning algorithms
* A discussion of explanatory and predictive modeling, and how they can be applied to decision-making processes
Big Data, Data Mining, and Machine Learning provides technology and marketing executives with the complete resource that has been notably absent from the veritable libraries of published books on the topic. Take control of your organization's big data analytics to produce real results with a resource that is comprehensive in scope and light on hyperbole.
eBook
High Performance PostgreSQL for Rails: Reliable, Scalable, Maintainable Database Applications
Build faster, more reliable Rails apps by taking the best advanced PostgreSQL and Active Record capabilities, and using them to solve your application scale and growth challenges. Gain the skills needed to comfortably work with multi-terabyte databases, and with complex Active Record, SQL, and specialized Indexes. Develop your skills with PostgreSQL on your laptop, then take them into production, while keeping everything in sync. Make slow queries fast, perform any schema or data migration without errors, use scaling techniques like read/write splitting, partitioning, and sharding, to meet demanding workload requirements from Internet scale consumer apps to enterprise SaaS.Deepen your firsthand knowledge of high-scale PostgreSQL databases and Ruby on Rails applications with dozens of practical and hands-on exercises. Unlock the mysteries surrounding complex Active Record. Make any schema or data migration change confidently, without downtime. Grow your experience with modern and exclusive PostgreSQL features like SQL Merge, Returning, and Exclusion constraints. Put advanced capabilities like Full Text Search and Publish Subscribe mechanisms built into PostgreSQL to work in your Rails apps. Improve the quality of the data in your database, using the advanced and extensible system of types and constraints to reduce and eliminate application bugs. Tackle complex topics like how to improve query performance using specialized indexes. Discover how to effectively use built-in database functions and write your own, administer replication, and make the most of partitioning and foreign data wrappers. Use more than 40 well-supported open source tools to extend and enhance PostgreSQL and Ruby on Rails. Gain invaluable insights into database administration by conducting advanced optimizations - including high-impact database maintenance - all while solving real-world operational challenges. Take your new skills into production today and then take your PostgreSQL and Rails applications to a whole new level of reliability and performance.What You Need:A computer running macOS, Linux, or Windows and WSL2PostgreSQL version 16, installed by package manager, compiled, or running with DockerAn Internet connection
eBook
Principles of Data Fabric
Apply Data Fabric solutions to automate Data Integration, Data Sharing, and Data Protection across disparate data sources using different data management styles. Purchase of the print or Kindle book includes a free PDF eBook
Key Features
Learn to design Data Fabric architecture effectively with your choice of toolBuild and use a Data Fabric solution using DataOps and Data Mesh frameworksFind out how to build Data Integration, Data Governance, and Self-Service analytics architecture
Book Description
Data can be found everywhere, from cloud environments and relational and non-relational databases to data lakes, data warehouses, and data lakehouses. Data management practices can be standardized across the cloud, on-premises, and edge devices with Data Fabric, a powerful architecture that creates a unified view of data. This book will enable you to design a Data Fabric solution by addressing all the key aspects that need to be considered. The book begins by introducing you to Data Fabric architecture, why you need them, and how they relate to other strategic data management frameworks. You’ll then quickly progress to grasping the principles of DataOps, an operational model for Data Fabric architecture. The next set of chapters will show you how to combine Data Fabric with DataOps and Data Mesh and how they work together by making the most out of it. After that, you’ll discover how to design Data Integration, Data Governance, and Self-Service analytics architecture. The book ends with technical architecture to implement distributed data management and regulatory compliance, followed by industry best practices and principles. By the end of this data book, you will have a clear understanding of what Data Fabric is and what the architecture looks like, along with the level of effort that goes into designing a Data Fabric solution.
What you will learn
Understand the core components of Data Fabric solutionsCombine Data Fabric with Data Mesh and DataOps frameworksImplement distributed data management and regulatory compliance using Data FabricManage and enforce Data Governance with active metadata using Data FabricExplore industry best practices for effectively implementing a Data Fabric solution
Who this book is for
If you are a data engineer, data architect, or business analyst who wants to learn all about implementing Data Fabric architecture, then this is the book for you. This book will also benefit senior data professionals such as chief data officers looking to integrate Data Fabric architecture into the broader ecosystem.
eBook