Kategoria BISAC: Computers >> Data Science - Data Modeling & Design

Big data has more disruptive potential than any information technology developed in the past 40 years. As author Jeffrey Needham points out in this revealing book, big data can provide unprecedented visibility into the operational efficiency of enterprises and agencies.

Disruptive Possibilities provides an historically-informed overview through a wide range of topics, from the evolution of commodity supercomputing and the simplicity of big data technology, to the ways conventional clouds differ from Hadoop analytics clouds. This relentlessly innovative form of computing will...

Learn how to create data models that allow complex data to be analyzed, manipulated, extracted, and reported upon accurately. Data Modeling: A Beginner's Guide teaches you techniques for gathering business requirements and using them to produce conceptual, logical, and physical database designs. You'll get details on Unified Modeling Language (UML), normalization, incorporating business rules, handling temporal data, and analytical database design. The methods presented in this fast-paced tutorial are applicable to any database management system,...

Learn the best practices of dimensional design. Star Schema: The Complete Reference offers in-depth coverage of design principles and their underlying rationales. Organized around design concepts and illustrated with detailed examples, this is a step-by-step guidebook for beginners and a comprehensive resource for experts.

This all-inclusive volume begins with dimensional design fundamentals and shows how they fit into diverse data warehouse architectures, including those of W.H. Inmon and Ralph Kimball. The book...

Introduction to Pattern Recognition: A Matlab Approach is an accompanying manual to Theodoridis/Koutroumbas' Pattern Recognition.

It includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition.

This text is designed for electronic engineering, computer science, computer engineering, biomedical engineering and applied mathematics students taking graduate courses on pattern recognition and machine learning as well as R&D engineers...

Developing High Quality Data Models provides an introduction to the key principles of data modeling. It explains the purpose of data models in both developing an Enterprise Architecture and in supporting Information Quality; common problems in data model development; and how to develop high quality data models, in particular conceptual, integration, and enterprise data models.

The book is organized into four parts. Part 1 provides an overview of data models and data modeling including the basics of data model notation; types and uses of data models; and the place of data...

Data analysis for database design is a subject of great practical value to systems analysts and designers. This classic text has been updated to include chapters on distributed database systems, query optimisation and object-orientation.The SQL content now includes features of SQL92 and SQL 99.

With new databases coming online all the time and the general expansion of the information age, it is increasingly important to ensure that the analysis and model of a database design is accurate and robust. This is an ideal book for helping you to ensure that your database is well designed...

Data Modeling Made Simple will provide the business or IT professional with a practical working knowledge of data modeling concepts and best practices. This book is written in a conversational style that encourages you to read it from start to finish and master these ten objectives:

1. Know when a data model is needed and which type of data model is most effective for each situation
2. Read a data model of any size and complexity with the same confidence as reading a book
3. Build a fully normalized relational data model, as well as an easily navigatable dimensional...

If you're a developer looking to supplement your own data tools and services, this concise ebook covers the most useful sources of public data available today. You'll find useful information on APIs that offer broad coverage, tie their data to the outside world, and are either accessible online or feature downloadable bulk data. You'll also find code and helpful links.

This guide organizes APIs by the subjects they cover--such as websites, people, or places--so you can quickly locate the best resources for augmenting the data you handle in your own service. Categories include:...

R is a powerful tool for statistics and graphics, but getting started with this language can be frustrating. This short, concise book provides beginners with a selection of how-to recipes to solve simple problems with R. Each solution gives you just what you need to know to use R for basic statistics, graphics, and regression.

You'll find recipes on reading data files, creating data frames, computing basic statistics, testing means and correlations, creating a scatter plot, performing simple linear regression, and many more. These solutions were selected from O'Reilly's R...

This practical guide offers a short course on scaling CouchDB to meet the capacity needs of your distributed application. Through a series of scenario-based examples, this book lets you explore several methods for creating a system that can accommodate growth and meet expected demand. In the process, you learn about several tools that can help you with replication, load balancing, clustering, and load testing and monitoring.

• Apply performance tips for tuning your database
• Replicate data, using Futon and CouchDB s RESTful interface
• Distribute CouchDB s workload...

How do you use R to import, manage, visualize, and analyze real-world data? With this short, hands-on tutorial, you learn how to collect online data, massage it into a reasonable form, and work with it using R facilities to interact with web servers, parse HTML and XML, and more. Rather than use canned sample data, you'll plot and analyze current home foreclosure auctions in Philadelphia.

This practical mashup exercise shows you how to access spatial data in several formats locally and over the Web to produce a map of home foreclosures. It's an excellent way to explore how the R...

Create your own natural language training corpus for machine learning. Whether you're working with English, Chinese, or any other natural language, this hands-on book guides you through a proven annotation development cycle--the process of adding metadata to your training corpus to help ML algorithms work more efficiently. You don't need any programming or linguistics experience to get started.

Using detailed examples at every step, you'll learn how the MATTER Annotation Development Process helps you Model, Annotate, Train, Test, Evaluate,...

To help you navigate the large number of new data tools available, this guide describes 60 of the most recent innovations, from NoSQL databases and MapReduce approaches to machine learning and visualization tools. Descriptions are based on first-hand experience with these tools in a production environment.

This handy glossary also includes a chapter of key terms that help define many of these tool categories:

• NoSQL Databases--Document-oriented databases using a key/value interface rather than SQL
• MapReduce--Tools that support distributed computing on...

Until now, design patterns for the MapReduce framework have been scattered among various research papers, blogs, and books. This handy guide brings together a unique collection of valuable MapReduce patterns that will save you time and effort regardless of the domain, language, or development framework you're using.

Each pattern is explained in context, with pitfalls and caveats clearly identified to help you avoid common design mistakes when modeling your big data architecture. This book also provides a complete overview of MapReduce that explains its origins and implementations,...

Whether you re building a social media site or an internal-use enterprise application, this hands-on guide shows you the connection between MongoDB and the business problems it s designed to solve. You ll learn how to apply MongoDB design patterns to several challenging domains, such as ecommerce, content management, and online gaming. Using Python and JavaScript code examples, you ll discover how MongoDB lets you scale your data model while simplifying the development process.

Many businesses launch NoSQL databases without understanding the techniques for using their features most...

Views are virtual tables. That means they should be updatable, just as "real" or base tables are. In fact, view updatability isn t just desirable, it s crucial, for practical reasons as well as theoretical ones. But view updating has always been a controversial topic. Ever since the relational model first appeared, there has been widespread skepticism as to whether (in general) view updating is even possible.

In stark contrast to this conventional wisdom, this book shows how views, just like base tables, can always be updated (so long as the updates don t violate...

Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today.

Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You'll...