Data Mining

Web Analytics: An Hour a Day

Written by an in-the-trenches practitioner, this step-by-step guide shows you how to implement a successful Web analytics strategy. Web analytics expert Avinash Kaushik, in his thought-provoking style, debunks leading myths and leads you on a path to gaining actionable insights from your analytics efforts. Discover how to move beyond clickstream analysis, why qualitative data should be your focus, and more insights and techniques that will help you develop a customer-centric mindset without sacrificing your company’s bottom line.

Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

Competing on Analytics: The New Science of Winning

You have more information at hand about your business environment than ever before. But are you using it to “out-think” your rivals? If not, you may be missing out on a potent competitive tool.

In Competing on Analytics: The New Science of Winning , Thomas H. Davenport and Jeanne G. Harris argue that the frontier for using data to make decisions has shifted dramatically. Certain high-performing enterprises are now building their competitive strategies around data-driven insights that in turn generate impressive business results. Their secret weapon? Analytics: sophisticated quantitative and statistical analysis and predictive modeling.

Exemplars of analytics are using new tools to identify their most profitable customers and offer them the right price, to accelerate product innovation, to optimize supply chains, and to identify the true drivers of financial performance. A wealth of examples—from organizations as diverse as Amazon, Barclay’s, Capital One, Harrah’s, Procter & Gamble, Wachovia, and the Boston Red Sox—illuminate how to leverage the power of analytics.

High Performance MySQL: Optimization, Backups, Replication, and More

High Performance MySQL is the definitive guide to building fast, reliable systems with MySQL. Written by noted experts with years of real-world experience building very large systems, this book covers every aspect of MySQL performance in detail, and focuses on robustness, security, and data integrity. High Performance MySQL teaches you advanced techniques in depth so you can bring out MySQL's full power. Learn how to design schemas, indexes, queries and advanced MySQL features for maximum performance, and get detailed guidance for tuning your MySQL server, operating system, and hardware to their fullest potential. You'll also learn practical, safe, high-performance ways to scale your applications with replication, load balancing, high availability, and failover. This second edition is completely revised and greatly expanded, with deeper coverage in all areas. Major additions include: Emphasis throughout on both performance and reliability Thorough coverage of storage engines, including in-depth tuning and optimizations for the InnoDB storage engine Effects of new features in MySQL 5.0 and 5.1, including stored procedures, partitioned databases, triggers, and views A detailed discussion on how to build very large, highly scalable systems with MySQL New options for backups and replication Optimization of advanced querying features, such as full-text searches Four new appendices The book also includes chapters on benchmarking, profiling, backups, security, and tools and techniques to help you measure, monitor, and manage your MySQL installations.

Advanced Web Metrics with Google Analytics

Let Web metrics expert Brian Clifton help you maximize your website's potential. In this book you'll discover the information you need to get a true picture of your site's impact and stay competitive using Google Analytics. Featuring implementation techniques not documented elsewhere, this informative guide teaches you how to turn data into actionable information and optimize the user experience of your website for better conversions. You'll learn to:

• Measure your web traffic, its sources and visitor engagements and understand its impact on ROI
• Configure your data collection parameters to track all online marketing channels, Flash events, banners, and more
• Follow best practices for tracking offline activities and learn how to extract, analyze, and integrate the collected data
• Optimize checkout systems, pay-per-click campaigns (including AdWords), SEO, and email marketing efforts
• Discover the benefits of ad version testing and the insight multivariate testing can bring

With a better understanding of your website visitors, you will be able to tailor page content and marketing budgets with laserlike precision for a better return on investment, and ultimately, a better bottom line.

Learning SQL (Learning)

SQL (Structured Query Language) is a standard programming language for generating, manipulating, and retrieving information from a relational database. If you're working with a relational database--whether you're writing applications, performing administrative tasks, or generating reports--you need to know how to interact with your data. Even if you are using a tool that generates SQL for you, such as a reporting tool, there may still be cases where you need to bypass the automatic generation feature and write your own SQL statements.

To help you attain this fundamental SQL knowledge, look to "Learning SQL," an introductory guide to SQL, designed primarily for developers just cutting their teeth on the language.

"Learning SQL" moves you quickly through the basics and then on to some of the more commonly used advanced features. Among the topics discussed:

The history of the computerized database

SQL Data Statements--those used to create, manipulate, and retrieve data stored in your database; example statements include select, update, insert, and delete

SQL Schema Statements--those used to create database objects, such as tables, indexes, and constraints

How data sets can interact with queries

The importance of subqueries

Data conversion and manipulation via SQL's built-in functions

How conditional logic can be used in Data Statements

Best of all, "Learning SQL" talks to you in a real-world manner, discussing various platform differences that you're likely to encounter and offering a series of chapter exercises that walk you through the learning process. Whenever possible, the book sticks to the features included in the ANSI SQL standards. This meansyou'll be able to apply what you learn to any of several different databases; the book covers MySQL, Microsoft SQL Server, and Oracle Database, but the features and syntax should apply just as well (perhaps with some tweaking) to IBM DB2, Sybase Adaptive Server, and PostgreSQL.

Put the power and flexibility of SQL to work. With "Learning SQL" you can master this important skill and know that the SQL statements you write are indeed correct.

The Elements of Statistical Learning

During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book.

This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for ``wide'' data (p bigger than n), including multiple testing and false discovery rates.

Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.

Head First SQL: Your Brain on SQL -- A Learner's Guide (Head First)

Is your data dragging you down? Are your tables all tangled up? Well we've got the tools to teach you just how to wrangle your databases into submission. Using the latest research in neurobiology, cognitive science, and learning theory to craft a multi-sensory SQL learning experience, Head First SQL has a visually rich format designed for the way your brain works, not a text-heavy approach that puts you to sleep.

Maybe you've written some simple SQL queries to interact with databases. But now you want more, you want to really dig into those databases and work with your data. Head First SQL will show you the fundamentals of SQL and how to really take advantage of it. We'll take you on a journey through the language, from basic INSERT statements and SELECT queries to hardcore database manipulation with indices, joins, and transactions. We all know "Data is Power" - but we'll show you how to have "Power over your Data". Expect to have fun, expect to learn, and expect to be querying, normalizing, and joining your data like a pro by the time you're finished reading!

Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)

As with any burgeoning technology that enjoys commercial attention, the use of data mining is surrounded by a great deal of hype. Exaggerated reports tell of secrets that can be uncovered by setting algorithms loose on oceans of data. But there is no magic in machine learning, no hidden power, no alchemy. Instead there is an identifiable body of practical techniques that can extract useful information from raw data. This book describes these techniques and shows how they work.

The book is a major revision of the first edition that appeared in 1999. While the basic core remains the same, it has been updated to reflect the changes that have taken place over five years, and now has nearly double the references. The highlights for the new edition include thirty new technique sections; an enhanced Weka machine learning workbench, which now features an interactive interface; comprehensive information on neural networks; a new section on Bayesian networks; plus much more.

* Algorithmic methods at the heart of successful data miningincluding tried and true techniques as well as leading edge methods
* Performance improvement techniques that work by transforming the input or output
* Downloadable Weka, a collection of machine learning algorithms for data mining tasks, including tools for data pre-processing, classification, regression, clustering, association rules, and visualizationin a new, interactive interface

Like the popular first edition, Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. Inside, you'll learn all you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining-including both tried-and-true techniques of the past and Java-based methods at the leading edge of contemporary research. If you're involved at any level in the work of extracting usable knowledge from large collections of data, this clearly written and effectively illustrated book will prove an invaluable resource. Complementing the authors' instruction, including a fully-revised Chapter 8 and 30 new technique sections, is a fully functional platform-independent Java software s

SQL Cookbook (Cookbooks (O'Reilly))

You know the rudiments of the SQL query language, yet you feel you aren't taking full advantage of SQL's expressive power. You'd like to learn how to do more work with SQL inside the database before pushing data across the network to your applications. You'd like to take your SQL skills to the next level.

Let's face it, SQL is a deceptively simple language to learn, and many database developers never go far beyond the simple statement: SELECT FROM WHERE . But there is "so" much more you can do with the language. In the "SQL Cookbook," experienced SQL developer Anthony Molinaro shares his favorite SQL techniques and features. You'll learn about:

Window functions, arguably the most significant enhancement to SQL in the past decade. If you're not using these, you're missing out

Powerful, database-specific features such as SQL Server's PIVOT and UNPIVOT operators, Oracle's MODEL clause, and PostgreSQL's very useful GENERATE_SERIES function

Pivoting rows into columns, reverse-pivoting columns into rows, using pivoting to facilitate inter-row calculations, and double-pivoting a result set

"Bucketization," and why you should never use that term in Brooklyn.

How to create histograms, summarize data into buckets, perform aggregations over a moving range of values, generate running-totals and subtotals, and other advanced, data warehousing techniques

The technique of "walking a string," which allows you to use SQL to parse through the characters, words, or delimited elements of a string

Written in O'Reilly's popular Problem/Solution/Discussion style, the "SQL Cookbook" is sure to please. Anthony's credo is: "When it comes down to it, we all go to work, weall have bills to pay, and we all want to go home at a reasonable time and enjoy what's still available of our days." The "SQL Cookbook" moves quickly from problem to solution, saving you time each step of the way.

SPSS For Dummies (For Dummies (Computer/Tech))

• SPSS (Statistical Package for the Social Sciences) is a data management and analysis software that allows users to generate solid, decision-making results by performing statistical analysis
• This book provides just the information needed: installing the software, entering data, setting up calculations, and analyzing data
• Covers computing cross tabulation, frequencies, descriptive ratios, means, bivariate and partial correlations, linear regression, and much more
• Explains how to output information into striking charts and graphs
• For ambitious users, also covers how to program SPSS to take their statistical analysis to the next level