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Designing Data-Intensive Applications: The Big Ideas Behind Relia...
by Martin Kleppmann

Language

English

Pages

624

Publication Date

March 16, 2017

Product Description
Customer Reviews
<div><p>Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?</p><p>In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.</p><ul><li>Peer under the hood of the systems you already use, and learn how to use and operate them more effectively</li><li>Make informed decisions by identifying the strengths and weaknesses of different tools</li><li>Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity</li><li>Understand the distributed systems research upon which modern databases are built</li><li>Peek behind the scenes of major online services, and learn from their architectures</li></ul></div>
Data-Driven Law: Data Analytics and the New Legal Services (Data ...
by Auerbach Publications

Language

English

Pages

227

Publication Date

July 16, 2018

Product Description
Customer Reviews
For increasingly data-savvy clients, lawyers can no longer give "it depends" answers rooted in anecdata. Clients insist that their lawyers justify their reasoning, and with more than a limited set of war stories. The considered judgment of an experienced lawyer is unquestionably valuable. However, on balance, clients would rather have the considered judgment of an experienced lawyer <I>informed by the most relevant information required to answer their questions</I>. <br /><P></P><B><br /><P>Data-Driven Law: Data Analytics and the New Legal Services</B> helps legal professionals meet the challenges posed by a data-driven approach to delivering legal services. Its chapters are written by leading experts who cover such topics as: </P><br /><UL><br /><LI>Mining legal data</LI><br /><LI>Computational law</LI><br /><LI>Uncovering bias through the use of Big Data</LI><br /><LI>Quantifying the quality of legal services</LI><br /><LI>Data mining and decision-making</LI><br /><LI>Contract analytics and contract standards</LI></UL><br /><P>In addition to providing clients with data-based insight, legal firms can track a matter with data from beginning to end, from the marketing spend through to the type of matter, hours spent, billed, and collected, including metrics on profitability and success. Firms can organize and collect documents after a matter and even automate them for reuse. Data on marketing related to a matter can be an amazing source of insight about which practice areas are most profitable.</P><br /><P></P><br /><P>Data-driven decision-making requires firms to think differently about their workflow. Most firms warehouse their files, never to be seen again after the matter closes. Running a data-driven firm requires lawyers and their teams to treat information <I>about </I>the work as part of the service, and to collect, standardize, and analyze matter data from cradle to grave. More than anything, using data in a law practice requires a different mindset about the value of this information. This book helps legal professionals to develop this data-driven mindset.</P>
Everybody Lies: Big Data, New Data, and What the Internet Can Tel...
by Seth Stephens-Davidowitz

Language

English

Pages

357

Publication Date

May 09, 2017

Product Description
Customer Reviews
<p>Foreword by Steven Pinker</p><p>Blending the informed analysis of <em>The Signal and the Noise</em> with the instructive iconoclasm of <em>Think Like a Freak</em>, a fascinating, illuminating, and witty look at what the vast amounts of information now instantly available to us reveals about ourselves and our world—provided we ask the right questions.</p><p>By the end of an average day in the early twenty-first century, human beings searching the internet will amass eight trillion gigabytes of data. This staggering amount of information—unprecedented in history—can tell us a great deal about who we are—the fears, desires, and behaviors that drive us, and the conscious and unconscious decisions we make. From the profound to the mundane, we can gain astonishing knowledge about the human psyche that less than twenty years ago, seemed unfathomable. </p><p><em>Everybody Lies</em> offers fascinating, surprising, and sometimes laugh-out-loud insights into everything from economics to ethics to sports to race to sex, gender and more, all drawn from the world of big data. What percentage of white voters didn’t vote for Barack Obama because he’s black? Does where you go to school effect how successful you are in life? Do parents secretly favor boy children over girls? Do violent films affect the crime rate? Can you beat the stock market? How regularly do we lie about our sex lives and who’s more self-conscious about sex, men or women? </p><p>Investigating these questions and a host of others, Seth Stephens-Davidowitz offers revelations that can help us understand ourselves and our lives better. Drawing on studies and experiments on how we really live and think, he demonstrates in fascinating and often funny ways the extent to which all the world is indeed a lab. With conclusions ranging from strange-but-true to thought-provoking to disturbing, he explores the power of this digital truth serum and its deeper potential—revealing biases deeply embedded within us, information we can use to change our culture, and the questions we’re afraid to ask that might be essential to our health—both emotional and physical. All of us are touched by big data everyday, and its influence is multiplying. <em>Everybody Lies</em> challenges us to think differently about how we see it and the world.</p>
SQL: Programming for Complete Beginners, Step-By-Step Illustrated...
by William B. Skates

Language

English

Pages

46

Publication Date

August 08, 2018

Product Description
Customer Reviews
<h2><b>Do you struggle with learning the complicated jargon in SQL?</b></h2><br /><h2><b>Do you want to learn SQL with ease?</b></h2><br /><h2><u>You have come to the right place! </u></h2><br /><h3>In This Book You Will Learn:</h3><ul><br /><li><b>The fundamentals of SQL.</b></li><br /> <li>The SQL Data Types.</li><br /> <li><b>How to use SQL constraints.</b></li><br /> <li><b>Data Query Statements.</b></li><br /> <li>Data Manipulation Statements.</li><br /> <li><b>The SQL Syntax.</b></li><br /> <li>How to easily manage databases.</li><br /></ul><p>Do you feel overwhelmed by the complicated jargon and tech stuff that comes with SQL?<br /> If so, this is the book you've been looking for. Each of the various commands and data types are explained thoroughly in an easy to understand way. In addition to that, every SQL statement has an example shown right after it to make the process of learning SQL as simple as possible. This book is not only to be used by beginners but also intermediates as a referencing tool when needed. </p><br /><h2><u>Become an Expert in 7 Chapters</u></h2><br /><p>You will learn:</p><br /><li><b>The basics of SQL - Chapter 1: Overview of SQL.</b></li><br /><li>The core fundamentals of SQL programming - Chapter 2: Fundamentsals of SQL</li><br /><li><b>What are databases - Chapter 3: Understanding databses.</b></li><br /><li>How to retrieve data - Chapter 4: SQL Syntax.</li><br /><li><b>How to use all data types in SQL - Chapter 5: Data Types.</b></li><br /><li>How to use the various SQL statements - Chapter 6: SQL Statements.</li><br /> <li><b>How to apply SQL constraints - Chapter 7: Constraints in SQL.</b></li><br /><br /><h2>Want To Learn More?</h2><br /><h3>Scroll to the top of the page and click the <b>BUY</b> button</h3><br /> <h3>Get your copy today. And get a <b>FREE</b> Bonus Inside</h3> <br />
Blockchain Basics: A Non-Technical Introduction in 25 Steps
by Daniel Drescher

Language

English

Pages

255

Publication Date

March 14, 2017

Product Description
Customer Reviews
<p>In 25 concise steps, you will learn the basics of blockchain technology. No mathematical formulas, program code, or computer science jargon are used. No previous knowledge in computer science, mathematics, programming, or cryptography is required. Terminology is explained through pictures, analogies, and metaphors.</p><p>This book bridges the gap that exists between purely technical books about the blockchain and purely business-focused books. It does so by explaining both the technical concepts that make up the blockchain and their role in business-relevant applications.</p><p></p><p><b>What You'll Learn</b></p><ul><li>What the blockchain is<br /></li><li>Why it is needed and what problem it solves<br /></li><li>Why there is so much excitement about the blockchain and its potential<br /></li><li>Major components and their purpose<br /></li><li>How various components of the blockchain work and interact<br /></li><li>Limitations, why they exist, and what has been done to overcome them<br /></li><li>Major application scenarios</li></ul><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p><b>Who This Book Is For</b></p><p> </p><p>Everyone who wants to get a general idea of what blockchain technology is, how it works, and how it will potentially change the financial system as we know it</p><p><br /></p>
Practical Statistics for Data Scientists: 50 Essential Concepts
by , Andrew Bruce

Language

English

Pages

318

Publication Date

May 10, 2017

Product Description
Customer Reviews
<div><p>Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.</p><p>Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.</p><p>With this book, you’ll learn:</p><ul><li>Why exploratory data analysis is a key preliminary step in data science</li><li>How random sampling can reduce bias and yield a higher quality dataset, even with big data</li><li>How the principles of experimental design yield definitive answers to questions</li><li>How to use regression to estimate outcomes and detect anomalies</li><li>Key classification techniques for predicting which categories a record belongs to</li><li>Statistical machine learning methods that “learn” from data</li><li>Unsupervised learning methods for extracting meaning from unlabeled data</li></ul></div>
Data Science for Business: What You Need to Know about Data Minin...
by , Tom Fawcett

Language

English

Pages

414

Publication Date

July 27, 2013

Product Description
Customer Reviews
<div><p>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.</p><p>Based on an MBA course Provost has taught at New York University over the past ten years, <i>Data Science for Business</i> provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.</p><ul><li>Understand how data science fits in your organization—and how you can use it for competitive advantage</li><li>Treat data as a business asset that requires careful investment if you’re to gain real value</li><li>Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way</li><li>Learn general concepts for actually extracting knowledge from data</li><li>Apply data science principles when interviewing data science job candidates</li></ul></div>
SQL in 10 Minutes, Sams Teach Yourself: Sams Teac Your SQL 10 Min...
by Ben Forta

Language

English

Pages

287

Publication Date

October 25, 2012

Product Description
Customer Reviews
Sams Teach Yourself SQL in 10 Minutes, Fourth Edition New full-color code examples help you see how SQL statements are structured Whether you're an application developer, database administrator, web application designer, mobile app developer, or Microsoft Office users, a good working knowledge of SQL is an important part of interacting with databases. And Sams Teach Yourself SQL in 10 Minutes offers the straightforward, practical answers you need to help you do your job. Expert trainer and popular author Ben Forta teaches you just the parts of SQL you need to know–starting with simple data retrieval and quickly going on to more complex topics including the use of joins, subqueries, stored procedures, cursors, triggers, and table constraints. You'll learn methodically, systematically, and simply–in 22 short, quick lessons that will each take only 10 minutes or less to complete. With the Fourth Edition of this worldwide bestseller, the book has been thoroughly updated, expanded, and improved. Lessons now cover the latest versions of IBM DB2, Microsoft Access, Microsoft SQL Server, MySQL, Oracle, PostgreSQL, SQLite, MariaDB, and Apache Open Office Base. And new full-color SQL code listings help the beginner clearly see the elements and structure of the language. 10 minutes is all you need to learn how to... Use the major SQL statements Construct complex SQL statements using multiple clauses and operators Retrieve, sort, and format database contents Pinpoint the data you need using a variety of filtering techniques Use aggregate functions to summarize data Join two or more related tables Insert, update, and delete data Create and alter database tables Work with views, stored procedures, and more Table of Contents 1 Understanding SQL 2 Retrieving Data 3 Sorting Retrieved Data 4 Filtering Data 5 Advanced Data Filtering 6 Using Wildcard Filtering 7 Creating Calculated Fields 8 Using Data Manipulation Functions 9 Summarizing Data 10 Grouping Data 11 Working with Subqueries 12 Joining Tables 13 Creating Advanced Joins 14 Combining Queries 15 Inserting Data 16 Updating and Deleting Data 17 Creating and Manipulating Tables 18 Using Views 19 Working with Stored Procedures 20 Managing Transaction Processing 21 Using Cursors 22 Understanding Advanced SQL Features Appendix A: Sample Table Scripts Appendix B: Working in Popular Applications Appendix C : SQL Statement Syntax Appendix D: Using SQL Datatypes Appendix E: SQL Reserved Words
Microsoft Excel Data Analysis and Business Modeling
by Wayne Winston

Language

English

Pages

863

Publication Date

November 29, 2016

Product Description
Customer Reviews
<B> <I> <P style="MARGIN: 0px">This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book.</P> <P style="MARGIN: 0px"> </I> </B> </P> <P style="MARGIN: 0px">Master business modeling and analysis techniques with Microsoft Excel 2016, and transform data into bottom-line results. Written by award-winning educator Wayne Winston, this hands on, scenario-focused guide helps you use Excel’s newest tools to ask the right questions and get accurate, actionable answers. This edition adds 150+ new problems with solutions, plus a chapter of basic spreadsheet models to make sure you’re fully up to speed.</P> <P style="MARGIN: 0px"> <BR> </P> <P style="MARGIN: 0px"> <B>Solve real business problems with Excel–and build your competitive advantage</B> </P> <UL> <LI>Quickly transition from Excel basics to sophisticated analytics</LI> <LI>Summarize data by using PivotTables and Descriptive Statistics</LI> <LI>Use Excel trend curves, multiple regression, and exponential smoothing</LI> <LI>Master advanced functions such as OFFSET and INDIRECT</LI> <LI>Delve into key financial, statistical, and time functions</LI> <LI>Leverage the new charts in Excel 2016 (including box and whisker and waterfall charts)</LI> <LI>Make charts more effective by using Power View</LI> <LI>Tame complex optimizations by using Excel Solver</LI> <LI>Run Monte Carlo simulations on stock prices and bidding models</LI> <LI>Work with the AGGREGATE function and table slicers</LI> <LI>Create PivotTables from data in different worksheets or workbooks</LI> <LI>Learn about basic probability and Bayes’ Theorem</LI> <LI>Automate repetitive tasks by using macros</LI> </UL>
Numsense! Data Science for the Layman: No Math Added
by , Kenneth Soo

Language

English

Pages

147

Publication Date

February 03, 2017

Product Description
Customer Reviews
<b> Used in Stanford's CS102 Big Data course.</b><br /><br />Want to get started on data science?<br />Our promise: no math added.<br /><br />This book has been written in layman's terms as a gentle introduction to data science and its algorithms. Each algorithm has its own dedicated chapter that explains how it works, and shows an example of a real-world application. To help you grasp key concepts, we stick to intuitive explanations and visuals.<br /><br />Popular concepts covered include:<br /><br />- A/B Testing<br />- Anomaly Detection<br />- Association Rules<br />- Clustering<br />- Decision Trees and Random Forests<br />- Regression Analysis<br />- Social Network Analysis<br />- Neural Networks<br /><br />Features:<br /><br />- Intuitive explanations and visuals<br />- Real-world applications to illustrate each algorithm<br />- Point summaries at the end of each chapter<br />- Reference sheets comparing the pros and cons of algorithms<br />- Glossary list of commonly-used terms<br /><br />With this book, we hope to give you a practical understanding of data science, so that you, too, can leverage its strengths in making better decisions.

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Enter the Kind Reader Monthly Drawing

Kind Reader Monthly Drawing (March 2017)

Congratulations to February 2017's winner Henry H. of New York, USA.

There's a daily limit of 3 free e-books that can be downloaded at KindReader.com