This collaborative book coordinated by the European Journalism Centre & the Open Knowledge Foundation aims to answer questions like Where can I find data? How can I request data? What tools can I use? How can I find stories in data? How can I make data journalism sustainable? It had a very successful start at the Mozilla Festival in London in November 2011 with fifty contributors including data journalists & professors from the New York Times Financial Times Guardian Chicago Tribune Medill School of Journalism & Cronkite School of Journalism Additional contributors now include leading developers analysts FOI experts & other practitioners from places like the BBC City University London Scraperwiki Zeit Online & many others The project has received coverage in the New York Times Liberation Tech Crunch World Editors Forum & other major publications ...

Data Mining Concepts & Techniques provides the concepts & techniques in processing gathered data or information which will be used in various applications Specifically it explains data mining & the tools used in discovering knowledge from the collected data This book is referred as the knowledge discovery from data (KDD) It focuses on the feasibility usefulness effectiveness & scalability of techniques of large data sets After describing data mining this edition explains the methods of knowing preprocessing processing & warehousing data It then presents information about data warehouses online analytical processing (OLAP) & data cube technology Then the methods involved in mining frequent patterns associations & correlations for large data sets are described The book details the methods for data classification & introduces the concepts & methods for data clustering The remaining chapters discuss the outlier detection & the trends applications & research frontiers in data mining This book is intended for Computer Science students application developers business professionals & researchers who seek information on data mining ...

Data Science & Big Data Analytics is about harnessing the power of data for new insights The book covers the breadth of activities & methods & tools that Data Scientists use 432 pages ...

Written by renowned data science experts Foster Provost & Tom Fawcett Data Science for Business introduces the fundamental principles of data science & walks you through the data-analytic thinking necessary for extracting useful knowledge & 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 not only learn how to improve communication between business stakeholders & data scientists but also how participate intelligently in your company's data science projects You'll also discover how to think data-analytically & fully appreciate how data science methods can support business decision-making Understand how data science fits in your organization
- & how you can use it for competitive advantage Treat data as a business asset that requires careful investment if you're to gain real value Approach business problems data-analytically using the data-mining process to gather good data in the most appropriate way Learn general concepts for actually extracting knowledge from data Apply data science principles when interviewing data science job candidates
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This is a first-principles-based practical introduction to the fundamentals of data science aimed at the mathematically-comfortable reader with some programming skills The book covers The important parts of Python to know The important parts of Math Probability Statistics to know The basics of data science How commonly-used data science techniques work (learning by implementing them) What is Map-Reduce & how to do it in Python Other applications such as NLP Network Analysis & more ...

Now in its second edition DS Malik brings his proven approach toC programming to the CS2 course Clearly written with the student in mind this text focuses on Data Structures &

Includes:: advanced topics in C such as Linked Lists & the Standard Template Library (STL) The text features abundant visual diagrams examples & extended Programming Examples all of which serve to illuminate difficult concepts Complete programming code & clear display of syntax explanation & example are used throughout the text & each chapter concludes with a robust exercise set

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Voted one of the "six best books for data geeks" by The Financial Times Read the review here Lecturers request your electronic inspection copy Never has it been more essential to work in the world of data Scholars & students need to be able to analyze design & curate information into useful tools of communication insight & understanding This book is the starting point in learning the process & skills of data visualization teaching the concepts & skills of how to present data & inspiring effective visual design Benefits of this book A flexible step-by-step journey that equips you to achieve great data visualization A curated collection of classic & contemporary examples giving illustrations of good & bad practice Examples on every page to give creative inspiration Illustrations of good & bad practice show you how to critically evaluate & improve your own work Advice & experience from the best designers in the field Loads of online practical help checklists case studies & exercises make this the most comprehensive text available ...

Learn how to turn raw data into rich interactive web visualizations with the powerful combination of Python & Java Script With this hands-on guide author Kyran Dale teaches you how build a basic dataviz toolchain with best-of-breed Python & Java Script libraries-including Scrapy Matplotlib Pandas Flask & D3-for crafting engaging browser-based visualizations As a working example throughout the book Dale walks you through transforming Wikipedia's table-based list of Nobel Prize winners into an interactive visualization You'll examine steps along the entire toolchain from scraping cleaning exploring & delivering data to building the visualization with Java Script's D3 library If you're ready to create your own web-based data visualizations-and know either Python or Java Script- this is the book for you Learn how to manipulate data with Python Understand the commonalities between Python & Java Script Extract information from websites by using Python's web-scraping tools Beautiful Soup & Scrapy Clean & explore data with Python's Pandas Matplotlib & Numpy libraries Serve data & create RESTful web APIs with Python's Flask framework Create engaging interactive web visualizations with Java Script's D3 library ...

How do you take your data analysis skills beyond Excel to the next level? By learning just enough Python to get stuff done This hands-on guide shows non-programmers like you how to process information that's initially too messy or difficult to access You don't need to know a thing about the Python programming language to get started Through various step-by-step exercises you'll learn how to acquire clean analyze & present data efficiently You'll also discover how to automate your data process schedule file- editing & clean-up tasks process larger datasets & create compelling stories with data you obtain Quickly learn basic Python syntax data types & language concepts Work with both machine-readable & human-consumable data Scrape websites & APIs to find a bounty of useful information Clean & format data to eliminate duplicates & errors in your datasets Learn when to standardize data & when to test & script data cleanup Explore & analyze your datasets with new Python libraries & techniques Use Python solutions to automate your entire data-wrangling process ...

School leaders must know how to analyze interpret & use data so that they can make informed decisions in all areas of education ranging from professional development to student learning This book offers strategies & tools to help launch or fine-tune efforts to become a performance-driven school Based on the authors extensive work with 12 schools the book

Includes:: an examination of such essential topics as establishing a data culture investing in an information management system selecting the right data & analyzing & acting on data to improve performance

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