Data Processing category: 1302 books

Translate your data into info-graphics using popular packages in R About This Book Use R's popular packages—such as ggplot2, ggvis, ggforce, and more—to create custom, interactive visualization solutions. Create, design, and build interactive dashboards using Shiny A highly practical...

The Big Data Now anthology is relevant to anyone who creates, collectsor relies upon data. It's not just a technical book or just a businessguide. Data is ubiquitous and it doesn't pay much attention toborders, so we've calibrated our coverage to follow it wherever itgoes.In the first edition of Big...

Explore Python frameworks like pandas, Jupyter notebooks, and Matplotlib to build data pipelines and data visualization Key Features Learn to set up data analysis pipelines with pandas and Jupyter notebooks Effective techniques for data selection, manipulation, and visualization Introduction...

Learn the basics of Data Science through an easy to understand conceptual framework and immediately practice using RapidMiner platform. Whether you are brand new to data science or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships...

The Data Quality Assessment Framework shows you how to measure and monitor data quality, ensuring quality over time. You’ll start with general concepts of measurement and work your way through a detailed framework of more than three dozen measurement types related to five objective dimensions of...

Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s...

The Practitioner's Guide to Data Quality Improvement offers a comprehensive look at data quality for business and IT, encompassing people, process, and technology. It shares the fundamentals for understanding the impacts of poor data quality, and guides practitioners and managers alike in socializing,...

What do you need to become a data-driven organization? Far more than having big data or a crack team of unicorn data scientists, it requires establishing an effective, deeply-ingrained data culture. This practical book shows you how true data-drivenness involves processes that require genuine buy-in...

Includes vital coverage of how to avoid common pitfalls when first introducing Data Science to the enterprise. The need for precise, actionable, reliable, real-time Business Intelligence (BI) lies at the heart of the role of Big Data in modern commerce. In turn, the art of “Data Science”...

Extract valuable data from your social media sites and make better business decisions using RAbout This BookExplore the social media APIs in R to capture data and tame itEmploy the machine learning capabilities of R to gain optimal business valueA hands-on guide with real-world examples to help...

Learn how to leverage the power of R for Business Intelligence About This Book Use this easy-to-follow guide to leverage the power of R analytics and make your business data more insightful. This highly practical guide teaches you how to develop dashboards that help you make informed decisions...

Exploit the visualization capabilities of Kibana and build powerful interactive dashboards About This Book Introduction to data-driven architecture and the Elastic stack Build effective dashboards for data visualization and explore datasets with Elastic Graph A comprehensive guide to learning...

Your one-stop guide to building an efficient data science pipeline using Jupyter About This Book Get the most out of your Jupyter notebook to complete the trickiest of tasks in Data Science Learn all the tasks in the data science pipeline—from data acquisition to visualization—and implement...

Generate effective results in a variety of visually appealing charts using the plotting packages in Python About This Book Explore various tools and their strengths while building meaningful representations that can make it easier to understand data Packed with computational methods and algorithms...