Big Data Visualization (eBook)

Learn effective tools and techniques to separate big data into manageable and logical components for efficient data visualization

Miller James D. Miller (Autor)

eBook Download: EPUB

2017
304 Seiten
Packt Publishing (Verlag)
978-1-78528-416-8 (ISBN)

Infos

Gain valuable insight into big data analytics with this book. Covering the tools you need to analyse data, together with IBM certified expert James Miller?s insight, this book is the key to data visualization success. ? Learn the tools & techniques to process big data for efficient data visualization ? Packed with insightful real-world use cases ? Addresses the difficulties faced by professionals in the field of big data analytics

---

Learn effective tools and techniques to separate big data into manageable and logical components for efficient data visualizationAbout This BookThis unique guide teaches you how to visualize your cluttered, huge amounts of big data with easeIt is rich with ample options and solid use cases for big data visualization, and is a must-have book for your shelfImprove your decision-making by visualizing your big data the right wayWho This Book Is ForThis book is for data analysts or those with a basic knowledge of big data analysis who want to learn big data visualization in order to make their analysis more useful. You need sufficient knowledge of big data platform tools such as Hadoop and also some experience with programming languages such as R. This book will be great for those who are familiar with conventional data visualizations and now want to widen their horizon by exploring big data visualizations.What You Will LearnUnderstand how basic analytics is affected by big dataDeep dive into effective and efficient ways of visualizing big dataGet to know various approaches (using various technologies) to address the challenges of visualizing big dataComprehend the concepts and models used to visualize big dataKnow how to visualize big data in real time and for different use casesUnderstand how to integrate popular dashboard visualization tools such as Splunk and TableauGet to know the value and process of integrating visual big data with BI tools such as TableauMake sense of the visualization options for big data, based upon the best suited visualization techniques for big dataIn DetailWhen it comes to big data, regular data visualization tools with basic features become insufficient. This book covers the concepts and models used to visualize big data, with a focus on efficient visualizations.This book works around big data visualizations and the challenges around visualizing big data and address characteristic challenges of visualizing like speed in accessing, understanding/adding context to, improving the quality of the data, displaying results, outliers, and so on. We focus on the most popular libraries to execute the tasks of big data visualization and explore "e;big data oriented"e; tools such as Hadoop and Tableau. We will show you how data changes with different variables and for different use cases with step-through topics such as: importing data to something like Hadoop, basic analytics.The choice of visualizations depends on the most suited techniques for big data, and we will show you the various options for big data visualizations based upon industry-proven techniques. You will then learn how to integrate popular visualization tools with graphing databases to see how huge amounts of certain data. Finally, you will find out how to display the integration of visual big data with BI using Cognos BI.Style and approachWith the help of insightful real-world use cases, we'll tackle data in the world of big data. The scalability and hugeness of the data makes big data visualizations different from normal data visualizations, and this book addresses all the difficulties encountered by professionals while visualizing their big data.

Produkt-Details

• Erscheint lt. Verlag: 28.2.2017
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik
• ISBN-10: 1-78528-416-9 / 1785284169
• ISBN-13: 978-1-78528-416-8 / 9781785284168