* This book will enable and empower you to break free of the shackles of spreadsheets
* Learn to make informed decisions using the data at hand with this highly practical, comprehensive guide
* This book includes real-world use cases that teach you how analytics can be put to work to more » optimize your business
* Using a fictional transactional dataset in raw form, you'll work your way up to ultimately creating a fully-functional warehouse and a fleshed-out BI platform
Business Intelligence (BI) is at the crux of revolutionizing enterprise. Everyone wants to minimize losses and maximize profits. Thanks to Big Data and improved methodologies to analyze data, Data Analysts and Data Scientists are increasingly using data to make informed decisions. Just knowing how to analyze data is not enough, you need to start thinking how to use data as a business asset and then perform the right analysis to build an insightful BI solution. Efficient BI strives to achieve the automation of data for ease of reporting and analysis.
Through this book, you will develop the ability to think along the right lines and use more than one tool to perform analysis depending on the needs of your business. We start off by preparing you for data analytics. We then move on to teach you a range of techniques to fetch important information from various databases, which can be used to optimize your business.
The book aims to provide a full end-to-end solution for an environment setup that can help you make informed business decisions and deliver efficient and automated BI solutions to any company.
It is a complete guide for implementing Business intelligence with the help of the most powerful tools like D3.js, R, Tableau, Qlikview and Python that are available on the market.
WHAT YOU WILL LEARN
* Create a BI environment that enables self-service reporting
* Understand SQL and the aggregation of data
* Develop a data model suitable for analytical reporting
* Connect a data warehouse to the analytic reporting tools
* Understand the specific benefits behind visualizations with D3.js, R, Tableau, QlikView, and Python
* Get to know the best practices to develop various reports and applications when using BI tools
* Explore the field of data analysis with all the data we will use for reporting « less
Source code is one of the biggest assets of a software company. However if not maintained well, it can become a big liability. As source code becomes larger. more complex and accessed via the cloud, maintaining code quality becomes even more challenging. The author provides straightforward tools and advice on how to manage code quality in this new environment.
Roslyn exposes a set of APIs which allow developers to parse their C# and VB.NET code and drastically lower the barrier to entry for Meta programming in .NET. Roslyn has a dedicated set of APIs for creating custom refactoring for integrating with Visual Studio.
What You Will Learn
* Understand the Roslyn Syntax API
* Use Data Visualization techniques to assist code analysis process visually
* Code health monitoring matrices (from the standard of Code Query Language)
* Code mining techniques to identify design patterns used in source code
* Code forensics techniques to identify probable author of a given source code
* Techniques to identify duplicate/near duplicate code
Who This Book is For
.NET Software Developers and Architects « less
Explore the world of data science from scratch with Julia by your side
* An in-depth exploration of Julia's growing ecosystem of packages
* Work with the most powerful open-source libraries for deep learning, data wrangling, and data visualization
* Learn about deep learning using Mocha.jl and give speed and high performance to data analysis on large data more » sets
Julia is a fast and high performing language that's perfectly suited to data science with a mature package ecosystem and is now feature complete. It is a good tool for a data science practitioner. There was a famous post at Harvard Business Review that Data Scientist is the sexiest job of the 21st century. (https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century).
This book will help you get familiarised with Julia's rich ecosystem, which is continuously evolving, allowing you to stay on top of your game.
This book contains the essentials of data science and gives a high-level overview of advanced statistics and techniques. You will dive in and will work on generating insights by performing inferential statistics, and will reveal hidden patterns and trends using data mining. This has the practical coverage of statistics and machine learning. You will develop knowledge to build statistical models and machine learning systems in Julia with attractive visualizations.
You will then delve into the world of Deep learning in Julia and will understand the framework, Mocha.jl with which you can create artificial neural networks and implement deep learning.
This book addresses the challenges of real-world data science problems, including data cleaning, data preparation, inferential statistics, statistical modeling, building high-performance machine learning systems and creating effective visualizations using Julia.
WHAT YOU WILL LEARN
* Apply statistical models in Julia for data-driven decisions
* Understanding the process of data munging and data preparation using Julia
* Explore techniques to visualize data using Julia and D3 based packages
* Using Julia to create self-learning systems using cutting edge machine learning algorithms
* Create supervised and unsupervised machine learning systems using Julia. Also, explore ensemble models
* Build a recommendation engine in Julia
* Dive into Julia’s deep learning framework and build a system using Mocha.jl
ABOUT THE AUTHOR
Anshul Joshi is a data science professional with more than 2 years of experience primarily in data munging, recommendation systems, predictive modeling, and distributed computing. He is a deep learning and AI enthusiast. Most of the time, he can be caught exploring GitHub or trying anything new on which he can get his hands on. He blogs on anshuljoshi.xyz.
TABLE OF CONTENTS
1. The Groundwork – Julia's Environment
2. Data Munging
3. Data Exploration
4. Deep Dive into Inferential Statistics
5. Making Sense of Data Using Visualization
6. Supervised Machine Learning
7. Unsupervised Machine Learning
8. Creating Ensemble Models
9. Time Series
10. Collaborative Filtering and Recommendation System
11. Introduction to Deep Learning « less
Unchain your data from the desktop with responsive visualizations Building Responsive Data Visualization for the Web is a handbook for any front-end development team needing a framework for integrating responsive web design into the current workflow. Written by a leading industry expert and design lead more » at Starbase Go, this book provides a wealth of information and practical guidance from the perspective of a real-world designer. You'll walk through the process of building data visualizations responsively as you learn best practices that build upon responsive web design principles, and get the hands-on practice you need with exercises, examples, and source code provided in every chapter. These strategies are designed to be implemented by teams large and small, with varying skill sets, so you can apply these concepts and skills to your project right away.
Responsive web design is the practice of building a website to suit base browser capability, then adding features that enhance the experience based on the user's device's capabilities. Applying these ideas to data produces visualizations that always look as if they were designed specifically for the device through which they are viewed. This book shows you how to incorporate these principles into your current practices, with highly practical hands-on training.
* Examine the hard data surrounding responsive design
* Master best practices with hands-on exercises
* Learn data-based document manipulation using D3.js
* Adapt your current strategies to responsive workflows
Data is growing exponentially, and the need to visualize it in any context has become crucial. Traditional visualizations allow important data to become lost when viewed on a small screen, and the web traffic speaks for itself – viewers repeatedly demonstrate their preference for responsive design. If you're ready to create more accessible, take-anywhere visualizations, Building Responsive Data Visualization for the Web is your tailor-made solution. « less
Bring your data to life by creating and deploying complex data visualizations with D3.js
* Learn how to create custom charts as reusable components that can be integrated with your existing projects
* Design data-driven applications with several charts interacting between them
* Create an analytics dashboard to display real-time data using Node.js and D3
D3.js more » is one of the most popular and powerful tools for creating data visualizations. As the pressure to produce accurate and clear insights from data increases, D3.js remains a reliable and high-quality data visualization solution. Mastering D3.js provides you with clear and detailed guidance to help you dive deeper into D3, and learn how to create data visualizations that are capable of responding to the modern challenges of data. Taking a comprehensive approach to D3.js, and tackling everything you need to take your data visualization skills to another level of sophistication, Mastering D3.js is an essential book for anyone interested in the intersection of data science and design.
Use this advanced D3.js book to get to grips with cutting-edge data visualization. Learn how to create a reusable chart and a layout algorithm, before moving further into D3, as you learn how to make a color picker and develop an effective user interface. You will also find further practical information on how to create a quality user dashboard for high-quality big data analytics and tips to help you learn how to integrate mapping libraries.
The book concludes with a clear demonstration of how to create a real-time data visualization application with Firebase to give you a complete picture of what D3.js makes possible in data visualization today.
WHAT YOU WILL LEARN
* Discover the full potential of D3.js as an awesome data visualization technology
* Learn D3.js application development
* Use practical tips and insight from an expert to learn how to design and make an effective interface
* Learn how to create custom charts as reusable components to be integrated with existing projects
* Create a powerful and high-quality analytics dashboard
* Find out how to create custom maps and integrate D3 with third-party mapping libraries
* Follow steps to create data-driven applications by integrating D3 with Backbone
* Learn how to collaborate with Firebase for real-time data analytics
ABOUT THE AUTHOR
Pablo Navarro Castillo is a mathematical engineer and developer. He earned his Master's degree in Applied Mathematics from École des Mines de Saint-Etienne in France. After working for a few years in operations research and data analysis, he began to work as a data visualization consultant and developer. In 2014, he founded Masega, which is a data visualization agency based in Santiago, Chile, where he currently works.
TABLE OF CONTENTS
1. Data Visualization
2. Reusable Charts
3. Creating Visualizations Without SVG
4. Creating a Color Picker with D3
5. Creating User Interface Elements
6. Interaction Between Charts
7. Creating a Charting Package
8. Data-Driven Applications
9. Creating a Dashboard
10. Creating Maps
11. Creating Advanced Maps
12. Creating a Real-time Application « less
With jqPlot, D3, and Highcharts