Presents an introduction to differential equations, probability, and stochastic processes with real-world applications of queues with delay and delayed network queues Featuring recent advances in queueing theory and modeling, Delayed and Network Queues provides the most up-to-date theories in queueing model applications. Balancing both theoretical and practical applications of queueing theory, the book introduces queueing network models as tools to assist in the answering of questions on cost and performance that arise throughout the life of a computer system and signal processing. Written by well-known researchers in the field, the book presents key information for understanding the essential aspects of queues with delay and networks of queues with unreliable nodes and vacationing servers. Beginning with simple analytical fundamentals, the book contains a selection of realistic and advanced queueing models that address current deficiencies. In addition, the book presents the treatment of queues with delay and networks of queues, including possible breakdowns and disruptions that may cause delay. Delayed and Network Queues also features: Numerous examples and exercises with applications in various fields of study such as mathematical sciences, biomathematics, engineering, physics, business, health industry, and economics A wide array of practical applications of network queues and queueing systems, all of which are related to the appropriate stochastic processes Up-to-date topical coverage such as single- and multiserver queues with and without delays, along with the necessary fundamental coverage of probability and difference equations Discussions on queueing models such as single- and multiserver Markovian queues with balking, reneging, delay, feedback, splitting, and blocking, as well as their role in the treatment of networks of queues with and without delay and network reliability Delayed and Network Queues is an excellent textbook for upper-undergraduate and graduate-level courses in applied mathematics, queueing theory, queueing systems, probability, and stochastic processes. The book is also an ideal reference for academics and practitioners in mathematical sciences, biomathematics, operations research, management, engineering, physics, business, economics, health industry, and industrial engineering. Aliakbar Montazer Haghighi, PhD, is Professor and Head of the Department of Mathematics at Prairie View A&M University, USA, as well as founding Editor-in-Chief of Applications and Applied Mathematics: An International Journal (AAM). His research interests include probability, statistics, stochastic processes, and queueing theory. Among his research publications and books, Dr. Haghighi is the coauthor of Difference and Differential Equations with Applications in Queueing Theory (Wiley, 2013). Dimitar P. Mishev, PhD, is Professor in the Department of Mathematics at Prairie View A&M University, USA. His research interests include differential and difference equations and queueing theory. The author of numerous research papers and three books, Dr. Mishev is the coauthor of Difference and Differential Equations with Applications in Queueing Theory (Wiley, 2013).

Learn how to use the Apache Hadoop projects, including MapReduce, HDFS, Apache Hive, Apache HBase, Apache Kafka, Apache Mahout, and Apache Solr. From setting up the environment to running sample applications each chapter in this book is a practical tutorial on using an Apache Hadoop ecosystem project. While several books on Apache Hadoop are available, most are based on the main projects, MapReduce and HDFS, and none discusses the other Apache Hadoop ecosystem projects and how they all work together as a cohesive big data development platform. What You Will Learn: Set up the environment in Linux for Hadoop projects using Cloudera Hadoop Distribution CDH 5 Run a MapReduce job Store data with Apache Hive, and Apache HBase Index data in HDFS with Apache Solr Develop a Kafka messaging system Stream Logs to HDFS with Apache Flume Transfer data from MySQL database to Hive, HDFS, and HBase with Sqoop Create a Hive table over Apache Solr Develop a Mahout User Recommender System Who This Book Is For: Apache Hadoop developers. Pre-requisite knowledge of Linux and some knowledge of Hadoop is required.

Unleash the power of data by creating interactive, engaging, and compelling visualizations for the web About This Book Get a portable, versatile, and flexible data visualization design approach that will help you navigate the complex path towards success Get thorough explanation of the many visual variables and visualization taxonomy to provide you with a menu of creative options A comprehensive and contemporary introduction to data-driven visualization design and the most effective approaches to designing impact-maximizing and cognition-amplifying visualizations Who This Book Is For This course is for developers who are excited about data and who want to share that excitement with others and it will be handy for the web developers or data scientists who want to create interactive visualizations for the web. Prior knowledge of developing web applications is required. You should have a working knowledge of both JavaScript and HTML. What You Will Learn Harness the power of D3 by building interactive and real-time data-driven web visualizations Find out how to use JavaScript to create compelling visualizations of social data Identify the purpose of your visualization and your project's parameters to determine overriding design considerations across your project's execution Apply critical thinking to visualization design and get intimate with your dataset to identify its potential visual characteristics Explore the various features of HTML5 to design creative visualizations Discover what data is available on Stack Overflow, Facebook, Twitter, and Google+ Gain a solid understanding of the common D3 development idioms Find out how to write basic D3 code for server using Node.js In Detail Do you want to create more attractive charts? Or do you have huge data sets and need to unearth the key insights in a visual manner? Data visualization is the representation and presentation of data, using proven design techniques to bring alive the patterns, stories, and key insights that are locked away. This learning path is divided into three modules. The first module will equip you with the key techniques required to overcome contemporary data visualization challenges. After getting familiar with key concepts of data visualization, it's time to incorporate it with various technologies. In the second module, Social Data Visualization with HTML5 and JavaScript, it teaches you how to leverage HTML5 techniques through JavaScript to build visualizations. It also clears up how the often complicated OAuth protocol works to help you unlock a universe of social media data from sites such as Twitter, Facebook, and Google+. Once you are familiar with the concepts of incorporating data visualization with HTML5 and JavaScript, third module, Learning d3.js Data Visualization, will lead you to D3, which has emerged as one of the leading platforms to develop beautiful, interactive visualizations over the web. This module provides a strong foundation in designing compelling web visualizations with D3.js. By the end of this course, you will have unlocked the mystery behind successful data visualizations. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Data Visualization: a successful design process by Andy Kirk Social Data Visualization with HTML5 and JavaScript by Simon Timms Learning d3.js Data Visualization, Second Edition by Ændrew Rininsland and Swizec Teller Style and approach This course includes all the resources that will help you jump into creating interactive and engaging visualizations for the web. Through this comprehensive course, you’ll learn how to create engaging visualizations for the web to represent your data from start to finish! Downloading the example code for this book. You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the code file.

"Hadoop Blueprints" guides you through using Hadoop and its ecosystem to solve real-life business problems. You will explore six case studies covering areas like fraud detection, marketing analysis, and data lakes, providing a thorough and practical understanding of Hadoop applications. What this Book will help me do Understand how to use Hadoop to solve real-life business scenarios effectively. Learn to build a 360-degree customer view integrating different data types. Develop and deploy a fraud detection system leveraging Hadoop technologies. Explore marketing campaign analysis and improvement using data-driven workflows on Hadoop. Gain hands-on experience with creating and maintaining efficient data lakes. Author(s) Sudheesh Narayan, along with his co-authors Anurag Shrivastava and Nod Deshpande, brings extensive experience in Big Data technologies. They have been involved in developing solutions utilizing Hadoop, Apache Spark, and other ecosystem components. Their practical approach to presenting complex technical topics ensures readers can apply their knowledge to real-world scenarios. Who is it for? This book is ideal for software developers, data engineers, and IT professionals who have a foundational understanding of Hadoop and seek to expand their practical skills. Readers should be familiar with Java or other scripting languages. It's perfect for those aiming to build actionable solutions for business problems using Big Data technologies.

In "Learning Tableau 10: Business Intelligence and data visualization that brings your business into focus", you will master data visualization and storytelling using Tableau 10. From foundational concepts to advanced features, this book will enable you to create compelling dashboards and conduct powerful data analysis, empowering businesses with actionable insights. What this Book will help me do Master the creation of effective and visually attractive dashboards in Tableau. Learn techniques for preparing and cleaning data for accurate visualizations. Build advanced visualizations that clarify and communicate complex ideas. Explore data clustering and distribution modeling to identify trends and make forecasts. Share your Tableau creations to promote a culture of evidence-based decision making. Author(s) The authors of 'Learning Tableau 10' are seasoned professionals with extensive experience in business intelligence and data visualization. They bring practical industry insights and a passion for empowering readers through clear instructional design. Their goal is to enable businesses to harness the full potential of Tableau for data-driven success. Who is it for? This book is ideal for data analysts, business professionals, or newcomers to data visualization who want to learn Tableau 10 from scratch or upgrade their skills. It is perfectly suited for beginners striving to bring professional insights and advanced users seeking to leverage Tableau's latest features effectively.

Dive into advanced GIS techniques with 'Mastering QGIS,' a comprehensive guide that teaches you how to leverage the full capabilities of the open-source GIS software QGIS. Through practical examples, you'll advance your skills from the fundamentals to professional levels by developing plugins, automating workflows, and mastering data visualization. What this Book will help me do Create comprehensive spatial databases to organize and analyze GIS data effectively. Master advanced styling techniques for professional-quality map presentation. Process vector and raster data, including preparing and analyzing data for specific use cases. Integrate Python scripting to automate GIS data workflows and extend QGIS functionality. Develop custom QGIS plugins to tailor the software to your projects and needs. Author(s) Kurt Menke, GISP, along with co-authors recognized as experts in GIS, share their extensive experience with QGIS. They bring a practical approach aimed at GIS professionals seeking deeper software mastery. Who is it for? This book is ideal for GIS professionals, students, and analysts intending to elevate their QGIS competency. Whether you're looking to switch from proprietary GIS tools or enhance your open-source skillset, this resource provides the expertise required to excel in your field.

Master the Powerful Multitenant Features of Oracle Database 12c Govern a scalable, extensible, and highly available enterprise database environment using the practical information contained in this Oracle Press guide. Written by a team of Oracle Masters, Oracle Database 12c Release 2 Multitenant shows, step-by-step, how to deploy and manage multitenant configurations across IT frameworks of all types and sizes. Find out how to create databases, work with PDBs and CDBs, administer Oracle Net Services, and automate administrative tasks. Backup and recovery, security, and advanced multitenant options are covered in complete detail. Learn how to: • Build high-performance multitenant Oracle databases • Create single-tenant, multitenant, and application containers • Establish network connections and manage services • Handle security using authentication, authorization, and encryption • Back up and restore your mission-critical data • Work with point-in-time recovery and Oracle Flashback • Move data and replicate and clone databases • Work with Oracle’s Resource Manager and Data Guard

Practical Data Analysis provides a hands-on guide to mastering essential data analysis techniques using tools like Pandas, MongoDB, and Apache Spark. With step-by-step instructions, you'll explore how to process diverse data types, apply machine learning methods, and uncover actionable insights that can drive innovative projects and business solutions. What this Book will help me do Master data acquisition, formatting, and visualization techniques to prepare your data for analysis. Understand and apply machine learning algorithms for tasks like classification and forecasting. Learn to analyze textual data, such as performing sentiment analysis and text classification. Effectively work with databases using tools like MongoDB and handle big data with Apache Spark. Develop data-driven applications using real-world examples like image similarity searches and social network graph analysis. Author(s) None Cuesta and Dr. Sampath Kumar are experienced data scientists and educators. They have considerable experience applying data analysis techniques in various domains and a passion for teaching these skills. Their practical approach to data analysis ensures an engaging learning experience for readers. Who is it for? This book is ideal for developers and data enthusiasts aiming to incorporate practical data analysis into their projects. It is perfectly suited for readers with basic programming, statistics, and linear algebra knowledge. Even if you're new to professional data analysis, you'll find the step-by-step examples approachable. This book guides you in transforming raw data into valuable insights.

Learn to build and implement a robust Oracle E-Business Suite system using the new release, EBS 12.2. This hands-on, real-world guide explains the rationale for using an Oracle E-Business Suite environment in a business enterprise and covers the major technology stack changes from EBS version 11i through R12.2. You will learn to build up an EBS environment from a simple single-node installation to a complex multi-node high available setup. Practical Oracle E-Business Suite focuses on release R12.2, but key areas in R12.1 are also covered wherever necessary. Detailed instructions are provided for the installation of EBS R12.2 in single and multi-node configurations, the logic and methodology used in EBS patching, and cloning of EBS single-node and complex multi-node environments configured with RAC. This book also provides information on FMW used in EBS 12.2, as well as performance tuning and EBS 12.2 on engineered system implementations. Understand Oracle EBS software and the underlying technology stack components Install/configure Oracle E-Business Suite R12.2 in simple and HA complex setups Manage Oracle EBS 12.2 Use online patching (adop) for Installation of Oracle EBS patches Clone an EBS environment in simple and complex configurations Perform and tune Oracle EBS in all layers (Application/DB/OS/NW) Secure E-Business Suite R12.2 Who This Book Is For: Developers, data architects, and data scientists looking to integrate the most successful big data open stack architecture and how to choose the correct technology in every layer

Explore how to leverage Apache Spark for efficient big data analytics and machine learning solutions in "Spark for Data Science". This detailed guide provides you with the skills to process massive datasets, perform data analytics, and build predictive models using Spark's powerful tools like RDDs, DataFrames, and Datasets. What this Book will help me do Gain expertise in data processing and transformation with Spark. Perform advanced statistical analysis to uncover insights. Master machine learning techniques to create predictive models using Spark. Utilize Spark's APIs to process and visualize big data. Build scalable and efficient data science solutions. Author(s) This book is co-authored by None Singhal and None Duvvuri, both accomplished data scientists with extensive experience in Apache Spark and big data technologies. They bring their practical industry expertise to explain complex topics in a straightforward manner. Their writing emphasizes real-world applications and step-by-step procedural guidance, making this a valuable resource for learners. Who is it for? This book is ideally suited for technologists seeking to incorporate data science capabilities into their work with Apache Spark, data scientists interested in machine learning algorithms implemented in Spark, and beginners aiming to step into the field of big data analytics. Whether you are familiar with Spark or completely new, this book offers valuable insights and practical knowledge.

Learn how to integrate full-stack open source big data architecture and to choose the correct technology—Scala/Spark, Mesos, Akka, Cassandra, and Kafka—in every layer. Big data architecture is becoming a requirement for many different enterprises. So far, however, the focus has largely been on collecting, aggregating, and crunching large data sets in a timely manner. In many cases now, organizations need more than one paradigm to perform efficient analyses. Big Data SMACK explains each of the full-stack technologies and, more importantly, how to best integrate them. It provides detailed coverage of the practical benefits of these technologies and incorporates real-world examples in every situation. This book focuses on the problems and scenarios solved by the architecture, as well as the solutions provided by every technology. It covers the six main concepts of big data architecture and how integrate, replace, and reinforce every layer: What You'll Learn The language: Scala The engine: Spark (SQL, MLib, Streaming, GraphX) The container: Mesos, Docker The view: Akka The storage: Cassandra The message broker: Kafka What You Will Learn: Make big data architecture without using complex Greek letter architectures Build a cheap but effective cluster infrastructure Make queries, reports, and graphs that business demands Manage and exploit unstructured and No-SQL data sources Use tools to monitor the performance of your architecture Integrate all technologies and decide which ones replace and which ones reinforce Who This Book Is For Developers, data architects, and data scientists looking to integrate the most successful big data open stack architecture and to choose the correct technology in every layer

Dive into the world of big data with "Big Data Analytics: Real Time Analytics Using Apache Spark and Hadoop." This comprehensive guide introduces readers to the fundamentals and practical applications of Apache Spark and Hadoop, covering essential topics like Spark SQL, DataFrames, structured streaming, and more. Learn how to harness the power of real-time analytics and big data tools effectively. What this Book will help me do Master the key components of Apache Spark and Hadoop ecosystems, including Spark SQL and MapReduce. Gain an understanding of DataFrames, DataSets, and structured streaming for seamless data handling. Develop skills in real-time analytics using Spark Streaming and technologies like Kafka and HBase. Learn to implement machine learning models using Spark's MLlib and ML Pipelines. Explore graph analytics with GraphX and leverage data visualization tools like Jupyter and Zeppelin. Author(s) Venkat Ankam, an expert in big data technologies, has years of experience working with Apache Hadoop and Spark. As an educator and technical consultant, Venkat has enabled numerous professionals to gain critical insights into big data ecosystems. With a pragmatic approach, his writings aim to guide readers through complex systems in a structured and easy-to-follow manner. Who is it for? This book is perfect for data analysts, data scientists, software architects, and programmers aiming to expand their knowledge of big data analytics. Readers should ideally have a basic programming background in languages like Python, Scala, R, or SQL. Prior hands-on experience with big data environments is not necessary but is an added advantage. This guide is created to cater to a range of skill levels, from beginners to intermediate learners.

Speed up the execution of important database queries by making good choices about which indexes to create. Choose correct index types for different scenarios. Avoid indexing pitfalls that can actually have indexes hurting performance rather than helping. Maintain indexes so as to provide consistent and predictable query response over the lifetime of an application. is about the one database structure at the heart of almost all performance concerns: the index. Database system performance is one of the top concerns in information technology today. Administrators struggle to keep up with the explosion of access and activity driven by the proliferation of computing into everything from phones to tablets to PCs in our increasingly connected world. At the heart of any good-performing database lies a sound indexing strategy that makes appropriate use of indexing, and especially of the vendor-specific indexing features on offer. Expert Oracle Indexing and Access Paths Few databases fully exploit the wealth of data access mechanisms provided by Oracle. helps by bringing together information on indexing and how to use it into one blissfully short volume that you can read quickly and have at your fingertips for reference. Learn the different types of indexes available and when each is best applied. Recognize when queries aren't using indexes as you intend. Manage your indexing for maximum performance. Confidently use the In Memory column store feature as an alternate access path to improve performance. Let Expert Indexing in Oracle Database 12c be your guide to deep mastery of the most fundamental performance optimization structure in Oracle Database. Expert Oracle Indexing and Access Paths Explains how indexes help performance, and sometimes hinder it too Demystifies the various index choices so that you can chose rightly Describes the database administration chores associated with indexes Demonstrates the use of the In Memory column store as an alternate access path to the data What You Will Learn Create an overall indexing strategy to guide your decisions Choose the correct indexing mechanisms for your applications Manage and maintain indices to avoid degradation and preserve efficiency Take better advantage of underused index types such as index-organized tables Choose the appropriate columns to index, with confidence Blend partitioning and materialized views into your indexing strategy Who This Book Is For All levels of database administrators and application developers who are struggling with the database performance and scalability challenge. Any database administrator involved with indexing, which is any database administrator period, will appreciate the wealth of advice packed into this gem of a book.

Dive into the advanced features of PostgreSQL and master database development with 'PostgreSQL Development Essentials'. This book guides you step-by-step through topics like advanced SQL queries, database design, query optimization, and using PostgreSQL with programming languages like Java and PHP. By the end, you'll have the skills to build secure, efficient, and enterprise-ready database applications. What this Book will help me do Write powerful and complex SQL queries to harness the full potential of PostgreSQL. Create and optimize robust database designs tailored to application needs. Enhance database performance through indexing, partitioning, and query optimization. Integrate PostgreSQL seamlessly with Java and PHP for advanced application development. Utilize PostgreSQL extensions and features to expand functionality and ensure scalability. Author(s) Baji Shaik, the author of 'PostgreSQL Development Essentials', has extensive experience in database development and optimization with a focus on PostgreSQL. With his practical approach, Baji simplifies advanced concepts and provides actionable insights to empower developers. His teaching style bridges technical depth with accessibility, making this book an essential for professionals aiming to excel in PostgreSQL. Who is it for? This book is designed for software developers and database professionals who have a foundational understanding of PostgreSQL and are eager to deepen their expertise. It is ideal for those looking to enrich their skills in advanced SQL, optimizing database performance, and integrating PostgreSQL with application frameworks like Java and PHP. If you're aiming to elevate your database applications to enterprise-grade quality while ensuring both efficiency and scalability, this book is tailored for you.

Up-to-Date Coverage of Microsoft® SQL Server® 2016 Reporting Services, Including the Mobile Report Publisher Build, publish, and maintain paginated and mobile reports using the expert tips and best practices contained in this hands-on guide. Written by a member of the original Reporting Services development team, Microsoft SQL Server 2016 Reporting Services, Fifth Edition, fully explains the process of creating and distributing reports and shows how to maximize all of the powerful, integrated SSRS capabilities, including the new and enhanced features. A detailed case study and sample reports are featured in this practical resource. • Plan for, install, configure, and customize SQL Server 2016 Reporting Services • Design and generate feature-rich reports using the Report Wizard • Work with Report Designer in Visual Studio, Report Builder, and the Mobile Report Publisher • Incorporate charts, images, gauges, and maps • Enhance your reports through summarizing, totaling, and interactivity • Build reusable report templates • Embed Visual Basic .NET functions and subreports • Enable end-user access via the Report Server and its web portal interface • Integrate SSRS reports with your own websites and custom applications • Follow along with sample reports from the book’s case study

Learn how to solve basic statistical problems with Ron Cody's easy-to-follow style using the point-and-click SAS Studio tasks. Aimed specifically at the health sciences, Biostatistics by Example Using SAS Studio, provides an introduction to SAS Studio tasks. The book includes many biological and health-related problem sets and is fully compatible with SAS University Edition. After reading this book you will be able to understand temporary and permanent SAS data sets, and you will learn how to create them from various data sources. You will also be able to use SAS Studio statistics tasks to generate descriptive statistics for continuous and categorical data. The inferential statistics portion of the book covers the following topics: paired and unpaired t tests one-way analysis of variance N-way ANOVA correlation simple and multiple regression logistic regression categorical data analysis power and sample size calculations Besides describing each of these statistical tests, the book also discusses the assumptions that need to be met before running and interpreting these tests. For two-sample tests and N-way tests, nonparametric tests are also described. This book leads you step-by-step through each of the statistical tests with numerous screen shots, and you will see how to read and interpret all of the output generated by these tests. Experience with some basic statistical tests used to analyze medical data or classroom experience in biostatistics or statistics is required. Although the examples are related to the medical and biology fields, researchers in other fields such as psychology or education will find this book helpful. No programming experience is required. Loading data files into SAS University Edition? Click here for more information.

IBM® Power Virtualization Center (IBM® PowerVC™) is an advanced, enterprise virtualization management offering for IBM Power Systems™. This IBM Redbooks® publication introduces PowerVC and helps you understand its functions, planning, installation, and setup. PowerVC Version 1.3.1 supports both large and small deployments, either by managing IBM PowerVM® that is controlled by the Hardware Management Console (HMC) or by IBM PowerVM Novalink, or by managing PowerKVM directly. With this capability, PowerVC can manage IBM AIX®, IBM i, and Linux workloads that run on IBM POWER® hardware, including IBM PurePower systems. PowerVC is available as a Standard Edition, or as a Cloud PowerVC Manager edition. PowerVC Standard Edition includes the following features and benefits: Virtual image capture, deployment, and management Policy-based virtual machine (VM) placement to improve use Management of real-time optimization and VM resilience to increase productivity VM Mobility with placement policies to reduce the burden on IT staff in a simple-to-install and easy-to-use graphical user interface (GUI) Role-based security policies to ensure a secure environment for common tasks IBM Cloud PowerVC Manager includes all of the PowerVC Standard Edition features and adds: A self-service portal that enables user access to the cloud infrastructure on a per-project basis The ability to enable an administrator to enable Dynamic Resource Optimization on a schedule This publication is for experienced users of IBM PowerVM and other virtualization solutions who want to understand and implement the next generation of enterprise virtualization management for Power Systems. Unless stated otherwise, the content of this publication refers to IBM PowerVC Version 1.3.1.

Use aggregate data to answer high-level business questions!

Data miners, data scientists, analytic managers, and analysts who work in all industries will find the insights in Randy Collica's Strategic Analytics and SAS: Using Aggregate Data to Drive Organizational Initiatives invaluable in their work. This book shows you how to use your existing data at aggregate levels to answer high-level business questions. Written in a detailed, step-by-step format, the multi-industry use cases begin with a high-level question that a C-level executive might ask. Collica then progresses through the steps to perform the analysis, including many tables and screenshots to guide you along the way. He then ends each use case with the solution to the high-level question. Topics covered include logistic analysis, models developed from surveys, survival analysis, confidence intervals, text mining and analysis, visual analytics, hypothesis tests, and size and magnitude of analytic effects. Connect the dots between detailed data on your customers and the high-level business goals of your organization with Strategic Analytics and SAS!

In this fourth edition of O’Reilly’s Data Science Salary Survey, 983 respondents working across a variety of industries answered questions about the tools they use, the tasks they engage in, and the salaries they make. This year’s survey includes data scientists, engineers, and others in the data space from 45 countries and 45 US states. The 2016 survey included new questions, most notably about specific data-related tasks that may affect salary. Plug in your own data points to the survey model and see how you compare to other data science professionals in your industry. With this report, you’ll learn: Where data scientists make the highest salaries—by country and by US state Tools that respondents most commonly use on the job, and tools that contribute most to salary Two activities that contribute to higher earnings among respondents How gender and bargaining skills affect salaries when all other factors are equal Salary differences between those using open source tools vs those using proprietary tools Salary differences between those who rely on Python vs those who use several tools Participate in the 2017 Survey The survey is now open for the 2017 report. Spend just 5 to 10 minutes and take the anonymous salary survey here: https://www.oreilly.com/ideas/take-the-2​017-data-science-salary-survey.

User experience monitoring is essential for enhancing the usability and performance of your mobile native app. How are your customers using your product? Which features do they prefer? How can you spot trouble before it adversely affects your product? This O’Reilly report provides an overview of several metrics you can apply, based on different use-cases. Author Wolfgang Beer explains the typical instrumentation and publishing process of mobile apps, and takes you through different instrumentation approaches. With screenshots from popular tools such as Google Analytics, Ruxit, Fabric, and Flurry Analytics, this report helps you choose the metrics that will help you improve your product’s performance. Monitor performance to understand your app’s stability and usability Measure app user engagement by identifying active and new users, and determining median session length Determine your app’s current retention and churn rates Gather business intelligence by defining users according to personas and lifetime value Oversee the service and infrastructure dependencies of your app in real time Visually track user behavior with heat maps and navigational paths Add automated or manual instrumentation before you publish your app