Manage Your SAP Projects with SAP Activate. Implementing SAP S/4HANA

Vinay Singh

It has been a general observation that most SAP consultants and professionals are used to the conventional waterfall methodology. Traditionally, this method has been there for ages and we all grew up learning about it and started practicing it in real world. The evolution of agile methodology has revolutionized the way we manage our projects and businesses. SAP Activate is an innovative, next generation business suite that allows producing working deliverables straight away. Manage your SAP Project with SAP Activate, will take your learning to the next level. The book promises to make you understand and practice the SAP Activate Framework. The focus is to take you on a journey of all the phases of SAP Activate methodology and make you understand all the phases with real time project examples. The author explains how SAP Activate methodology can be used through real-world use cases, with a comprehensive discussion on Agile and Scrum, in the context of SAP Project.You will get familiar with SAP S4HANA which is an incredibly innovative platform for businesses which can store business data, interpret it, analyze it, process it in real time, and use it when it's needed depending upon the business requirement.

CompTIA Project+ Certification Guide. Learn project management best practices and successfully pass the CompTIA Project+ PK0-004 exam

J. Ashley Hunt

The CompTIA Project+ exam is designed for IT professionals who want to improve their career trajectory by gaining certification in project management specific to their industry. This guide covers everything necessary to pass the current iteration of the Project+ PK0-004 exam.The CompTIA Project+ Certification Guide starts by covering project initiation best practices, including an understanding of organizational structures, team roles, and responsibilities. You’ll then study best practices for developing a project charter and the scope of work to produce deliverables necessary to obtain formal approval of the end result. The ability to monitor your project work and make changes as necessary to bring performance back in line with the plan is the difference between a successful and unsuccessful project. The concluding chapters of the book provide best practices to help keep an eye on your projects and close them out successfully. The guide also includes practice questions created to mirror the exam experience and help solidify your understanding of core project management concepts.By the end of this book, you will be able to develop creative solutions for complex issues faced in project management.

Machine Learning with the Elastic Stack. Expert techniques to integrate machine learning with distributed search and analytics

Rich Collier, Bahaaldine Azarmi

Machine Learning with the Elastic Stack is a comprehensive overview of the embedded commercial features of anomaly detection and forecasting. The book starts with installing and setting up Elastic Stack. You will perform time series analysis on varied kinds of data, such as log files, network flows, application metrics, and financial data.As you progress through the chapters, you will deploy machine learning within the Elastic Stack for logging, security, and metrics. In the concluding chapters, you will see how machine learning jobs can be automatically distributed and managed across the Elasticsearch cluster and made resilient to failure.By the end of this book, you will understand the performance aspects of incorporating machine learning within the Elastic ecosystem and create anomaly detection jobs and view results from Kibana directly.

Become a Python Data Analyst. Perform exploratory data analysis and gain insight into scientific computing using Python

Alvaro Fuentes

Python is one of the most common and popular languages preferred by leading data analysts and statisticians for working with massive datasets and complex data visualizations.Become a Python Data Analyst introduces Python’s most essential tools and libraries necessary to work with the data analysis process, right from preparing data to performing simple statistical analyses and creating meaningful data visualizations.In this book, we will cover Python libraries such as NumPy, pandas, matplotlib, seaborn, SciPy, and scikit-learn, and apply them in practical data analysis and statistics examples. As you make your way through the chapters, you will learn to efficiently use the Jupyter Notebook to operate and manipulate data using NumPy and the pandas library. In the concluding chapters, you will gain experience in building simple predictive models and carrying out statistical computation and analysis using rich Python tools and proven data analysis techniques.By the end of this book, you will have hands-on experience performing data analysis with Python.

Exploring Experience Design. Fusing business, tech, and design to shape customer engagement

Ezra Schwartz

We live in an experience economy in which interaction with products is valued more than owning them. Products are expected to engage and delight in order to form the emotional bonds that forge long-term customer loyalty:Products need to anticipate our needs and perform tasks for us: refrigerators order food, homes monitor energy, and cars drive autonomously; they track our vitals, sleep, location, finances, interactions, and content use; recognize our biometric signatures, chat with us, understand and motivate us. Beautiful and easy to use, products have to be fully customizable to match our personal preferences.Accomplishing these feats is easier said than done, but a solution has emerged in the form of Experience design (XD), the unifying approach to fusing business, technology and design around a user-centered philosophy.This book explores key dimensions of XD: Close collaboration among interdisciplinary teams, rapid iteration and ongoing user validation. We cover the processes, methodologies, tools, techniques and best-practices practitioners use throughout the entire product development life-cycle, as ideas are transformed to into positive experiences which lead to perpetual customer engagement and brand loyalty.

R Statistics Cookbook. Over 100 recipes for performing complex statistical operations with R 3.5

Francisco Juretig

R is a popular programming language for developing statistical software. This book will be a useful guide to solving common and not-so-common challenges in statistics. With this book, you'll be equipped to confidently perform essential statistical procedures across your organization with the help of cutting-edge statistical tools.You'll start by implementing data modeling, data analysis, and machine learning to solve real-world problems. You'll then understand how to work with nonparametric methods, mixed effects models, and hidden Markov models. This book contains recipes that will guide you in performing univariate and multivariate hypothesis tests, several regression techniques, and using robust techniques to minimize the impact of outliers in data.You'll also learn how to use the caret package for performing machine learning in R. Furthermore, this book will help you understand how to interpret charts and plots to get insights for better decision making.By the end of this book, you will be able to apply your skills to statistical computations using R 3.5. You will also become well-versed with a wide array of statistical techniques in R that are extensively used in the data science industry.

Testing Practitioner Handbook. Gain insights into the latest technology and business trends within testing domains

Renu Rajani

The book is based on the author`s experience in leading and transforming large test engagements and architecting solutions for customer testing requirements/bids/problem areas. It targets the testing practitioner population and provides them with a single go-to place to find perspectives, practices, trends, tools, and solutions to test applications as they face the evolving digital world. This book is divided into five parts where each part explores different aspects of testing in the real world. The first module explains the various testing engagement models. You will then learn how to efficiently test code in different life cycles. The book discusses the different aspects of Quality Analysis consideration while testing social media, mobile, analytics, and the Cloud. In the last module, you will learn about futuristic technologies to test software.By the end of the book, you will understand the latest business and IT trends in digital transformation and learn the best practices to adopt for business assurance.

Securing Network Infrastructure. Discover practical network security with Nmap and Nessus 7

Sairam Jetty, Sagar Rahalkar

Digitization drives technology today, which is why it’s so important for organizations to design security mechanisms for their network infrastructures. Analyzing vulnerabilities is one of the best ways to secure your network infrastructure.This Learning Path begins by introducing you to the various concepts of network security assessment, workflows, and architectures. You will learn to employ open source tools to perform both active and passive network scanning and use these results to analyze and design a threat model for network security. With a firm understanding of the basics, you will then explore how to use Nessus and Nmap to scan your network for vulnerabilities and open ports and gain back door entry into a network. As you progress through the chapters, you will gain insights into how to carry out various key scanning tasks, including firewall detection, OS detection, and access management to detect vulnerabilities in your network.By the end of this Learning Path, you will be familiar with the tools you need for network scanning and techniques for vulnerability scanning and network protection.This Learning Path includes content from the following Packt books:•Network Scanning Cookbook by Sairam Jetty•Network Vulnerability Assessment by Sagar Rahalkar