The concept of deep machine learning is easier to understand by paying attention to the cyclic stochastic time series and a time series whose content is non-stationary not only within the cycles, but also over the cycles as the cycle-to-cycle variations.

Next-Generation Sequencing Data Analysis walks readers through NGS data analysis step-by-step for a wide range of NGS applications.

Practice making sense of data with IBM’s SPSS Statistics software SPSS Statistics Workbook For Dummies gives you the practice you need to navigate the leading statistical software suite. Data management and analysis, advanced analytics, business intelligence—SPSS is a powerhouse of a research platform, and this book helps you master the fundamentals and analyze data more effectively. You’ll work through practice problems that help you understand the calculations you need to perform, complete predictive analyses, and produce informative graphs. This workbook gives you hands-on exercises to hone your statistical analysis skills with SPSS Statistics 28. Plus, explanations and insider tips help you navigate the software with ease. Practical and easy-to-understand, in classic Dummies style. Practice organizing, analyzing, and graphing data Learn to write, edit, and format SPSS syntax Explore the upgrades and features new to SPSS 28 Try your hand at advanced data analysis procedures For academics using SPSS for research, business analysts and market researchers looking to extract valuable insights from data, and anyone with a hankering for more stats practice.

Lead your demand planning process to excellence and deliver real value to your supply chain. In Demand Forecasting Best Practices you’ll learn how to: Lead your team to improve quality while reducing workload Properly define the objectives and granularity of your demand planning Use intelligent KPIs to track accuracy and bias Identify areas for process improvement Help planners and stakeholders add value Determine relevant data to collect and how best to collect it Utilize different statistical and machine learning models An expert demand forecaster can help an organization avoid overproduction, reduce waste, and optimize inventory levels for a real competitive advantage. Demand Forecasting Best Practices teaches you how to become that virtuoso demand forecaster. This one-of-a-kind guide reveals forecasting tools, metrics, models, and stakeholder management techniques for delivering more effective supply chains. Everything you learn has been proven and tested in a live business environment. Discover author Nicolas Vandeput’s original five step framework for demand planning excellence and learn how to tailor it to your own company’s needs. Illustrations and real-world examples make each concept easy to understand and easy to follow. You’ll soon be delivering accurate predictions that are driving major business value. About the Technology An expert demand forecaster can help an organization avoid overproduction, reduce waste, and optimize inventory levels for a real competitive advantage. This book teaches you how to become that virtuoso demand forecaster. About the Book Demand Forecasting Best Practices reveals forecasting tools, metrics, models, and stakeholder management techniques for managing your demand planning process efficiently and effectively. Everything you learn has been proven and tested in a live business environment. Discover author Nicolas Vandeput’s original five step framework for demand planning excellence and learn how to tailor it to your own company’s needs. Illustrations and real-world examples make each concept easy to understand and easy to follow. You’ll soon be delivering accurate predictions that are driving major business value. What's Inside Enhance forecasting quality while reducing team workload Utilize intelligent KPIs to track accuracy and bias Identify process areas for improvement Assist stakeholders in sales, marketing, and finance Optimize statistical and machine learning models About the Reader For demand planners, sales and operations managers, supply chain leaders, and data scientists. About the Author Nicolas Vandeput is a supply chain data scientist, the founder of consultancy company SupChains in 2016, and a teacher at CentraleSupélec, France. Quotes This new book continues to push the FVA mindset, illustrating practices that drive the efficiency and effectiveness of the business forecasting process. - Michael Gilliland, Editor-in-Chief, Foresight: Journal of Applied Forecasting A must-read for any SCM professional, data scientist, or business owner. It's practical, accessible, and packed with valuable insights. - Edouard Thieuleux, Founder of AbcSupplyChain An exceptional resource that covers everything from basic forecasting principles to advanced forecasting techniques using artificial intelligence and machine learning. The writing style is engaging, making complex concepts accessible to both beginners and experts. - Daniel Stanton, Mr. Supply Chain® Nicolas did it again! Demand Forecasting Best Practices provides practical and actionable advice for improving the demand planning process. - Professor Spyros Makridakis, The Makridakis Open Forecasting Center, Institute For the Future (IFF), University of Nicosia This book is now my companion on all of our planning and forecasting projects. A perfect foundation for implementation and also to recommend process improvements. - Werner Nindl, Chief Architect – CPM Practice Director, Pivotal Drive This author understands the nuances of forecasting, and is able to explain them well. - Burhan Ul Haq, Director of Products, Enablers Both broader and deeper than I expected. - Maxim Volgin, Quantitative Marketing Manager, KLM Great book with actionable insights. - Simon Tschöke, Head of Research, German Edge Cloud

Dive into the exciting world of data science with this practical introduction. Packed with essential skills and useful examples, Dive Into Data Science will show you how to obtain, analyze, and visualize data so you can leverage its power to solve common business challenges. With only a basic understanding of Python and high school math, you’ll be able to effortlessly work through the book and start implementing data science in your day-to-day work. From improving a bike sharing company to extracting data from websites and creating recommendation systems, you’ll discover how to find and use data-driven solutions to make business decisions. Topics covered include conducting exploratory data analysis, running A/B tests, performing binary classification using logistic regression models, and using machine learning algorithms. You’ll also learn how to: •Forecast consumer demand •Optimize marketing campaigns •Reduce customer attrition •Predict website traffic •Build recommendation systems With this practical guide at your fingertips, harness the power of programming, mathematical theory, and good old common sense to find data-driven solutions that make a difference. Don’t wait; dive right in!

Understand the essentials of people analytics and learn how to find, collect, analyse and apply data to add business value with the second edition of this guide.

This book covers the basics of SAP’s Integration Suite, including a broad overview of its capabilities, installation, and real-life examples to illustrate how it can be used to integrate, develop, administer, and monitor applications in the cloud. As you progress through the book, you will see how SAP Integration Suite works as an open, enterprise-grade platform that is a fully vendor-managed, multi-cloud offering that will help you expedite your SAP and third-party integration scenarios. The entire value chain is explored in detail, including usage of APIs and runtime control. Author Jaspreet Bagga demonstrates how SAP’s prebuilt integration packages facilitate quicker, more comprehensive integrations, and how they support a variety of integration patterns. You’ll learn how to leverage the platform to enable seamless cloud and on-premises applications connectivity, develop custom scenarios, mix master data, blend business-to-business (B2B) and electronic data interchange (EDI) processes, including trading partner management. Also covered are business-to-government (B2G) scenarios, orchestrating data and pipelines, and mixing event-driven integration. Upon completing this book, you will have a thorough understanding of why SAP Integration Suite is the middleware of SAP’s integration strategy, and be able to effectively use it in your own integration scenarios. What You Will Learn Understand SAP Integration Suite and its core capabilities Know how integration technologies, such as architecture and supplementary intelligent technologies, work within the SAP Integration Suite Discover services for pre-packaged accelerators: SAP API Management, the Integration Advisor, and the SAP API Business Hub Utilize integration features to link your on-premises or cloud-based systems Understand the capabilities of the newly released Migration Assessment Who This Book Is forWeb developers and application leads who want to learn SAP Integration Suite.

Data Engineering with dbt provides a comprehensive guide to building modern, reliable data platforms using dbt and SQL. You'll gain hands-on experience building automated ELT pipelines, using dbt Cloud with Snowflake, and embracing patterns for scalable and maintainable data solutions. What this Book will help me do Set up and manage a dbt Cloud environment and create reliable ELT pipelines. Integrate Snowflake with dbt to implement robust data engineering workflows. Transform raw data into analytics-ready data using dbt's features and SQL. Apply advanced dbt functionality such as macros and Jinja for efficient coding. Ensure data accuracy and platform reliability with built-in testing and monitoring. Author(s) None Zagni is a seasoned data engineering professional with a wealth of experience in designing scalable data platforms. Through practical insights and real-world applications, Zagni demystifies complex data engineering practices. Their approachable teaching style makes technical concepts accessible and actionable. Who is it for? This book is perfect for data engineers, analysts, and analytics engineers looking to leverage dbt for data platform development. If you're a manager or decision maker interested in fostering efficient data workflows or a professional with basic SQL knowledge aiming to deepen your expertise, this resource will be invaluable.

In "Geospatial Data Analytics on AWS," you will learn how to store, manage, and analyze geospatial data effectively using various AWS services. This book provides insight into building geospatial data lakes, leveraging AWS databases, and applying best practices to derive insights from spatial data in the cloud. What this Book will help me do Design and manage geospatial data lakes on AWS leveraging S3 and other storage solutions. Analyze geospatial data using AWS services such as Athena and Redshift. Utilize machine learning models for geospatial data processing and analytics using SageMaker. Visualize geospatial data through services like Amazon QuickSight and OpenStreetMap integration. Avoid common pitfalls when managing geospatial data in the cloud. Author(s) Scott Bateman, Janahan Gnanachandran, and Jeff DeMuth bring their extensive experience in cloud computing and geospatial analytics to this book. With backgrounds in cloud architecture, data science, and geospatial applications, they aim to make complex topics accessible. Their collaborative approach ensures readers can practically apply concepts to real-world challenges. Who is it for? This book is ideal for GIS and data professionals, including developers, analysts, and scientists. It suits readers with a basic understanding of geographical concepts but no prior AWS experience. If you're aiming to enhance your cloud-based geospatial data management and analytics skills, this is the guide for you.

A companion to Remote Sensing and Digital Image Processing with R, this lab manual covers examples of natural resource data analysis applications including practical, problem-solving exercises and case studies that use the free and open-source platform R.

Dive into the world of SAP UIs and begin your journey to becoming a development expert. In this book, you will learn the latest cutting-edge web technologies and gain a comprehensive understanding of the user experience concept that undergirds the SAP Fiori design system. SAP UI Frameworks for Enterprise Developers is filled with hands-on tutorials that will guide you through every step of the development journey, from setting up your coding editor to building your first application using UI5, SAP Fiori Elements, UI5 Web Components, or Fundamental Library Styles. Authors Marius Obert and Volker Buzek understand that staying ahead in the rapidly evolving UI technology landscape can be challenging, so they’ve included insights into upcoming industry-wide trends and future innovations. This book will provide you with the knowledge and skills needed to build intuitive applications with an eye-catching, SAP Fiori-conforming user interface.Don’t miss this opportunity to take your UI development skills to the next level! What You Will Learn Gain an overview of the technologies that can be used to implement enterprise-ready SAP Fiori UIs ready to be deployed in the cloud as well as on-premises Discover resources for connecting with domain experts to stay on top your game and learn about innovations in the SAP ecosystem Survey industry-wide technologies trends, like micro frontends and PWA, and relate these trends to both enterprise software and new projects led by SAP Who This Book Is For This book is intended for anyone interested in building intuitive enterprise user interfaces with modern web technologies in the greater SAP universe.

Time series data is at the heart of many applications, from finance and system monitoring to weather forecasting and medical data analysis. "Time Series Indexing" offers a hands-on guide to implementing and leveraging the iSAX indexing technique in Python to efficiently manage, search, and analyze time series data. What this Book will help me do Gain the know-how to implement algorithms like SAX and iSAX with illustrative Python examples. Learn to construct robust time series indexes tailored to real-world data sets. Understand the theoretical underpinnings of time series processing and indexing techniques. Explore and employ visualization techniques to interpret time series structures and insights. Gain the skills to adapt iSAX methodologies to other programming environments and practices. Author(s) Mihalis Tsoukalos is an accomplished developer and author specializing in Python programming and data processing techniques. With years of experience translating complex academic research into practical applications, Mihalis excels at bridging the gap between theory and practice. His writing approach ensures readers grasp both the foundational principles and the hands-on methods needed to succeed. Who is it for? This book best suits researchers, analysts, and developers who work with time series data and seek to elevate their proficiency in indexing and managing such data. It is perfect for professionals with a foundational knowledge of Python and programming concepts. This material also supports learners eager to derive actionable insights from theory-heavy academic research.

Master the Fundamentals of Modern Visual Analytics--and Craft Compelling Visual Narratives in Tableau! Do you need to persuade or inform people? Do you have data? Then you need to master visual analytics and visual storytelling. Today, the #1 tool for telling visual stories with data is Tableau, and demand for Tableau skills is soaring. In Visual Analytics Fundamentals, renowned visual storyteller and analytics professor Lindy Ryan introduces all the fundamental visual analytics knowledge, cognitive and perceptual concepts, and hands-on Tableau techniques you'll need. Ryan puts core analytics and visual concepts upfront, so you'll always know exactly what you're trying to accomplish and can apply this knowledge with any tool. Building on this foundation, she presents classroom-proven guided exercises for translating ideas into reality with Tableau 2022. Youll learn how to organize data and structure analysis with stories in mind, embrace exploration and visual discovery, and articulate your findings with rich data, well-curated visualizations, and skillfully crafted narrative frameworks. Ryan's insider tips take you far beyond the basics--and you'll rely on her expert checklists for years to come. Communicate more powerfully by applying scientific knowledge of the human brain Get started with the Tableau platform and Tableau Desktop 2022 Connect data and quickly prepare it for analysis Ask questions that help you keep data firmly in context Choose the right charts, graphs, and maps for each project--and avoid the wrong ones Craft storyboards that reflect your message and audience Direct attention to what matters most Build data dashboards that guide people towards meaningful outcomes Master advanced visualizations, including timelines, Likert scales, and lollipop charts This book has only one prerequisite: your desire to communicate insights from data in ways that are memorable and actionable. It's for executives and professionals sharing important results, students writing reports or presentations, teachers cultivating data literacy, journalists making sense of complex trends. . . . practically everyone! Don't even have Tableau? Download your free trial of Tableau Desktop and let's get started! ...

Do you know what happens to your personal data when you are browsing, buying, or using apps? Discover how your data is harvested and exploited, and what you can do to access, delete, and monetize it. Data for All empowers everyone—from tech experts to the general public—to control how third parties use personal data. Read this eye-opening book to learn: The types of data you generate with every action, every day Where your data is stored, who controls it, and how much money they make from it How you can manage access and monetization of your own data Restricting data access to only companies and organizations you want to support The history of how we think about data, and why that is changing The new data ecosystem being built right now for your benefit The data you generate every day is the lifeblood of many large companies—and they make billions of dollars using it. In Data for All, bestselling author John K. Thompson outlines how this one-sided data economy is about to undergo a dramatic change. Thompson pulls back the curtain to reveal the true nature of data ownership, and how you can turn your data from a revenue stream for companies into a financial asset for your benefit. About the Technology Do you know what happens to your personal data when you’re browsing and buying? New global laws are turning the tide on companies who make billions from your clicks, searches, and likes. This eye-opening book provides an inspiring vision of how you can take back control of the data you generate every day. About the Book Data for All gives you a step-by-step plan to transform your relationship with data and start earning a “data dividend”—hundreds or thousands of dollars paid out simply for your online activities. You’ll learn how to oversee who accesses your data, how much different types of data are worth, and how to keep private details private. What's Inside The types of data you generate with every action, every day How you can manage access and monetization of your own data The history of how we think about data, and why that is changing The new data ecosystem being built right now for your benefit About the Reader For anyone who is curious or concerned about how their data is used. No technical knowledge required. About the Author John K. Thompson is an international technology executive with over 37 years of experience in the fields of data, advanced analytics, and artificial intelligence. Quotes An honest, direct, pull-no-punches source on one of the most important personal issues of our time....I changed some of my own behaviors after reading the book, and I suggest you do so as well. You have more to lose than you may think. - From the Foreword by Thomas H. Davenport, author of Competing on Analytics and The AI Advantage A must-read for anyone interested in the future of data. It helped me understand the reasons behind the current data ecosystem and the laws that are shaping its future. A great resource for both professionals and individuals. I highly recommend it. - Ravit Jain, Founder & Host of The Ravit Show, Data Science Evangelist

In "Building a Next-Gen SOC with IBM QRadar", you'll learn how to utilize IBM QRadar to create an efficient Security Operations Center (SOC). The book covers deploying QRadar in various environments, understanding its architecture, and leveraging its powerful features to detect and respond to real-time threats with confidence, ultimately enabling advanced security practices. What this Book will help me do Understand and deploy IBM QRadar in different environments, including on-premises and cloud. Leverage QRadar's features to analyze network traffic, detect threats, and enhance security monitoring. Effectively use QRadar rules and searches to identify, correlate, and respond to security events. Integrate AI technologies with QRadar to automate and improve threat management processes. Maintain, troubleshoot, and scale the QRadar environment to meet evolving security needs. Author(s) Ashish Kothekar is an experienced cybersecurity specialist with a deep understanding of IBM QRadar and SOC operations. He has dedicated his career to helping organizations implement effective security practices. Through his accessible writing and detailed examples, he aims to empower security professionals to maximize their use of QRadar. Who is it for? This book is perfect for SOC analysts, security engineers, and cybersecurity enthusiasts who want to enhance their security skills. Readers should have a basic knowledge of networking and cybersecurity principles. If you're looking to deepen your understanding of IBM QRadar and build a next-gen SOC, this book is for you.

This IBM® Redpaper™ publication provides a broad understanding of a new architecture of the IBM Power System E980 (9080-M9S) server that supports IBM AIX®, IBM i, and Linux operating systems (OSes). The objective of this paper is to introduce the major innovative Power E980 offerings and relevant functions: The IBM POWER9™ processor, which is available at frequencies of 3.55 - 4.0 GHz. Significantly strengthened cores and larger caches. Supports up to 64 TB memory. Integrated I/O subsystem and hot-pluggable Peripheral Component Interconnect Express (PCIe) Gen4 slots, double the bandwidth of Gen3 I/O slots. Supports EXP12SX and ESP24SX external disk drawers, which have 12 Gb SAS interfaces and double the existing EXP24S drawer bandwidth. New IBM EnergyScale™ technology offers new variable processor frequency modes that provide a significant performance boost beyond the static nominal frequency. This publication is for professionals who want to acquire a better understanding of IBM Power Systems™ products. The intended audience includes the following roles: Clients Sales and marketing professionals Technical support professionals IBM Business Partners Independent software vendors (ISVs) This paper expands the current set of IBM Power Systems documentation by providing a desktop reference that offers a detailed technical description of the Power E980 server. This paper does not replace the current marketing materials and configuration tools. It is intended as an extra source of information that, together with existing sources, can be used to enhance your knowledge of IBM server solutions.

Digital Pricing Strategy provides a best practice overview of how companies design, analyse and execute digital pricing strategies.

Incredibly useful, knowledge graphs help organizations keep track of medical research, cybersecurity threat intelligence, GDPR compliance, web user engagement, and much more. They do so by storing interlinked descriptions of entities—objects, events, situations, or abstract concepts—and encoding the underlying information. How do you create a knowledge graph? And how do you move it from theory into production? Using hands-on examples, this practical book shows data scientists and data engineers how to build their own knowledge graphs. Authors Jesús Barrasa and Jim Webber from Neo4j illustrate common patterns for building knowledge graphs that solve many of today's pressing knowledge management problems. You'll quickly discover how these graphs become increasingly useful as you add data and augment them with algorithms and machine learning. Learn the organizing principles necessary to build a knowledge graph Explore how graph databases serve as a foundation for knowledge graphs Understand how to import structured and unstructured data into your graph Follow examples to build integration-and-search knowledge graphs Learn what pattern detection knowledge graphs help you accomplish Explore dependency knowledge graphs through examples Use examples of natural language knowledge graphs and chatbots Use graph algorithms and ML to gain insight into connected data

This IBM® Redbooks® publication offers a short overview of IBM's integrated environment for container workloads, IBM Storage Fusion. The product comes in two variants, IBM Storage Fusion HCI System including all required hardware, and IBM Storage Fusion SDS (software-only) for deployment in public or private Clouds. This paper has been updated with the 2.5.1 release only for IBM Storage Fusion and the 2.5.2 release of IBM Storage Fusion HCI System.

This volume provides a roadmap for the deployment of semantic technologies in the field of data science and enables the user to create intelligence through these technologies by exploring the opportunities and eradicating the challenges in the current and future time frame.