Because it continually implements entrepreneurial creativity and innovative business models, the economic landscape is ever-changing in today's globalized world. As consumers become more willing to accept new strategic trends, this has led to the emergence of disruptive technologies. Since this equipment has an insufficient amount of information and high risks, it is necessary to assess the potential of disruptive technologies in the commercial environment. Impact of Disruptive Technologies on the Sharing Economy provides emerging research exploring the theoretical and practical aspects of disruptive technologies and knowledge-based entrepreneurial efforts and applications within management, business, and economics. Featuring coverage on a broad range of topics such as consumer ethics, corporate governance, and insurance issues, this book is ideally designed for IT specialists, IT consultants, software developers, computer engineers, managers, executives, managing directors, students, professors, scientists, professionals, industry practitioners, academicians, and researchers seeking current research on the consequences of disruptive technologies.

Build, design, and improve advanced business intelligence solutions using Tableau's latest features, including Tableau Prep Builder, Tableau Hyper, and Tableau Server Key Features Master new features in Tableau 2021 to solve real-world analytics challenges Perform geo-spatial, time series, and self-service analytics using real-life examples Build and publish dashboards and explore storytelling using Python and R integration support Book DescriptionTableau is one of the leading business intelligence (BI) tools that can help you solve data analysis challenges. With this book, you will master Tableau's features and offerings in various paradigms of the BI domain. Updated with fresh topics including Quick Level of Detail expressions, the newest Tableau Server features, Einstein Discovery, and more, this book covers essential Tableau concepts and advanced functionalities. Leveraging Tableau Hyper files and using Prep Builder, you'll be able to perform data preparation and handling easily. You'll gear up to perform complex joins, spatial joins, unions, and data blending tasks using practical examples. Next, you'll learn how to execute data densification and further explore expert-level examples to help you with calculations, mapping, and visual design using Tableau extensions. You'll also learn about improving dashboard performance, connecting to Tableau Server and understanding data visualization with examples. Finally, you'll cover advanced use cases such as self-service analysis, time series analysis, and geo-spatial analysis, and connect Tableau to Python and R to implement programming functionalities within it. By the end of this Tableau book, you'll have mastered the advanced offerings of Tableau 2021 and be able to tackle common and advanced challenges in the BI domain. What you will learn Get up to speed with various Tableau components Master data preparation techniques using Tableau Prep Builder Discover how to use Tableau to create a PowerPoint-like presentation Understand different Tableau visualization techniques and dashboard designs Interact with the Tableau server to understand its architecture and functionalities Study advanced visualizations and dashboard creation techniques Brush up on powerful self-service analytics, time series analytics, and geo-spatial analytics Who this book is forThis book is designed for business analysts, business intelligence professionals and data analysts who want to master Tableau to solve a range of data science and business intelligence problems. The book is ideal if you have a good understanding of Tableau and want to take your skills to the next level.

Implement critical business processes with mySAP Business Suite to integrate key functions that add value to every facet of your organization Key Features Learn master data concepts and UI technologies in SAP systems Explore key functions of different sales processes, order fulfillment options, transportation planning, logistics execution processes, and customer invoicing Configure the Order to Cash process in SAP systems and apply it to your business needs Book DescriptionUsing different SAP systems in an integrated way to gain maximum benefits while running your business is made possible by this book, which covers how to effectively implement SAP Order to Cash Process with SAP Customer Relationship Management (CRM), SAP Advanced Planning and Optimization (APO), SAP Transportation Management System (TMS), SAP Logistics Execution System (LES), and SAP Enterprise Central Component (ECC). You'll understand the integration of different systems and how to optimize the complete Order to Cash Process with mySAP Business Suite. With the help of this book, you'll learn to implement mySAP Business Suite and understand the shortcomings in your existing SAP ECC environment. As you advance through the chapters, you'll get to grips with master data attributes in different SAP environments and then shift focus to the Order to Cash cycle, including order management in SAP CRM, order fulfillment in SAP APO, transportation planning in SAP TMS, logistics execution in SAP LES, and billing in SAP ECC. By the end of this SAP book, you'll have gained a thorough understanding of how different SAP systems work together with the Order to Cash process. What you will learn Discover master data in different SAP environments Find out how different sales processes, such as quotations, contracts, and order management, work in SAP CRM Become well-versed with the steps involved in order fulfillment, such as basic and advanced ATP checks in SAP APO Get up and running with transportation requirement and planning and freight settlement with SAP TMS Explore warehouse management with SAP LES to ensure high transparency and predictability of processes Understand how to process customer invoicing with SAP ECC Who this book is forThis book is for SAP consultants, SME managers, solution architects, and key users of SAP with knowledge of end-to-end business processes. Customers operating SAP CRM, SAP TMS, and SAP APO as part of daily operations will also benefit from this book by understanding the key capabilities and integration touchpoints. Working knowledge of SAP ECC, SAP CRM, SAP APO, SAP TMS, and SAP LES is necessary to get started with this book.

Explore Amazon Connect, from implementing call flows and creating AI bots to integrating artificial intelligence solutions and analyzing critical customer sentiment Key Features Discover how to integrate chat with Connect to allow organizations to reduce operations costs Leverage machine learning to perform natural language processing (NLP) for analyzing customer feedback and trends Learn how to integrate your enterprise application with Amazon Connect Book DescriptionAmazon Connect is a pay-as-you-go cloud contact center solution that powers Amazon's customer contact system and provides an impressive user experience while reducing costs. Connect's scalability has been especially helpful during COVID-19, helping customers with research, remote work, and other solutions, and has driven adoption rates higher. Amazon Connect: Up and Running will help you develop a foundational understanding of Connect's capabilities and how businesses can effectively estimate the costs and risks associated with migration. Complete with hands-on tutorials, costing profiles, and real-world use cases relating to improving business operations, this easy-to-follow guide will teach you everything you need to get your call center online, interface with critical business systems, and take your customer experience to the next level. As you advance, you'll understand the benefits of using Amazon Connect and cost estimation guidelines for migration and new deployments. Later, the book guides you through creating AI bots, implementing interfaces, and leveraging machine learning for business analytics. By the end of this book, you'll be able to bring a Connect call center online with all its major components and interfaces to significantly reduce personnel overhead and provide your customers with an enhanced user experience (UX). What you will learn Become well-versed with the capabilities and benefits of Amazon Connect Determine cost-effective solutions by integrating Connect with AWS Create, modify, and connect contact flows to improve efficiency Build a conversational interface with Amazon Lex Find out how to transfer contact records out of Connect via Kinesis Gather user insights and improve business operations with Amazon QuickSight Analyze customer-agent conversations with ML speech analytics capabilities Discover ways to provide superior customer service at a lower cost Who this book is forThis Amazon Connect book is for anyone looking to save costs and improve their customer experience through a more advanced call center using Amazon Connect and other AWS capabilities. A technical understanding of Amazon Web Services (AWS) and beginner-level business administration experience are necessary to address cost concerns and risks.

Explore Kinesis managed services such as Kinesis Data Streams, Kinesis Data Analytics, Kinesis Data Firehose, and Kinesis Video Streams with the help of practical use cases Key Features Get well versed with the capabilities of Amazon Kinesis Explore the monitoring, scaling, security, and deployment patterns of various Amazon Kinesis services Learn how other Amazon Web Services and third-party applications such as Splunk can be used as destinations for Kinesis data Book DescriptionAmazon Kinesis is a collection of secure, serverless, durable, and highly available purpose-built data streaming services. This data streaming service provides APIs and client SDKs that enable you to produce and consume data at scale. Scalable Data Streaming with Amazon Kinesis begins with a quick overview of the core concepts of data streams, along with the essentials of the AWS Kinesis landscape. You'll then explore the requirements of the use case shown through the book to help you get started and cover the key pain points encountered in the data stream life cycle. As you advance, you'll get to grips with the architectural components of Kinesis, understand how they are configured to build data pipelines, and delve into the applications that connect to them for consumption and processing. You'll also build a Kinesis data pipeline from scratch and learn how to implement and apply practical solutions. Moving on, you'll learn how to configure Kinesis on a cloud platform. Finally, you'll learn how other AWS services can be integrated into Kinesis. These services include Redshift, Dynamo Database, AWS S3, Elastic Search, and third-party applications such as Splunk. By the end of this AWS book, you'll be able to build and deploy your own Kinesis data pipelines with Kinesis Data Streams (KDS), Kinesis Data Firehose (KFH), Kinesis Video Streams (KVS), and Kinesis Data Analytics (KDA). What you will learn Get to grips with data streams, decoupled design, and real-time stream processing Understand the properties of KFH that differentiate it from other Kinesis services Monitor and scale KDS using CloudWatch metrics Secure KDA with identity and access management (IAM) Deploy KVS as infrastructure as code (IaC) Integrate services such as Redshift, Dynamo Database, and Splunk into Kinesis Who this book is forThis book is for solutions architects, developers, system administrators, data engineers, and data scientists looking to evaluate and choose the most performant, secure, scalable, and cost-effective data streaming technology to overcome their data ingestion and processing challenges on AWS. Prior knowledge of cloud architectures on AWS, data streaming technologies, and architectures is expected.

Prepare to achieve AWS Machine Learning Specialty certification with this complete, up-to-date guide and take the exam with confidence Key Features Get to grips with core machine learning algorithms along with AWS implementation Build model training and inference pipelines and deploy machine learning models to the Amazon Web Services (AWS) cloud Learn all about the AWS services available for machine learning in order to pass the MLS-C01 exam Book DescriptionThe AWS Certified Machine Learning Specialty exam tests your competency to perform machine learning (ML) on AWS infrastructure. This book covers the entire exam syllabus using practical examples to help you with your real-world machine learning projects on AWS. Starting with an introduction to machine learning on AWS, you'll learn the fundamentals of machine learning and explore important AWS services for artificial intelligence (AI). You'll then see how to prepare data for machine learning and discover a wide variety of techniques for data manipulation and transformation for different types of variables. The book also shows you how to handle missing data and outliers and takes you through various machine learning tasks such as classification, regression, clustering, forecasting, anomaly detection, text mining, and image processing, along with the specific ML algorithms you need to know to pass the exam. Finally, you'll explore model evaluation, optimization, and deployment and get to grips with deploying models in a production environment and monitoring them. By the end of this book, you'll have gained knowledge of the key challenges in machine learning and the solutions that AWS has released for each of them, along with the tools, methods, and techniques commonly used in each domain of AWS ML. What you will learn Understand all four domains covered in the exam, along with types of questions, exam duration, and scoring Become well-versed with machine learning terminologies, methodologies, frameworks, and the different AWS services for machine learning Get to grips with data preparation and using AWS services for batch and real-time data processing Explore the built-in machine learning algorithms in AWS and build and deploy your own models Evaluate machine learning models and tune hyperparameters Deploy machine learning models with the AWS infrastructure Who this book is forThis AWS book is for professionals and students who want to prepare for and pass the AWS Certified Machine Learning Specialty exam or gain deeper knowledge of machine learning with a special focus on AWS. Beginner-level knowledge of machine learning and AWS services is necessary before getting started with this book.