Advertisement
| bigquery to salesforce marketing cloud: Hands-On Salesforce Data Cloud Joyce Kay Avila, 2024-08-09 Learn how to implement and manage a modern customer data platform (CDP) through the Salesforce Data Cloud platform. This practical book provides a comprehensive overview that shows architects, administrators, developers, data engineers, and marketers how to ingest, store, and manage real-time customer data. Author Joyce Kay Avila demonstrates how to use Salesforce's native connectors, canonical data model, and Einstein's built-in trust layer to accelerate your time to value. You'll learn how to leverage Salesforce's low-code/no-code functionality to expertly build a Data Cloud foundation that unlocks the power of structured and unstructured data. Use Data Cloud tools to build your own predictive models or leverage third-party machine learning platforms like Amazon SageMaker, Google Vertex AI, and Databricks. This book will help you: Develop a plan to execute a CDP project effectively and efficiently Connect Data Cloud to external data sources and build out a Customer 360 Data Model Leverage data sharing capabilities with Snowflake, BigQuery, Databricks, and Azure Use Salesforce Data Cloud capabilities for identity resolution and segmentation Create calculated, streaming, visualization, and predictive insights Use Data Graphs to power Salesforce Einstein capabilities Learn Data Cloud best practices for all phases of the development lifecycle |
| bigquery to salesforce marketing cloud: Developing Data Migrations and Integrations with Salesforce David Masri, 2018-12-18 Migrate your data to Salesforce and build low-maintenance and high-performing data integrations to get the most out of Salesforce and make it a go-to place for all your organization's customer information. When companies choose to roll out Salesforce, users expect it to be the place to find any and all Information related to a customer—the coveted Client 360° view. On the day you go live, users expect to see all their accounts, contacts, and historical data in the system. They also expect that data entered in other systems will be exposed in Salesforce automatically and in a timely manner. This book shows you how to migrate all your legacy data to Salesforce and then design integrations to your organization's mission-critical systems. As the Salesforce platform grows more powerful, it also grows in complexity. Whether you are migrating data to Salesforce, or integrating with Salesforce, it is important to understand how these complexities need to be reflected in your design. Developing Data Migrations and Integrations with Salesforce covers everything you need to know to migrate your data to Salesforce the right way, and how to design low-maintenance, high-performing data integrations with Salesforce. This book is written by a practicing Salesforce integration architect with dozens of Salesforce projects under his belt. The patterns and practices covered in this book are the results of the lessons learned during those projects. What You’ll Learn Know how Salesforce’s data engine is architected and why Use the Salesforce Data APIs to load and extract data Plan and execute your data migration to Salesforce Design low-maintenance, high-performing data integrations with Salesforce Understand common data integration patterns and the pros and cons of each Know real-time integration options for Salesforce Be aware of common pitfalls Build reusable transformation code covering commonly needed Salesforce transformation patterns Who This Book Is For Those tasked with migrating data to Salesforce or building ongoing data integrations with Salesforce, regardless of the ETL tool or middleware chosen; project sponsors or managers nervous about data tracks putting their projects at risk; aspiring Salesforce integration and/or migration specialists; Salesforce developers or architects looking to expand their skills and take on new challenges |
| bigquery to salesforce marketing cloud: Architecting Data and Machine Learning Platforms Marco Tranquillin, Valliappa Lakshmanan, Firat Tekiner, 2023-10-12 All cloud architects need to know how to build data platforms that enable businesses to make data-driven decisions and deliver enterprise-wide intelligence in a fast and efficient way. This handbook shows you how to design, build, and modernize cloud native data and machine learning platforms using AWS, Azure, Google Cloud, and multicloud tools like Snowflake and Databricks. Authors Marco Tranquillin, Valliappa Lakshmanan, and Firat Tekiner cover the entire data lifecycle from ingestion to activation in a cloud environment using real-world enterprise architectures. You'll learn how to transform, secure, and modernize familiar solutions like data warehouses and data lakes, and you'll be able to leverage recent AI/ML patterns to get accurate and quicker insights to drive competitive advantage. You'll learn how to: Design a modern and secure cloud native or hybrid data analytics and machine learning platform Accelerate data-led innovation by consolidating enterprise data in a governed, scalable, and resilient data platform Democratize access to enterprise data and govern how business teams extract insights and build AI/ML capabilities Enable your business to make decisions in real time using streaming pipelines Build an MLOps platform to move to a predictive and prescriptive analytics approach |
| bigquery to salesforce marketing cloud: Hands-On Salesforce Data Cloud Joyce Kay Avila, 2024-08-09 Learn how to implement and manage a modern customer data platform (CDP) through the Salesforce Data Cloud platform. This practical book provides a comprehensive overview that shows architects, administrators, developers, data engineers, and marketers how to ingest, store, and manage real-time customer data. Author Joyce Kay Avila demonstrates how to use Salesforce's native connectors, canonical data model, and Einstein's built-in trust layer to accelerate your time to value. You'll learn how to leverage Salesforce's low-code/no-code functionality to expertly build a Data Cloud foundation that unlocks the power of structured and unstructured data. Use Data Cloud tools to build your own predictive models or leverage third-party machine learning platforms like Amazon SageMaker, Google Vertex AI, and Databricks. This book will help you: Develop a plan to execute a CDP project effectively and efficiently Connect Data Cloud to external data sources and build out a Customer 360 Data Model Leverage data sharing capabilities with Snowflake, BigQuery, Databricks, and Azure Use Salesforce Data Cloud capabilities for identity resolution and segmentation Create calculated, streaming, visualization, and predictive insights Use Data Graphs to power Salesforce Einstein capabilities Learn Data Cloud best practices for all phases of the development lifecycle |
| bigquery to salesforce marketing cloud: Programming Salesforce Marketing Cloud ZHONGCHEN ZHOU, 2019-04-03 This book introduces concepts to integrate with marketing cloud using API and build custom components in a platform agnostic way, including the following aspects: Marketing Cloud Package Custom Journey Builder Activity API Integration (Server to Server & Web App) Custom Marketing Cloud App Server Side JavaScript These concepts will be applicable to any programming language and platform. After introducing the concepts, we will implement these concepts using APEX programming language within Salesforce sale cloud. Tips, patterns and special considerations will be introduced when using APEX in sales cloud to implement these concepts, for example: how to serve custom activity configuration file; how to expose less REST service and write less APEX class and at the same time achieve right level of encapsulation; how to decode JWT passing from marketing cloud Journey Builder; how to build user interface and allow marketing cloud users without sales cloud account to access; how to display visualforce page inside marketing cloud iframes how to set up the right architecture. |
| bigquery to salesforce marketing cloud: Strategic Blueprint for Enterprise Analytics Liang Wang, |
| bigquery to salesforce marketing cloud: Fundamentals of Analytics Engineering Dumky De Wilde, Fanny Kassapian, Jovan Gligorevic, Juan Manuel Perafan, Lasse Benninga, Ricardo Angel Granados Lopez, Taís Laurindo Pereira, 2024-03-29 Gain a holistic understanding of the analytics engineering lifecycle by integrating principles from both data analysis and engineering Key Features Discover how analytics engineering aligns with your organization's data strategy Access insights shared by a team of seven industry experts Tackle common analytics engineering problems faced by modern businesses Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionWritten by a team of 7 industry experts, Fundamentals of Analytics Engineering will introduce you to everything from foundational concepts to advanced skills to get started as an analytics engineer. After conquering data ingestion and techniques for data quality and scalability, you’ll learn about techniques such as data cleaning transformation, data modeling, SQL query optimization and reuse, and serving data across different platforms. Armed with this knowledge, you will implement a simple data platform from ingestion to visualization, using tools like Airbyte Cloud, Google BigQuery, dbt, and Tableau. You’ll also get to grips with strategies for data integrity with a focus on data quality and observability, along with collaborative coding practices like version control with Git. You’ll learn about advanced principles like CI/CD, automating workflows, gathering, scoping, and documenting business requirements, as well as data governance. By the end of this book, you’ll be armed with the essential techniques and best practices for developing scalable analytics solutions from end to end.What you will learn Design and implement data pipelines from ingestion to serving data Explore best practices for data modeling and schema design Scale data processing with cloud based analytics platforms and tools Understand the principles of data quality management and data governance Streamline code base with best practices like collaborative coding, version control, reviews and standards Automate and orchestrate data pipelines Drive business adoption with effective scoping and prioritization of analytics use cases Who this book is for This book is for data engineers and data analysts considering pivoting their careers into analytics engineering. Analytics engineers who want to upskill and search for gaps in their knowledge will also find this book helpful, as will other data professionals who want to understand the value of analytics engineering in their organization's journey toward data maturity. To get the most out of this book, you should have a basic understanding of data analysis and engineering concepts such as data cleaning, visualization, ETL and data warehousing. |
| bigquery to salesforce marketing cloud: Data-Driven Customer Engagement Ralf Strauss, |
| bigquery to salesforce marketing cloud: Salesforce Marketing Cloud For Dummies Chester Bullock, Mark Pollard, 2017-10-13 Salesforce Marketing Cloud: Take your digital marketing on a journey! Everything seems to be moving to the cloud these days—and digital marketing is no exception! Salesforce Marketing Cloud For Dummies guides you through the use of Salesforce's exciting suite of cloud-based digital marketing solutions, which have the power to help you plan, personalize, and optimize your customers' journey. Written by a leader of the Salesforce training and development team, Salesforce Marketing Cloud users will find essential information on using the suite of tools and tips and tricks that only an insider would be able to share. With easy-to-follow instructions, this guide helps you discover how to incorporate your data sets into the tools to create models, campaigns, and customer maps that enable you to create a positive experience for your customers. As Salesforce.com's multi-channel digital marketing platform, the Salesforce Marketing Cloud focuses on helping you manage one-on-one customer journeys. Leveraging a variety of features, this suite of tools offers email marketing, mobile marketing, social media marketing, content and messaging, predictive intelligence, and more. Your ability to navigate these features and functions will determine your digital marketing campaign's success, so it's critical that you make the most of this tool! Navigate and manage the Salesforce Marketing Cloud Define and understand your customers' journeys—and how you fit into them Engage your customers across devices, ensuring consistent communication Use predictive data to optimize engagement Salesforce Marketing Cloud For Dummies helps you make the most of your investment in the digital marketing world! |
| bigquery to salesforce marketing cloud: Rise of the Data Cloud Frank Slootman, Steve Hamm, 2020-12-18 The rise of the Data Cloud is ushering in a new era of computing. The world’s digital data is mass migrating to the cloud, where it can be more effectively integrated, managed, and mobilized. The data cloud eliminates data siloes and enables data sharing with business partners, capitalizing on data network effects. It democratizes data analytics, making the most sophisticated data science tools accessible to organizations of all sizes. Data exchanges enable businesses to discover, explore, and easily purchase or sell data—opening up new revenue streams. Business leaders have long dreamed of data driving their organizations. Now, thanks to the Data Cloud, nothing stands in their way. |
| bigquery to salesforce marketing cloud: AI and Data Engineering Solutions for Effective Marketing Alla, Lhoussaine, Hmioui, Aziz, Bentalha, Badr, 2024-07-17 In the world of contemporary marketing, a challenge exists — the relationship between data engineering, artificial intelligence, and the essential elements of effective marketing. Businesses find themselves at a crossroads, grappling with the imperative to navigate this complex landscape. This challenge serves as the backdrop for the exploration in AI and Data Engineering Solutions for Effective Marketing, a comprehensive reference tailored for academic scholars. Seamlessly integrating theoretical models with real-world applications, the book delves into critical facets of strategic and operational marketing. From the adoption of data science techniques to grappling with big data's vast potential, it offers a guide for academics seeking profound insights into the future of marketing strategies and their efficient execution. Designed for researchers, practitioners, and students with an interest in the intersection of artificial intelligence, data engineering, and marketing, this book serves as a guide for implementing new marketing management solutions and optimizing their operational efficiency. While the primary audience is researchers and practitioners in the field, the book is also tailored to benefit students seeking a deep understanding of the latest developments in marketing. |
| bigquery to salesforce marketing cloud: Automating Salesforce Marketing Cloud Greg Gifford, Jason Hanshaw, 2022-04-18 Make the most of Salesforce Marketing Cloud through automation and increase your productivity on the platform without adding any extra resources Key Features Increase your knowledge of automation theory and the applications of SFMC Explore automation with SFMC and its capabilities beyond general usage Understand the automation features and integrations of SFMC to use the platform from outside the user interface (UI) for maximum efficiency Book DescriptionSalesforce Marketing Cloud (SFMC) allows you to use multiple channels and tools to create a 1:1 marketing experience for your customers and subscribers. Through automation and helper tasks, you can greatly increase your productivity while also reducing the level of effort required in terms of volume and frequency. Automating Salesforce Marketing Cloud starts by discussing what automation is generally and then progresses to what automation is in SFMC. After that, you’ll focus on how to perform automation inside of SFMC all the way to fully running processes and capabilities from an external service. Later chapters explore the benefits and capabilities of automation and having an automation mindset both within and outside of SFMC. Equipped with this knowledge and example code, you'll be prepared to maximize your SFMC efficiency. By the end of this Salesforce book, you’ll have the skills you need to build automation both inside and outside of SFMC, along with the knowledge for using the platform optimally.What you will learn Understand automation to make the most of the SFMC platform Optimize ETL activities, data import integrations, data segmentations, email sends, and more Explore different ways to use scripting and API calls to increase Automation Studio efficiency Identify opportunities for automation with custom integrations and third-party solutions Optimize usage of SFMC by building on the core concepts of custom integrations and third-party tools Maximize utilization of employee skills and capabilities and reduce operational costs while increasing output Who this book is for This book is for Salesforce Marketing Cloud users who want to know how to make their day to day lives more efficient and get the most out of the tool by working smarter, not harder. A solid understanding of SFMC and basic knowledge of what automation is will help you get the most out of this book. |
| bigquery to salesforce marketing cloud: Foundations of Modern Networking William Stallings, 2015-10-27 Foundations of Modern Networking is a comprehensive, unified survey of modern networking technology and applications for today’s professionals, managers, and students. Dr. William Stallings offers clear and well-organized coverage of five key technologies that are transforming networks: Software-Defined Networks (SDN), Network Functions Virtualization (NFV), Quality of Experience (QoE), the Internet of Things (IoT), and cloudbased services. Dr. Stallings reviews current network ecosystems and the challenges they face–from Big Data and mobility to security and complexity. Next, he offers complete, self-contained coverage of each new set of technologies: how they work, how they are architected, and how they can be applied to solve real problems. Dr. Stallings presents a chapter-length analysis of emerging security issues in modern networks. He concludes with an up-to date discussion of networking careers, including important recent changes in roles and skill requirements. Coverage: Elements of the modern networking ecosystem: technologies, architecture, services, and applications Evolving requirements of current network environments SDN: concepts, rationale, applications, and standards across data, control, and application planes OpenFlow, OpenDaylight, and other key SDN technologies Network functions virtualization: concepts, technology, applications, and software defined infrastructure Ensuring customer Quality of Experience (QoE) with interactive video and multimedia network traffic Cloud networking: services, deployment models, architecture, and linkages to SDN and NFV IoT and fog computing in depth: key components of IoT-enabled devices, model architectures, and example implementations Securing SDN, NFV, cloud, and IoT environments Career preparation and ongoing education for tomorrow’s networking careers Key Features: Strong coverage of unifying principles and practical techniques More than a hundred figures that clarify key concepts Web support at williamstallings.com/Network/ QR codes throughout, linking to the website and other resources Keyword/acronym lists, recommended readings, and glossary Margin note definitions of key words throughout the text |
| bigquery to salesforce marketing cloud: Bad Dog Martin Kihn, 2011-04-05 (A true story.) Meet Hola. She’s a nightmare, but it’s not her fault if she tackles strangers and chews on furniture, or if she runs after buses and fried chicken containers and drug dealers. No one ever told her not to. Worse yet, she scares her family. Hola may be the most beautiful Bernese mountain dog in the world, but she’s never been trained. At least not by anyone who knew what he was doing. Hola’s supposed master, Marty, is a high-functioning alcoholic. A TV writer turned management consultant, Marty’s in debt and out of shape; he’s about to lose his job, and one day he emerges from a haze of peach-flavored vodka to find he’s on the verge of losing his wife, Gloria, too, if he can’t get his life—and his dog—under control. Desperately trying to save his marriage, Marty throws himself headlong into the world of competitive dog training. Unfortunately, he knows even less than Hola, the only dog ever to be expelled from her puppy preschool twice. Somehow, together, they need to get through the American Kennel Club’s rigorous Canine Good Citizen test. Of course, Hola first needs to learn how to sit. It won’t be easy. It certainly won’t be pretty. But maybe, just maybe, there will be cheesecake. |
| bigquery to salesforce marketing cloud: Customer 360 Martin Kihn, Andrea Chen Lin, 2024-11-06 Become more competitive by developing a superior customer experience through data, AI, and trust - and get your organization ready for AI agents like Agentforce Customer 360: How Data, AI, and Trust Changes Everything delivers key insight and vision on using emerging technologies to delight customers and become more competitive by providing a superior customer experience. Find out why AI agents like Agentforce need a strong foundation of customer data. This book helps readers attract and engage their customers across channels and throughout their journey, from acquisition and onboarding, through service, upsell, retention, and win-back. To demonstrate the influence and importance of these ideas, this book contains a multitude of real-world case studies from companies in a range of industries, with business models, and at various stages of digital maturity. Readers will learn about: Using exciting technologies like AI and GPT while building a commitment to ethical use, safety, and privacy through secure guardrails Getting ready to use exciting emerging technologies like AI agents and autonomous AI Organizing data around customers, prospects, and accounts—even if that data comes from many different sources in different formats Making new technologies an extension of your existing data investments so that both work better Choosing a strategy and implementation plan to minimize time-to-value and ensure success weighing build, buy, or partner Handling internal stakeholders and dealing with change in a way that benefits the business For business leaders, executives, managers, and entrepreneurs, Customer 360: How Data, AI, and Trust Changes Everything is an essential read to understand and connect technology, people, processes, and strategy—truly the future of customer engagement—and leave competitors wondering what just happened. |
| bigquery to salesforce marketing cloud: The AMPscript Guide Adam Spriggs, Eliot Harper, 2018-03 AMPscript is a scripting language for Salesforce Marketing Cloud. You can use it to create highly sophisticated, personalized content through an extensive set of functions.The language follows a simple syntax and semantics. With an understanding of the fundamentals, you can quickly gain proficiency in AMPscript - no prior experience in scripting languages is needed.This book extends the existing Salesforce documentation to provide an authoritative reference manual on AMPscript. Whether you are inexperienced in writing scripts or are already highly proficient in AMPscript, this book will enable you to enjoy rapid development through clear explanations and extensive documentation on all AMPscript functions, including real-world supporting code samples for you to reuse. |
| bigquery to salesforce marketing cloud: CRM goes digital Martin Stadelmann, Mario Pufahl, David D. Laux, 2020-03-30 Wie verändert sich das Customer-Relationship-Management durch die digitale Transformation? Dieses Buch verrät es Ihnen! Das Kundenmanagement hat seit der Digitalisierung vollkommen neue Formen angenommen. Dieses CRM-Buch von Martin Stadelmann, Mario Pufahl und David Laux widmet sich daher den neuen Ansätzen, die Vertrieb, Marketing und Service mittlerweile dominieren: Omnichannel- oder Mobile-CRM-Konzepte Big Data- und Social-Media-Instrumente Customer-Experience- oder Customer-Loyalty-Ansätze Künstliche Intelligenz etc. In diesem zukunftsweisenden, praxisorientierten und konzeptionell fundierten Customer-Relationship-Management-Buch erfahren Sie mehr über folgende Themen: zukünftige Entwicklung im Kundenmanagement mittels eines digitalen CRMs (dCRM) Auswirkungen der Digitalisierung auf die Produkt- und Serviceoptimierung bzw. auf Vertriebssteuerungund Kundenbindung Verbesserung der Vertriebsperformance durch eine radikale Kundenorientierung Die Antworten auf diese und weitere Fragen geben fachkundige Experten aus Wissenschaft und Praxis. CRM goes digital – In diesem Buch erhalten Sie konkrete Handlungsempfehlungen. CRM-Systeme sind wichtige Instrumente kundenorientierter Unternehmen. Dennoch unterscheiden sich die Anforderungen und Lösungsmöglichkeiten bei jeder Firma. Die hier vorgestellten Handlungsempfehlungen dienen lediglich als Orientierung für Entscheider. Um ein möglichst großes Spektrum zu erfassen, enthält das Buch exemplarisch ausgewählte Branchenbeispiele, die Ihnen nicht nur die Grundlagen vermitteln, sondern ebenfalls den Umgang mit Technologien wie Customer Journey Management oder Cloud-CRM erläutern. Nutzen Sie begleitend zur Lektüre die SN More Media App, um auf das Zusatzmaterial und die Erklärvideos zuzugreifen. |
| bigquery to salesforce marketing cloud: Monolith to Microservices Sam Newman, 2019-11-14 How do you detangle a monolithic system and migrate it to a microservice architecture? How do you do it while maintaining business-as-usual? As a companion to Sam Newman’s extremely popular Building Microservices, this new book details a proven method for transitioning an existing monolithic system to a microservice architecture. With many illustrative examples, insightful migration patterns, and a bevy of practical advice to transition your monolith enterprise into a microservice operation, this practical guide covers multiple scenarios and strategies for a successful migration, from initial planning all the way through application and database decomposition. You’ll learn several tried and tested patterns and techniques that you can use as you migrate your existing architecture. Ideal for organizations looking to transition to microservices, rather than rebuild Helps companies determine whether to migrate, when to migrate, and where to begin Addresses communication, integration, and the migration of legacy systems Discusses multiple migration patterns and where they apply Provides database migration examples, along with synchronization strategies Explores application decomposition, including several architectural refactoring patterns Delves into details of database decomposition, including the impact of breaking referential and transactional integrity, new failure modes, and more |
| bigquery to salesforce marketing cloud: BigQuery for Data Warehousing Mark Mucchetti, 2020-12-20 Create a data warehouse, complete with reporting and dashboards using Google’s BigQuery technology. This book takes you from the basic concepts of data warehousing through the design, build, load, and maintenance phases. You will build capabilities to capture data from the operational environment, and then mine and analyze that data for insight into making your business more successful. You will gain practical knowledge about how to use BigQuery to solve data challenges in your organization. BigQuery is a managed cloud platform from Google that provides enterprise data warehousing and reporting capabilities. Part I of this book shows you how to design and provision a data warehouse in the BigQuery platform. Part II teaches you how to load and stream your operational data into the warehouse to make it ready for analysis and reporting. Parts III and IV cover querying and maintaining, helping you keep your information relevant with other Google Cloud Platform services and advanced BigQuery. Part V takes reporting to the next level by showing you how to create dashboards to provide at-a-glance visual representations of your business situation. Part VI provides an introduction to data science with BigQuery, covering machine learning and Jupyter notebooks. What You Will Learn Design a data warehouse for your project or organization Load data from a variety of external and internal sources Integrate other Google Cloud Platform services for more complex workflows Maintain and scale your data warehouse as your organization grows Analyze, report, and create dashboards on the information in the warehouse Become familiar with machine learning techniques using BigQuery ML Who This Book Is For Developers who want to provide business users with fast, reliable, and insightful analysis from operational data, and data analysts interested in a cloud-based solution that avoids the pain of provisioning their own servers. |
| bigquery to salesforce marketing cloud: Building Interactive Business Intelligence Dashboards with Google Looker Helita Br Sitorus, Andy Ismail, Rike Setiawati, 2024-07-07 Building Interactive Business Intelligence Dashboards with Google Looker: Beginner's Practical Guide Unlock the power of your data and transform it into actionable insights with this beginner-friendly guide to Google Looker. Learn how to connect to diverse data sources, transform raw data into meaningful metrics, and create visually stunning, interactive dashboards that drive informed decision-making. This book is your roadmap to mastering Looker's intuitive interface and powerful features, enabling you to uncover hidden patterns, track key performance indicators, and communicate your findings effectively. Whether you're a business analyst, marketer, or data enthusiast, this practical guide will empower you to harness the full potential of Google Looker and elevate your business intelligence capabilities. |
| bigquery to salesforce marketing cloud: Cloud Computing Bible Barrie Sosinsky, 2010-12-10 The complete reference guide to the hot technology of cloud computing Its potential for lowering IT costs makes cloud computing a major force for both IT vendors and users; it is expected to gain momentum rapidly with the launch of Office Web Apps later this year. Because cloud computing involves various technologies, protocols, platforms, and infrastructure elements, this comprehensive reference is just what you need if you?ll be using or implementing cloud computing. Cloud computing offers significant cost savings by eliminating upfront expenses for hardware and software; its growing popularity is expected to skyrocket when Microsoft introduces Office Web Apps This comprehensive guide helps define what cloud computing is and thoroughly explores the technologies, protocols, platforms and infrastructure that make it so desirable Covers mobile cloud computing, a significant area due to ever-increasing cell phone and smartphone use Focuses on the platforms and technologies essential to cloud computing Anyone involved with planning, implementing, using, or maintaining a cloud computing project will rely on the information in Cloud Computing Bible. |
| bigquery to salesforce marketing cloud: Business Intelligence Demystified Anoop Kumar V K, 2021-09-25 Clear your doubts about Business Intelligence and start your new journey KEY FEATURES ● Includes successful methods and innovative ideas to achieve success with BI. ● Vendor-neutral, unbiased, and based on experience. ● Highlights practical challenges in BI journeys. ● Covers financial aspects along with technical aspects. ● Showcases multiple BI organization models and the structure of BI teams. DESCRIPTION The book demystifies misconceptions and misinformation about BI. It provides clarity to almost everything related to BI in a simplified and unbiased way. It covers topics right from the definition of BI, terms used in the BI definition, coinage of BI, details of the different main uses of BI, processes that support the main uses, side benefits, and the level of importance of BI, various types of BI based on various parameters, main phases in the BI journey and the challenges faced in each of the phases in the BI journey. It clarifies myths about self-service BI and real-time BI. The book covers the structure of a typical internal BI team, BI organizational models, and the main roles in BI. It also clarifies the doubts around roles in BI. It explores the different components that add to the cost of BI and explains how to calculate the total cost of the ownership of BI and ROI for BI. It covers several ideas, including unconventional ideas to achieve BI success and also learn about IBI. It explains the different types of BI architectures, commonly used technologies, tools, and concepts in BI and provides clarity about the boundary of BI w.r.t technologies, tools, and concepts. The book helps you lay a very strong foundation and provides the right perspective about BI. It enables you to start or restart your journey with BI. WHAT YOU WILL LEARN ● Builds a strong conceptual foundation in BI. ● Gives the right perspective and clarity on BI uses, challenges, and architectures. ● Enables you to make the right decisions on the BI structure, organization model, and budget. ● Explains which type of BI solution is required for your business. ● Applies successful BI ideas. WHO THIS BOOK IS FOR This book is a must-read for business managers, BI aspirants, CxOs, and all those who want to drive the business value with data-driven insights. TABLE OF CONTENTS 1. What is Business Intelligence? 2. Why do Businesses need BI? 3. Types of Business Intelligence 4. Challenges in Business Intelligence 5. Roles in Business Intelligence 6. Financials of Business Intelligence 7. Ideas for Success with BI 8. Introduction to IBI 9. BI Architectures 10. Demystify Tech, Tools, and Concepts in BI |
| bigquery to salesforce marketing cloud: Designing Cloud Data Platforms Danil Zburivsky, Lynda Partner, 2021-04-20 Centralized data warehouses, the long-time defacto standard for housing data for analytics, are rapidly giving way to multi-faceted cloud data platforms. Companies that embrace modern cloud data platforms benefit from an integrated view of their business using all of their data and can take advantage of advanced analytic practices to drive predictions and as yet unimagined data services. Designing Cloud Data Platforms is an hands-on guide to envisioning and designing a modern scalable data platform that takes full advantage of the flexibility of the cloud. As you read, you''ll learn the core components of a cloud data platform design, along with the role of key technologies like Spark and Kafka Streams. You''ll also explore setting up processes to manage cloud-based data, keep it secure, and using advanced analytic and BI tools to analyse it. about the technology Access to affordable, dependable, serverless cloud services has revolutionized the way organizations can approach data management, and companies both big and small are raring to migrate to the cloud. But without a properly designed data platform, data in the cloud can remain just as siloed and inaccessible as it is today for most organizations. Designing Cloud Data Platforms lays out the principles of a well-designed platform that uses the scalable resources of the public cloud to manage all of an organization''s data, and present it as useful business insights. about the book In Designing Cloud Data Platforms, you''ll learn how to integrate data from multiple sources into a single, cloud-based, modern data platform. Drawing on their real-world experiences designing cloud data platforms for dozens of organizations, cloud data experts Danil Zburivsky and Lynda Partner take you through a six-layer approach to creating cloud data platforms that maximizes flexibility and manageability and reduces costs. Starting with foundational principles, you''ll learn how to get data into your platform from different databases, files, and APIs, the essential practices for organizing and processing that raw data, and how to best take advantage of the services offered by major cloud vendors. As you progress past the basics you''ll take a deep dive into advanced topics to get the most out of your data platform, including real-time data management, machine learning analytics, schema management, and more. what''s inside The tools of different public cloud for implementing data platforms Best practices for managing structured and unstructured data sets Machine learning tools that can be used on top of the cloud Cost optimization techniques about the reader For data professionals familiar with the basics of cloud computing and distributed data processing systems like Hadoop and Spark. about the authors Danil Zburivsky has over 10 years experience designing and supporting large-scale data infrastructure for enterprises across the globe. Lynda Partner is the VP of Analytics-as-a-Service at Pythian, and has been on the business side of data for over 20 years. |
| bigquery to salesforce marketing cloud: Salesforce For Dummies Liz Kao, Jon Paz, 2019-12-12 Get up to lightning speed with this fully updated, bestselling guide to using Salesforce.com! Salesforce.com For Dummies, 7th Edition gives you an edge in building relationships and managing your company's sales, marketing, customer service, and support operations. You’ll learn how to maximize the new user interface to organize contacts, schedule business appointments, use forecasting tools to predict upcoming sales, make accurate projects based on past performance, and more. Written by Salesforce.com insiders with years of expertise in CRM services, this new edition covers the latest enhancements to Salesforce.com, the world's most popular customer relationship management software. You’ll find out how to determine the right configuration to suit your business needs, and how to use apps, widgets, and tools to personalize your system. Then, you’ll explore prospecting leads, managing accounts and partners, developing contacts, tracking products, calculating forecasts, and utilizing service and support. Customize the new user interface with apps, widgets, and tools Prospect leads, drive sales, and provide outstanding customer service Manage contacts, identify opportunities, and analyze your results Collaborate with colleagues using Chatter More than 150,000 companies worldwide use Salesforce.com as their CRM solution—if you’re a new or existing user looking to maximize the potential of the new UI, this book has everything you need. |
| bigquery to salesforce marketing cloud: Building Machine Learning and Deep Learning Models on Google Cloud Platform Ekaba Bisong, 2019-09-27 Take a systematic approach to understanding the fundamentals of machine learning and deep learning from the ground up and how they are applied in practice. You will use this comprehensive guide for building and deploying learning models to address complex use cases while leveraging the computational resources of Google Cloud Platform. Author Ekaba Bisong shows you how machine learning tools and techniques are used to predict or classify events based on a set of interactions between variables known as features or attributes in a particular dataset. He teaches you how deep learning extends the machine learning algorithm of neural networks to learn complex tasks that are difficult for computers to perform, such as recognizing faces and understanding languages. And you will know how to leverage cloud computing to accelerate data science and machine learning deployments. Building Machine Learning and Deep Learning Models on Google Cloud Platform is divided into eight parts that cover the fundamentals of machine learning and deep learning, the concept of data science and cloud services, programming for data science using the Python stack, Google Cloud Platform (GCP) infrastructure and products, advanced analytics on GCP, and deploying end-to-end machine learning solution pipelines on GCP. What You’ll Learn Understand the principles and fundamentals of machine learning and deep learning, the algorithms, how to use them, when to use them, and how to interpret your resultsKnow the programming concepts relevant to machine and deep learning design and development using the Python stack Build and interpret machine and deep learning models Use Google Cloud Platform tools and services to develop and deploy large-scale machine learning and deep learning products Be aware of the different facets and design choices to consider when modeling a learning problem Productionalize machine learning models into software products Who This Book Is For Beginners to the practice of data science and applied machine learning, data scientists at all levels, machine learning engineers, Google Cloud Platform data engineers/architects, and software developers |
| bigquery to salesforce marketing cloud: Data Lake for Enterprises Tomcy John, Pankaj Misra, 2017-05-31 A practical guide to implementing your enterprise data lake using Lambda Architecture as the base About This Book Build a full-fledged data lake for your organization with popular big data technologies using the Lambda architecture as the base Delve into the big data technologies required to meet modern day business strategies A highly practical guide to implementing enterprise data lakes with lots of examples and real-world use-cases Who This Book Is For Java developers and architects who would like to implement a data lake for their enterprise will find this book useful. If you want to get hands-on experience with the Lambda Architecture and big data technologies by implementing a practical solution using these technologies, this book will also help you. What You Will Learn Build an enterprise-level data lake using the relevant big data technologies Understand the core of the Lambda architecture and how to apply it in an enterprise Learn the technical details around Sqoop and its functionalities Integrate Kafka with Hadoop components to acquire enterprise data Use flume with streaming technologies for stream-based processing Understand stream- based processing with reference to Apache Spark Streaming Incorporate Hadoop components and know the advantages they provide for enterprise data lakes Build fast, streaming, and high-performance applications using ElasticSearch Make your data ingestion process consistent across various data formats with configurability Process your data to derive intelligence using machine learning algorithms In Detail The term Data Lake has recently emerged as a prominent term in the big data industry. Data scientists can make use of it in deriving meaningful insights that can be used by businesses to redefine or transform the way they operate. Lambda architecture is also emerging as one of the very eminent patterns in the big data landscape, as it not only helps to derive useful information from historical data but also correlates real-time data to enable business to take critical decisions. This book tries to bring these two important aspects — data lake and lambda architecture—together. This book is divided into three main sections. The first introduces you to the concept of data lakes, the importance of data lakes in enterprises, and getting you up-to-speed with the Lambda architecture. The second section delves into the principal components of building a data lake using the Lambda architecture. It introduces you to popular big data technologies such as Apache Hadoop, Spark, Sqoop, Flume, and ElasticSearch. The third section is a highly practical demonstration of putting it all together, and shows you how an enterprise data lake can be implemented, along with several real-world use-cases. It also shows you how other peripheral components can be added to the lake to make it more efficient. By the end of this book, you will be able to choose the right big data technologies using the lambda architectural patterns to build your enterprise data lake. Style and approach The book takes a pragmatic approach, showing ways to leverage big data technologies and lambda architecture to build an enterprise-level data lake. |
| bigquery to salesforce marketing cloud: Storage Systems Alexander Thomasian, 2021-10-13 Storage Systems: Organization, Performance, Coding, Reliability and Their Data Processing was motivated by the 1988 Redundant Array of Inexpensive/Independent Disks proposal to replace large form factor mainframe disks with an array of commodity disks. Disk loads are balanced by striping data into strips—with one strip per disk— and storage reliability is enhanced via replication or erasure coding, which at best dedicates k strips per stripe to tolerate k disk failures. Flash memories have resulted in a paradigm shift with Solid State Drives (SSDs) replacing Hard Disk Drives (HDDs) for high performance applications. RAID and Flash have resulted in the emergence of new storage companies, namely EMC, NetApp, SanDisk, and Purestorage, and a multibillion-dollar storage market. Key new conferences and publications are reviewed in this book.The goal of the book is to expose students, researchers, and IT professionals to the more important developments in storage systems, while covering the evolution of storage technologies, traditional and novel databases, and novel sources of data. We describe several prototypes: FAWN at CMU, RAMCloud at Stanford, and Lightstore at MIT; Oracle's Exadata, AWS' Aurora, Alibaba's PolarDB, Fungible Data Center; and author's paper designs for cloud storage, namely heterogeneous disk arrays and hierarchical RAID. - Surveys storage technologies and lists sources of data: measurements, text, audio, images, and video - Familiarizes with paradigms to improve performance: caching, prefetching, log-structured file systems, and merge-trees (LSMs) - Describes RAID organizations and analyzes their performance and reliability - Conserves storage via data compression, deduplication, compaction, and secures data via encryption - Specifies implications of storage technologies on performance and power consumption - Exemplifies database parallelism for big data, analytics, deep learning via multicore CPUs, GPUs, FPGAs, and ASICs, e.g., Google's Tensor Processing Units |
| bigquery to salesforce marketing cloud: Mastering Microsoft Power BI Brett Powell, 2018-03-29 Design, create and manage robust Power BI solutions to gain meaningful business insights Key Features Master all the dashboarding and reporting features of Microsoft Power BI Combine data from multiple sources, create stunning visualizations and publish your reports across multiple platforms A comprehensive guide with real-world use cases and examples demonstrating how you can get the best out of Microsoft Power BI Book DescriptionThis book is intended for business intelligence professionals responsible for the design and development of Power BI content as well as managers, architects and administrators who oversee Power BI projects and deployments. The chapters flow from the planning of a Power BI project through the development and distribution of content to the administration of Power BI for an organization. BI developers will learn how to create sustainable and impactful Power BI datasets, reports, and dashboards. This includes connecting to data sources, shaping and enhancing source data, and developing an analytical data model. Additionally, top report and dashboard design practices are described using features such as Bookmarks and the Power KPI visual. BI managers will learn how Power BI’s tools work together such as with the On-premises data gateway and how content can be staged and securely distributed via Apps. Additionally, both the Power BI Report Server and Power BI Premium are reviewed. By the end of this book, you will be confident in creating effective charts, tables, reports or dashboards for any kind of data using the tools and techniques in Microsoft Power BI.What you will learn Build efficient data retrieval and transformation processes with the Power Query M Language Design scalable, user-friendly DirectQuery and Import Data Models Develop visually rich, immersive, and interactive reports and dashboards Maintain version control and stage deployments across development, test, and production environments Manage and monitor the Power BI Service and the On-premises data gateway Develop a fully on-premise solution with the Power BI Report Server Scale up a Power BI solution via Power BI Premium capacity and migration to Azure Analysis Services or SQL Server Analysis Services Who this book is for Business Intelligence professionals and existing Power BI users looking to master Power BI for all their data visualization and dashboarding needs will find this book to be useful. While understanding of the basic BI concepts is required, some exposure to Microsoft Power BI will be helpful. |
| bigquery to salesforce marketing cloud: Tableau Your Data! Daniel G. Murray, 2016-01-29 Transform your organization's data into actionable insights with Tableau Tableau is designed specifically to provide fast and easy visual analytics. The intuitive drag-and-drop interface helps you create interactive reports, dashboards, and visualizations, all without any special or advanced training. This all new edition of Tableau Your Data! is your Tableau companion, helping you get the most out of this invaluable business toolset. Tableau Your Data! shows you how to build dynamic, best of breed visualizations using the Tableau Software toolset. This comprehensive guide covers the core feature set for data analytics, and provides clear step-by-step guidance toward best practices and advanced techniques that go way beyond the user manual. You'll learn how Tableau is different from traditional business information analysis tools, and how to navigate your way around the Tableau 9.0 desktop before delving into functions and calculations, as well as sharing with the Tableau Server. Analyze data more effectively with Tableau Desktop Customize Tableau's settings for your organization's needs with detailed real-world examples on data security, scaling, syntax, and more Deploy visualizations to consumers throughout the enterprise - from sales to marketing, operations to finance, and beyond Understand Tableau functions and calculations and leverage Tableau across every link in the value chain Learn from actual working models of the book's visualizations and other web-based resources via a companion website Tableau helps you unlock the stories within the numbers, and Tableau Your Data! puts the software's full functionality right at your fingertips. |
| bigquery to salesforce marketing cloud: Cloud Computing Dan C. Marinescu, 2013-05-30 Cloud Computing: Theory and Practice provides students and IT professionals with an in-depth analysis of the cloud from the ground up. Beginning with a discussion of parallel computing and architectures and distributed systems, the book turns to contemporary cloud infrastructures, how they are being deployed at leading companies such as Amazon, Google and Apple, and how they can be applied in fields such as healthcare, banking and science. The volume also examines how to successfully deploy a cloud application across the enterprise using virtualization, resource management and the right amount of networking support, including content delivery networks and storage area networks. Developers will find a complete introduction to application development provided on a variety of platforms. - Learn about recent trends in cloud computing in critical areas such as: resource management, security, energy consumption, ethics, and complex systems - Get a detailed hands-on set of practical recipes that help simplify the deployment of a cloud based system for practical use of computing clouds along with an in-depth discussion of several projects - Understand the evolution of cloud computing and why the cloud computing paradigm has a better chance to succeed than previous efforts in large-scale distributed computing |
| bigquery to salesforce marketing cloud: Journey Builder Developer's Guide Eliot Harper, 2015-04-17 A guide for developers and integrators working with Salesforce Marketing Cloud. This book describes the core concepts, components, API methods and procedural steps required to build integrated customer journeys using Journey Builder. |
| bigquery to salesforce marketing cloud: Ecosystem-Led Growth Bob Moore, 2024-03-04 A blueprint to new levels of company growth leveraging your firm’s Partner Ecosystem In Ecosystem-Led Growth: A Blueprint For Sales and Marketing Success Using the Power of Partnerships, veteran entrepreneur and tech leader Bob Moore delivers an intuitive and insightful guide to using your company’s Partner Ecosystem to unlock countless leads, break sales records, scale your organization, and build a once-in-a-generation business. In the book, you’ll discover why partnerships are no longer the domain of “partner people” schmoozing at conferences. Instead, they can be used to unlock vast amounts of data, new relationships, and scalable growth plays. You’ll learn about: Transformational technologies that bring partner data to your fingertips Savvy companies and executives who convert that data into untapped growth opportunities Real-world examples of go-to-market leaders at dozens of leading tech companies implementing a powerful new perspective on growth An indispensable roadmap to an exciting new strategy for scaling your firm, Ecosystem-Led Growth will earn a place on the bookshelves of managers, executives, founders, entrepreneurs, salespeople, marketers, and anyone else interested in taking their company to new heights. |
| bigquery to salesforce marketing cloud: The Internet of Things and Big Data Analytics Pethuru Raj, T Poongodi, Balamurugan Balusamy, Manju Khari, 2020-06-07 This book comprehensively conveys the theoretical and practical aspects of IoT and big data analytics with the solid contributions from practitioners as well as academicians. This book examines and expounds the unique capabilities of the big data analytics platforms in capturing, cleansing and crunching IoT device/sensor data in order to extricate actionable insights. A number of experimental case studies and real-world scenarios are incorporated in this book in order to instigate our book readers. This book Analyzes current research and development in the domains of IoT and big data analytics Gives an overview of latest trends and transitions happening in the IoT data analytics space Illustrates the various platforms, processes, patterns, and practices for simplifying and streamlining IoT data analytics The Internet of Things and Big Data Analytics: Integrated Platforms and Industry Use Cases examines and accentuates how the multiple challenges at the cusp of IoT and big data can be fully met. The device ecosystem is growing steadily. It is forecast that there will be billions of connected devices in the years to come. When these IoT devices, resource-constrained as well as resource-intensive, interact with one another locally and remotely, the amount of multi-structured data generated, collected, and stored is bound to grow exponentially. Another prominent trend is the integration of IoT devices with cloud-based applications, services, infrastructures, middleware solutions, and databases. This book examines the pioneering technologies and tools emerging and evolving in order to collect, pre-process, store, process and analyze data heaps in order to disentangle actionable insights. |
| bigquery to salesforce marketing cloud: INTELIGENCIA ARTIFICIAL PARA EL MARKETING Eduardo Liberos Hoppe, Silvia Ahumada Luyando, Miranda Sánchez Ahumada, 2024-01-15 El libro Inteligencia artificial para el marketing está dirigido a directivos de marketing, grandes corporaciones y gerentes de pymes y universitarios de los últimos años en las carreras de Administración y Dirección de Empresas, Marketing y Gestión Comercial. ¿Cómo aplicar IA en marketing? El lector aprenderá cómo se crea una IA, qué técnicas podemos utilizar en marketing y las herramientas y plataformas que mejor funcionan en marketing. Los autores han trabajado con 476 plataformas de IA, y en el libro se explican los mejores usos para las disciplinas del marketing: segmentación, investigación de mercados, posicionamiento, marketing de producto, política de precios, distribución, marketing de guerrillas, marketing digital, comercio electrónico, entre otras. El libro se divide en 7 capítulos, donde se tratan de una manera profunda todas las herramientas y técnicas que un directivo puede utilizar para poner en marcha un programa de IA en el área de marketing. También se enseña el funcionamiento de las nuevas plataformas y soluciones de IA en marketing, Los autores son profesionales de reconocido prestigio que han desarrollado sus carreras profesionales en grandes corporaciones españolas y americanas. Han sido galardonados con algunos de los premios más prestigiosos en el mundo de la comunicación y son profesores invitados de algunas de las mejores escuelas de negocios y universidades de España y Latinoamérica como ESIC, IE, IEDGE, IEB, EADA, INESDI, CESMA o la Universidad Panamericana. También son speakers habituales en congresos especializados del sector de la publicidad y universidades como la Universidad Complutense, Universidad Iberoamericana, ITESO o TEC-Monterrey. Índice Prólogos.- Introducción a la inteligencia artificial aplicada al marketing.- Análisis de datos.- Machine learning.- Usos de la inteligencia artificial en marketing.- Técnicas de inteligencia artificial para el marketing.- Prompts para chatbots.- Plataformas de la IA en marketing. Bibliografía. |
| bigquery to salesforce marketing cloud: Essentials of Business Analytics Bhimasankaram Pochiraju, Sridhar Seshadri, 2019-07-10 This comprehensive edited volume is the first of its kind, designed to serve as a textbook for long-duration business analytics programs. It can also be used as a guide to the field by practitioners. The book has contributions from experts in top universities and industry. The editors have taken extreme care to ensure continuity across the chapters. The material is organized into three parts: A) Tools, B) Models and C) Applications. In Part A, the tools used by business analysts are described in detail. In Part B, these tools are applied to construct models used to solve business problems. Part C contains detailed applications in various functional areas of business and several case studies. Supporting material can be found in the appendices that develop the pre-requisites for the main text. Every chapter has a business orientation. Typically, each chapter begins with the description of business problems that are transformed into data questions; and methodology is developed to solve these questions. Data analysis is conducted using widely used software, the output and results are clearly explained at each stage of development. These are finally transformed into a business solution. The companion website provides examples, data sets and sample code for each chapter. |
| bigquery to salesforce marketing cloud: Jumpstart Snowflake Dmitry Anoshin, Dmitry Shirokov, Donna Strok, 2019-12-20 Explore the modern market of data analytics platforms and the benefits of using Snowflake computing, the data warehouse built for the cloud. With the rise of cloud technologies, organizations prefer to deploy their analytics using cloud providers such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform. Cloud vendors are offering modern data platforms for building cloud analytics solutions to collect data and consolidate into single storage solutions that provide insights for business users. The core of any analytics framework is the data warehouse, and previously customers did not have many choices of platform to use. Snowflake was built specifically for the cloud and it is a true game changer for the analytics market. This book will help onboard you to Snowflake, present best practices to deploy, and use the Snowflake data warehouse. In addition, it covers modern analytics architecture and use cases. It provides use cases of integration with leading analytics software such as Matillion ETL, Tableau, and Databricks. Finally, it covers migration scenarios for on-premise legacy data warehouses. What You Will Learn Know the key functionalities of Snowflake Set up security and access with cluster Bulk load data into Snowflake using the COPY command Migrate from a legacy data warehouse to Snowflake integrate the Snowflake data platform with modern business intelligence (BI) and data integration tools Who This Book Is For Those working with data warehouse and business intelligence (BI) technologies, and existing and potential Snowflake users |
| bigquery to salesforce marketing cloud: The Forecaster Method John Lincoln, 2019-07-19 Never Waste Another Digital Marketing Dollar Again (While Growing Your Business Faster Than Ever)! The Forecaster Method is the proven system to accurately evaluate, forecast, and scale your digital marketing. What You Will Learn: - Bring dollars online from traditional media with confidence!- Accurately forecast and scale your digital marketing- Establish goals and hit them while reducing costs- Establish executive-level reporting and Key Performance Indicators (KPIs)- Set the right overall marketing budget based on a real model- Find new opportunities and phase out poor performers- Create a diversified portfolio of traffic - Set business revenue targets and hit them - Learn how to convert your traffic for less- Learn how to build audiences and market to them over time- Learn how much you should be spending on marketing- Get access to real industry studies that show benchmark data- And more!With hundreds of ways to spend your money in digital today, now is the most important time for this system to be released. Welcome to the Forecaster Method, your guide to transitioning more marketing dollars online from offline, structuring your approach, properly using a performance-based model, and using clear data to scale results. If you are a CMO, business owner, or digital marketer (or perhaps aspire to be in positions such as these) of a multi-million or even multi-billion-dollar company, consider this book your new best friend. As a large company you are competing with the smartest minds in the business, many of which are nimbler in performance-based marketing. It is critical you understand how to test, measure, and prove results as well as scale your online marketing. It is no longer the same marketing mix as it was a few years ago. Digital marketing has exploded and there are so many new ways to advertise it is almost impossible to keep up with. The key to success is following a methodical digital marketing process. About The AuthorJohn Lincoln (MBA) is CEO of Ignite Visibility (a 2017, 2018 and 2019 Inc. 5000 company) a highly sought-after digital marketing strategist, frequent industry speaker, and winner of the coveted Search Engine Land Search Marketer of the Year award.With 16+ years of demanding experience, Lincoln has worked with over 1,000 online businesses including amazing clients such as Office Depot, Tony Robbins, Morgan Stanley, Fox, USA Today, Sharp Healthcare, 5 Hour Energy, Cox Communications, and more. |
| bigquery to salesforce marketing cloud: Machine Learning with BigQuery ML Alessandro Marrandino, 2021-06-11 Manage different business scenarios with the right machine learning technique using Google's highly scalable BigQuery ML Key FeaturesGain a clear understanding of AI and machine learning services on GCP, learn when to use these, and find out how to integrate them with BigQuery MLLeverage SQL syntax to train, evaluate, test, and use ML modelsDiscover how BigQuery works and understand the capabilities of BigQuery ML using examplesBook Description BigQuery ML enables you to easily build machine learning (ML) models with SQL without much coding. This book will help you to accelerate the development and deployment of ML models with BigQuery ML. The book starts with a quick overview of Google Cloud and BigQuery architecture. You'll then learn how to configure a Google Cloud project, understand the architectural components and capabilities of BigQuery, and find out how to build ML models with BigQuery ML. The book teaches you how to use ML using SQL on BigQuery. You'll analyze the key phases of a ML model's lifecycle and get to grips with the SQL statements used to train, evaluate, test, and use a model. As you advance, you'll build a series of use cases by applying different ML techniques such as linear regression, binary and multiclass logistic regression, k-means, ARIMA time series, deep neural networks, and XGBoost using practical use cases. Moving on, you'll cover matrix factorization and deep neural networks using BigQuery ML's capabilities. Finally, you'll explore the integration of BigQuery ML with other Google Cloud Platform components such as AI Platform Notebooks and TensorFlow along with discovering best practices and tips and tricks for hyperparameter tuning and performance enhancement. By the end of this BigQuery book, you'll be able to build and evaluate your own ML models with BigQuery ML. What you will learnDiscover how to prepare datasets to build an effective ML modelForecast business KPIs by leveraging various ML models and BigQuery MLBuild and train a recommendation engine to suggest the best products for your customers using BigQuery MLDevelop, train, and share a BigQuery ML model from previous parts with AI Platform NotebooksFind out how to invoke a trained TensorFlow model directly from BigQueryGet to grips with BigQuery ML best practices to maximize your ML performanceWho this book is for This book is for data scientists, data analysts, data engineers, and anyone looking to get started with Google's BigQuery ML. You'll also find this book useful if you want to accelerate the development of ML models or if you are a business user who wants to apply ML in an easy way using SQL. Basic knowledge of BigQuery and SQL is required. |
| bigquery to salesforce marketing cloud: Between Empowerment and Manipulation Marijn Sax, 2021-09-28 Popular health apps are commercial services. Despite the promise of empowerment they offer, the tensions introduced by their data-driven, dynamically adjustable digital environments engender a potential for manipulation to which their designers and operators can easily succumb. In this important book, the author develops an ethical framework to evaluate the commercial practices of for-profit health apps, proceeding to a detailed proposal of how to legally address the exploitation, for financial gain, of users’ need for health. Focusing on the intricate tracking of users over time, coupled with the possibility to personalize the environment based on knowledge gained from tracking, the book’s in-depth analysis of popular for-profit health apps engages with such particulars as the following: the strategic framing of health in health apps; the cultural tendency to presume we are unhealthy until we have proven we are healthy; the key concepts of autonomy, vulnerability, trust, and manipulation; how health apps develop ongoing profitable relationships with users; and use of misleading and aggressive commercial practices. The author argues that the European Union’s Unfair Commercial Practices Directive, when informed by ethical considerations, offers promising legal solutions to the manipulation concerns raised by popular for-profit health apps. The book will be welcomed not only for its incisive scrutiny of the health app phenomenon but also for the light it sheds on the wider problems inherent in the digital society—what digital environments know about their users, how they use that knowledge, and for which purpose. Its progress from an ethical approach to legal solutions will recommend the book to lawyers concerned with business practices, human resources professionals, policymakers, and academics interested in the intersection of ethics and law. |
| bigquery to salesforce marketing cloud: The Unified Star Schema Bill Inmon, Francesco Puppini, 2020-10 Master the most agile and resilient design for building analytics applications: the Unified Star Schema (USS) approach. The USS has many benefits over traditional dimensional modeling. Witness the power of the USS as a single star schema that serves as a foundation for all present and future business requirements of your organization. |
BigQuery overview | Google Cloud
5 days ago · BigQuery's serverless architecture lets you use languages like SQL and Python to answer your organization's biggest questions with zero infrastructure management. BigQuery …
BigQuery documentation - Google Cloud
Jun 5, 2025 · BigQuery is Google Cloud's fully managed, petabyte-scale, and cost-effective analytics data warehouse that lets you run analytics over vast amounts of data in near real …
Enable the BigQuery sandbox - Google Cloud
5 days ago · The BigQuery sandbox lets you experience BigQuery without providing a credit card or creating a billing account for your project. If you already created a billing account, you can …
Explore the Google Cloud console | BigQuery
4 days ago · Shows how to use the Google Cloud console to work with BigQuery projects, display resources (such as datasets and tables), compose and run SQL queries, and view query and …
Pricing | BigQuery: Cloud Data Warehouse - Google Cloud
BigQuery Omni offers the following pricing models depending on your workloads and needs. On-Demand compute pricing. Similar to BigQuery on-demand analysis model, BigQuery Omni …
Overview of BigQuery analytics - Google Cloud
Jun 5, 2025 · This document describes how BigQuery processes queries, and it provides an overview of several features that are useful for understanding and analyzing your data. …
Introduction to SQL in BigQuery - Google Cloud
4 days ago · Introduction to SQL in BigQuery. This document provides an overview of supported statements and SQL dialects in BigQuery. GoogleSQL is an ANSI-compliant Structured Query …
De un almacén de datos a una plataforma autónoma de datos e IA
BigQuery es un almacén de datos empresarial totalmente administrado que permite realizar análisis de grandes volúmenes de datos.
BigQuery explained: An overview of BigQuery's architecture
Sep 2, 2020 · In this first post, we will look at how data warehouses change business decision making, how BigQuery solves problems with traditional data warehouses, and dive into a high …
BigQuery | Plate-forme de données d'IA | Lakehouse | EDW
BigQuery est un entrepôt de données d'entreprise qui permet de traiter plusieurs pétaoctets de données avec le langage SQL et des fonctionnalités de machine learning.
BigQuery overview | Google Cloud
5 days ago · BigQuery's serverless architecture lets you use languages like SQL and Python to answer your organization's biggest questions with zero infrastructure management. BigQuery …
BigQuery documentation - Google Cloud
Jun 5, 2025 · BigQuery is Google Cloud's fully managed, petabyte-scale, and cost-effective analytics data warehouse that lets you run analytics over vast amounts of data in near real …
Enable the BigQuery sandbox - Google Cloud
5 days ago · The BigQuery sandbox lets you experience BigQuery without providing a credit card or creating a billing account for your project. If you already created a billing account, you can …
Explore the Google Cloud console | BigQuery
4 days ago · Shows how to use the Google Cloud console to work with BigQuery projects, display resources (such as datasets and tables), compose and run SQL queries, and view query and …
Pricing | BigQuery: Cloud Data Warehouse - Google Cloud
BigQuery Omni offers the following pricing models depending on your workloads and needs. On-Demand compute pricing. Similar to BigQuery on-demand analysis model, BigQuery Omni …
Overview of BigQuery analytics - Google Cloud
Jun 5, 2025 · This document describes how BigQuery processes queries, and it provides an overview of several features that are useful for understanding and analyzing your data. …
Introduction to SQL in BigQuery - Google Cloud
4 days ago · Introduction to SQL in BigQuery. This document provides an overview of supported statements and SQL dialects in BigQuery. GoogleSQL is an ANSI-compliant Structured Query …
De un almacén de datos a una plataforma autónoma de datos e IA
BigQuery es un almacén de datos empresarial totalmente administrado que permite realizar análisis de grandes volúmenes de datos.
BigQuery explained: An overview of BigQuery's architecture
Sep 2, 2020 · In this first post, we will look at how data warehouses change business decision making, how BigQuery solves problems with traditional data warehouses, and dive into a high …
BigQuery | Plate-forme de données d'IA | Lakehouse | EDW
BigQuery est un entrepôt de données d'entreprise qui permet de traiter plusieurs pétaoctets de données avec le langage SQL et des fonctionnalités de machine learning.
