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Podcasts
Salesforce Process Builder Quick Start Guide. Build complex workflows by clicking, not coding
Salesforce Management System is an information system used in CRM to automate business processes, such as sales and marketing. Process Builder is a visual tool created to automate business processes in Salesforce. It enables users with no coding expertise to build complex Salesforce workflows.The book starts with an introduction to Process Builder, focussing on the building blocks of creating Processes. Then you will learn about different applications of Process Builder for developing streamlined solutions. You will learn how to easily automate business processes and tackle complex business scenarios using Processes. The book explains the workings of the Process Builder so that you can create reusable processes. It also explains how you can migrate existing Workflow Rules to Process Builder.By the end of the book, you will have a clear understanding of how to use Flows and Process Builder to optimize code usage.
Adrian Ward, Christian Screen, Haroun Khan
Oracle Business Intelligence Enterprise Edition (OBIEE) 12c is packed full of features and has a fresh approach to information presentation, system management, and security. OBIEE can help any organization to understand its data, to make useful information from data, and to ensure decision-making is supported by facts. OBIEE can focus on information that needs action, alerting users when conditions are met. OBIEE can be used for data analysis, form production, dashoarding, and workflow processes.We will introduce you to OBIEE features and provide a step-by-step guide to build a complete system from scratch. With this guide, you will be equipped with a good basic understanding of what the product contains, how to install and configure it, and how to create effective Business Intelligence. This book contains the necessary information for a beginner to create a high-performance OBIEE 12c system.This book is also a guide that explains how to use an existing OBIEE 12c system, and shows end users how to create.
DevOps is a practical field that focuses on delivering business value as efficiently as possible. DevOps encompasses all code workflows from testing environments to production environments. It stresses cooperation between different roles, and how they can work together more closely, as the roots of the word imply—Development and Operations.Practical DevOps begins with a quick refresher on DevOps and continuous delivery and quickly moves on to show you how DevOps affects software architectures. You'll create a sample enterprise Java application that you’'ll continue to work with through the remaining chapters. Following this, you will explore various code storage and build server options. You will then learn how to test your code with a few tools and deploy your test successfully. In addition to this, you will also see how to monitor code for any anomalies and make sure that it runs as expected. Finally, you will discover how to handle logs and keep track of the issues that affect different processes.By the end of the book, you will be familiar with all the tools needed to deploy, integrate, and deliver efficiently with DevOps.
Making sure that your application runs across different systems as intended is quickly becoming a standard development requirement. With Docker, you can ensure that what you build will behave the way you expect it to, regardless of where it's deployed. By guiding you through Docker from start to finish (from installation, to the Docker Registry, all the way through to working with Docker Swarms), we’ll equip you with the skills you need to migrate your workflow to Docker with complete confidence.
Tableau 2019.x Cookbook. Over 115 recipes to build end-to-end analytical solutions using Tableau
Dmitry Anoshin, Teodora Matic, Slaven Bogdanovic, Tania Lincoln, ...
Tableau has been one of the most popular business intelligence solutions in recent times, thanks to its powerful and interactive data visualization capabilities. Tableau 2019.x Cookbook is full of useful recipes from industry experts, who will help you master Tableau skills and learn each aspect of Tableau's ecosystem.This book is enriched with features such as Tableau extracts, Tableau advanced calculations, geospatial analysis, and building dashboards. It will guide you with exciting data manipulation, storytelling, advanced filtering, expert visualization, and forecasting techniques using real-world examples. From basic functionalities of Tableau to complex deployment on Linux, you will cover it all. Moreover, you will learn advanced features of Tableau using R, Python, and various APIs. You will learn how to prepare data for analysis using the latest Tableau Prep. In the concluding chapters, you will learn how Tableau fits the modern world of analytics and works with modern data platforms such as Snowflake and Redshift. In addition, you will learn about the best practices of integrating Tableau with ETL using Matillion ETL.By the end of the book, you will be ready to tackle business intelligence challenges using Tableau's features.
Silas Toms, Paul Crickard, Eric van Rees
Python comes with a host of open source libraries and tools that help you work on professional geoprocessing tasks without investing in expensive tools. This book will introduce Python developers, both new and experienced, to a variety of new code libraries that have been developed to perform geospatial analysis, statistical analysis, and data management. This book will use examples and code snippets that will help explain how Python 3 differs from Python 2, and how these new code libraries can be used to solve age-old problems in geospatial analysis.You will begin by understanding what geoprocessing is and explore the tools and libraries that Python 3 offers. You will then learn to use Python code libraries to read and write geospatial data. You will then learn to perform geospatial queries within databases and learn PyQGIS to automate analysis within the QGIS mapping suite. Moving forward, you will explore the newly released ArcGIS API for Python and ArcGIS Online to perform geospatial analysis and create ArcGIS Online web maps. Further, you will deep dive into Python Geospatial web frameworks and learn to create a geospatial REST API.
Managing physical servers will be a thing of the past once you’re able to harness the power of serverless computing. If you’re already prepped with the basics of serverless computing, Serverless Programming Cookbook will help you take the next step ahead. This recipe-based guide provides solutions to problems you might face while building serverless applications. You'll begin by setting up Amazon Web Services (AWS), the primary cloud provider used for most recipes. The next set of recipes will cover various components to build a Serverless application including REST APIs, database, user management, authentication, web hosting, domain registration, DNS management, CDN, messaging, notifications and monitoring. The book also introduces you to the latest technology trends such as Data Streams, Machine Learning and NLP. You will also see patterns and practices for using various services in a real world application. Finally, to broaden your understanding of Serverless computing, you'll also cover getting started guides for other cloud providers such as Azure, Google Cloud Platform and IBM cloud. By the end of this book, you’ll have acquired the skills you need to build serverless applications efficiently using various cloud offerings.
R Data Analysis Projects. Build end to end analytics systems to get deeper insights from your data
R offers a large variety of packages and libraries for fast and accurate data analysis and visualization. As a result, it’s one of the most popularly used languages by data scientists and analysts, or anyone who wants to perform data analysis. This book will demonstrate how you can put to use your existing knowledge of data analysis in R to build highly efficient, end-to-end data analysis pipelines without any hassle.You’ll start by building a content-based recommendation system, followed by building a project on sentiment analysis with tweets. You’ll implement time-series modeling for anomaly detection, and understand cluster analysis of streaming data. You’ll work through projects on performing efficient market data research, building recommendation systems, and analyzing networks accurately, all provided with easy to follow codes. With the help of these real-world projects, you’ll get a better understanding of the challenges faced when building data analysis pipelines, and see how you can overcome them without compromising on the efficiency or accuracy of your systems. The book covers some popularly used R packages such as dplyr, ggplot2, RShiny, and others, and includes tips on using them effectively.By the end of this book, you’ll have a better understanding of data analysis with R, and be able to put your knowledge to practical use without any hassle.