Explore common and not-so-common data transformation scenarios and solutions to become well-versed with Tableau Prep and create efficient and powerful data pipelines Key FeaturesCombine, clean, and shape data for analysis using self-service data preparation techniquesBecome proficient with Tableau Prep for building and managing data flows across your organizationLearn how to combine multiple data transformations in order to build a robust datasetBook Description Tableau Prep is a tool in the Tableau software suite, created specifically to develop data pipelines. This book will describe, in detail, a variety of scenarios that you can apply in your environment for developing, publishing, and maintaining complex Extract, Transform and Load (ETL) data pipelines. The book starts by showing you how to set up Tableau Prep Builder. You'll learn how to obtain data from various data sources, including files, databases, and Tableau Extracts. Next, the book demonstrates how to perform data cleaning and data aggregation in Tableau Prep Builder. You'll also gain an understanding of Tableau Prep Builder and how you can leverage it to create data pipelines that prepare your data for downstream analytics processes, including reporting and dashboard creation in Tableau. As part of a Tableau Prep flow, you'll also explore how to use R and Python to implement data science components inside a data pipeline. In the final chapter, you'll apply the knowledge you've gained to build two use cases from scratch, including a data flow for a retail store to prepare a robust dataset using multiple disparate sources and a data flow for a call center to perform ad hoc data analysis. By the end of this book, you'll be able to create, run, and publish Tableau Prep flows and implement solutions to common problems in data pipelines. What you will learnPerform data cleaning and preparation techniques for advanced data analysisUnderstand how to combine multiple disparate datasetsPrepare data for different Business Intelligence (BI) toolsApply Tableau Prep's calculation language to create powerful calculationsUse Tableau Prep for ad hoc data analysis and data science flowsDeploy Tableau Prep flows to Tableau Server and Tableau OnlineWho this book is for This book is for business intelligence professionals, data analysts, and Tableau users looking to learn Tableau Prep essentials and create data pipelines or ETL processes using it. Beginner-level knowledge of data management will be beneficial to understand the concepts covered in this Tableau cookbook more effectively.

Explore common and not-so-common data transformation scenarios and solutions to become well-versed with Tableau Prep and create efficient and powerful data pipelines Key FeaturesCombine, clean, and shape data for analysis using self-service data preparation techniquesBecome proficient with Tableau Prep for building and managing data flows across your organizationLearn how to combine multiple data transformations in order to build a robust datasetBook Description Tableau Prep is a tool in the Tableau software suite, created specifically to develop data pipelines. This book will describe, in detail, a variety of scenarios that you can apply in your environment for developing, publishing, and maintaining complex Extract, Transform and Load (ETL) data pipelines. The book starts by showing you how to set up Tableau Prep Builder. You'll learn how to obtain data from various data sources, including files, databases, and Tableau Extracts. Next, the book demonstrates how to perform data cleaning and data aggregation in Tableau Prep Builder. You'll also gain an understanding of Tableau Prep Builder and how you can leverage it to create data pipelines that prepare your data for downstream analytics processes, including reporting and dashboard creation in Tableau. As part of a Tableau Prep flow, you'll also explore how to use R and Python to implement data science components inside a data pipeline. In the final chapter, you'll apply the knowledge you've gained to build two use cases from scratch, including a data flow for a retail store to prepare a robust dataset using multiple disparate sources and a data flow for a call center to perform ad hoc data analysis. By the end of this book, you'll be able to create, run, and publish Tableau Prep flows and implement solutions to common problems in data pipelines. What you will learnPerform data cleaning and preparation techniques for advanced data analysisUnderstand how to combine multiple disparate datasetsPrepare data for different Business Intelligence (BI) toolsApply Tableau Prep's calculation language to create powerful calculationsUse Tableau Prep for ad hoc data analysis and data science flowsDeploy Tableau Prep flows to Tableau Server and Tableau OnlineWho this book is for This book is for business intelligence professionals, data analysts, and Tableau users looking to learn Tableau Prep essentials and create data pipelines or ETL processes using it. Beginner-level knowledge of data management will be beneficial to understand the concepts covered in this Tableau cookbook more effectively.

Perform advanced dashboard, visualization, and analytical techniques with Tableau Desktop, Tableau Prep, and Tableau Server Key FeaturesUnique problem-solution approach to aid effective business decision-makingCreate interactive dashboards and implement powerful business intelligence solutionsIncludes best practices on using Tableau with modern cloud analytics servicesBook Description 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. What you will learnUnderstand the basic and advanced skills of Tableau DesktopImplement best practices of visualization, dashboard, and storytellingLearn advanced analytics with the use of build in statisticsDeploy the multi-node server on Linux and WindowsUse Tableau with big data sources such as Hadoop, Athena, and SpectrumCover Tableau built-in functions for forecasting using R packagesCombine, shape, and clean data for analysis using Tableau PrepExtend Tableau’s functionalities with REST API and R/PythonWho this book is for Tableau 2019.x Cookbook is for data analysts, data engineers, BI developers, and users who are looking for quick solutions to common and not-so-common problems faced while using Tableau products. Put each recipe into practice by bringing the latest offerings of Tableau 2019.x to solve real-world analytics and business intelligence challenges. Some understanding of BI concepts and Tableau is required.

Whether you're a beginner just learning how to create data visualizations or a Jedi who's already used Tableau for years, this cookbook has a recipe for everyone. Author Lorna Brown provides more than 100 practical recipes to enhance the way you build Tableau dashboards--and helps you understand your data through the power of Tableau Desktop's interactive datavisualizations. With this cookbook, Tableau beginners will learn hands-on how this unique self-serve tool works, while experienced users will find this book to be an ideal reference guide on how to employ specific techniques. It also links you to online resources and community features, such as Tableau Tip Tuesday and Workout Wednesday. By the time you reach the end, you'll be a competent user of Tableau Desktop. You'll learn how to: Build both basic and complex data visualizations with Tableau Desktop Gain hands-on experience with Tableau's latest features, including set and parameter actions Create interactive dashboards to support business questions Improve your analytical skills to enhance the visualizations you've already created Learn data visualization skills and best practices to help you and your organization

Enhance the way you use Tableau Server's analytical tools by learning how to manage content to drive user engagement Key FeaturesUnderstand how to quickly get connected, start publishing workbooks, and adjust basic settingsNavigate the Tableau Server interface to filter and locate content, customize viewing options, and automate various tasksLearn best practices for improving the efficiency of workbooks and data sourcesBook Description Tableau Server is a business intelligence application that provides a centralized location to store, edit, share, and collaborate on content, such as dashboards and curated data sources. This book gets you up and running with Tableau Server to help you increase end-user engagement for your published work as well as reduce or eliminate redundant tasks. You'll explore Tableau Server's structure and how to get started by connecting, publishing content, and navigating the software interface. Next, you'll learn when and how to update the settings of your content at various levels to best utilize Tableau Server's features. You'll understand how to interact with the Tableau Server interface to locate, sort, filter, manage and customize content. Later, the book shows you how to leverage other valuable features that enable you and your audience to share, download, and interact with content on Tableau Server. As you progress, you'll cover principles to increase the performance of your published content. All along, the book shows you how to navigate, interact with, and use Tableau Server with the help of engaging examples and best practices shared by recognized Tableau professionals. By the end of this Tableau book, you'll have a solid understanding of how to use Tableau Server to manage content, automate tasks, and increase end-user engagement. What you will learnGet well-versed in Tableau Server's interface to quickly and easily access essential contentExplore the different types of content and navigate through the project hierarchy quicklyUnderstand how to connect, publish, manage, and modify content on Tableau ServerDiscover how to share content and collaborate with othersAutomate tedious tasks by creating custom views, alerts, subscriptions, and data refresh schedulesBuild data visualizations using Web EditUnderstand how to monitor disparate metrics on multiple dashboardsWho this book is for This Tableau software book is for BI developers, data analysts, and everyday users who have access to Tableau Server and possess basic web navigation skills. No prior experience with Tableau Server is required.

Now in color, this edition of Learning Tableau will empower you to bring data to life and make better business decisions. Purchase of the print or Kindle book includes a free eBook in PDF format. Key FeaturesLearn the basics of data analysis, from snappy visualizations to comprehensive dashboardsGain meaningful insights with geospatial analysis, scripting extensions, and other advanced methodsExplore the latest Tableau 2022 features, including Einstein Discovery and Explain DataBook Description Learning Tableau 2022 helps you get started with Tableau and data visualization, but it does more than just cover the basic principles. It helps you understand how to analyze and communicate data visually, and articulate data stories using advanced features. This new edition is updated with Tableau's latest features, such as dashboard extensions, Explain Data, and integration with CRM Analytics (Einstein Analytics), which will help you harness the full potential of artificial intelligence (AI) and predictive modeling in Tableau. After an exploration of the core principles, this book will teach you how to use table and level of detail calculations to extend and alter default visualizations, build interactive dashboards, and master the art of telling stories with data. You'll learn about visual statistical analytics and create different types of static and animated visualizations and dashboards for rich user experiences. We then move on to interlinking different data sources with Tableau's Data Model capabilities, along with maps and geospatial visualization. You will further use Tableau Prep Builder's ability to efficiently clean and structure data. By the end of this book, you will be proficient in implementing the powerful features of Tableau 2022 to improve the business intelligence insights you can extract from your data. What you will learnDevelop stunning visualizations to explain complex data with clarityBuild interactive dashboards to drive actionable user insightsExplore Data Model capabilities and interlink data from various sourcesCreate and use calculations to solve problems and enrich your analyticsEnable smart decision-making with data clustering, distribution, and forecastingExtend Tableau's native functionality with extensions, scripts, and AI through CRM Analytics (formerly Einstein Analytics)Leverage Tableau Prep Builder's amazing capabilities for data cleaning and structuringShare your data stories to build a culture of trust and actionWho this book is for This Tableau book is for aspiring BI developers and data analysts, data scientists, researchers, and anyone else who wants to gain a deeper understanding of data through Tableau. This book starts from the ground up, so you won't need any prior experience with Tableau before you dive in, but a full Tableau license (or 14-day demo license) is essential to be able to make use of all the exercises.

Create, deploy, and test your Python applications, analyses, and models with ease using Streamlit Key Features Learn how to showcase machine learning models in a Streamlit application effectively and efficiently Become an expert Streamlit creator by getting hands-on with complex application creation Discover how Streamlit enables you to create and deploy apps effortlessly Book DescriptionStreamlit shortens the development time for the creation of data-focused web applications, allowing data scientists to create web app prototypes using Python in hours instead of days. Getting Started with Streamlit for Data Science takes a hands-on approach to helping you learn the tips and tricks that will have you up and running with Streamlit in no time. You'll start with the fundamentals of Streamlit by creating a basic app and gradually build on the foundation by producing high-quality graphics with data visualization and testing machine learning models. As you advance through the chapters, you’ll walk through practical examples of both personal data projects and work-related data-focused web applications, and get to grips with more challenging topics such as using Streamlit Components, beautifying your apps, and quick deployment of your new apps. By the end of this book, you’ll be able to create dynamic web apps in Streamlit quickly and effortlessly using the power of Python.What you will learn Set up your first development environment and create a basic Streamlit app from scratch Explore methods for uploading, downloading, and manipulating data in Streamlit apps Create dynamic visualizations in Streamlit using built-in and imported Python libraries Discover strategies for creating and deploying machine learning models in Streamlit Use Streamlit sharing for one-click deployment Beautify Streamlit apps using themes, Streamlit Components, and Streamlit sidebar Implement best practices for prototyping your data science work with Streamlit Who this book is for This book is for data scientists and machine learning enthusiasts who want to create web apps using Streamlit. Whether you’re a junior data scientist looking to deploy your first machine learning project in Python to improve your resume or a senior data scientist who wants to use Streamlit to make convincing and dynamic data analyses, this book will help you get there! Prior knowledge of Python programming will assist with understanding the concepts covered.