Jen Stirrup – författare

Advance your Power BI skills by adding AI to your repertoire at a practice level. With this practical book, business-oriented software engineers and developers will learn the terminologies, practices, and strategy necessary to successfully incorporate AI into your business intelligence estate. Jen Stirrup, CEO of AI and BI leadership consultancy Data Relish, and Thomas Weinandy, research economist at Upside, show you how to use data already available to your organization.

Springboarding from the skills that you already possess, this book adds AI to your organization''s technical capability and expertise with Microsoft Power BI. By using your conceptual knowledge of BI, you''ll learn how to choose the right model for your AI work and identify its value and validity.

Use Power BI to build a good data model for AIDemystify the AI terminology that you need to knowIdentify AI project roles, responsibilities, and teams for AIUse AI models, including supervised machine learning techniquesDevelop and train models in Azure ML for consumption in Power BIImprove your business AI maturity level with Power BIUse the AI feedback loop to help you get started with the next project

Advance your Power BI skills by adding AI to your repertoire at a practice level. With this practical book, business-oriented software engineers and developers will learn the terminologies, practices, and strategy necessary to successfully incorporate AI into your business intelligence estate. Jen Stirrup, CEO of AI and BI leadership consultancy Data Relish, and Thomas Weinandy, research economist at Upside, show you how to use data already available to your organization.

Springboarding from the skills that you already possess, this book adds AI to your organization''s technical capability and expertise with Microsoft Power BI. By using your conceptual knowledge of BI, you''ll learn how to choose the right model for your AI work and identify its value and validity.

Use Power BI to build a good data model for AIDemystify the AI terminology that you need to knowIdentify AI project roles, responsibilities, and teams for AIUse AI models, including supervised machine learning techniquesDevelop and train models in Azure ML for consumption in Power BIImprove your business AI maturity level with Power BIUse the AI feedback loop to help you get started with the next project

Advance your Power BI skills by adding AI to your repertoire at a practice level. With this practical book, business-oriented software engineers and developers will learn the terminologies, practices, and strategy necessary to successfully incorporate AI into your business intelligence estate. Jen Stirrup, CEO of AI and BI leadership consultancy Data Relish, and Thomas Weinandy, research economist at Upside, show you how to use data already available to your organization.Springboarding from the skills that you already possess, this book adds AI to your organization's technical capability and expertise with Microsoft Power BI. By using your conceptual knowledge of BI, you'll learn how to choose the right model for your AI work and identify its value and validity.Use Power BI to build a good data model for AIDemystify the AI terminology that you need to knowIdentify AI project roles, responsibilities, and teams for AIUse AI models, including supervised machine learning techniquesDevelop and train models in Azure ML for consumption in Power BIImprove your business AI maturity level with Power BIUse the AI feedback loop to help you get started with the next project

Master the intricacies of Tableau to create effective data visualizations

Key Features

Arm yourself with an arsenal of advanced chart types and geocoding to efficiently and engagingly present informationMap a grid over a network node diagram and use that grid to demonstrate loads, processing time, and more in TableauIntegrate R with Tableau by utilizing R functions, libraries, and saved models

Book Description

Tableau has emerged as one of the most popular Business Intelligence solutions in recent times, thanks to its powerful and interactive data visualization capabilities. This book will empower you to become a master in Tableau by exploiting the many new features introduced in Tableau 10.0.You will embark on this exciting journey by getting to know the valuable methods of utilizing advanced calculations to solve complex problems. These techniques include creative use of different types of calculations such as row-level, aggregate-level, and more. You will discover how almost any data visualization challenge can be met in Tableau by getting a proper understanding of the tool’s inner workings and creatively exploring possibilities. You’ll be armed with an arsenal of advanced chart types and techniques to enable you to efficiently and engagingly present information to a variety of audiences through the use of clear, efficient, and engaging dashboards. Explanations and examples of efficient and inefficient visualization techniques, well-designed and poorly designed dashboards, and compromise options when Tableau consumers will not embrace data visualization will build on your understanding of Tableau and how to use it efficiently.By the end of the book, you will be equipped with all the information you need to create effective dashboards and data visualization solutions using Tableau.

What you will learn

Create a worksheet that can display the current balance for any given period in timeRecreate a star schema from in a data warehouse in TableauCombine level of detail calculations with table calculations, sets, and parametersCreate custom polygons to build filled maps for area codes in the USAVisualize data using a set of analytical and advanced charting techniquesKnow when to use Tableau instead of PowerPointBuild a dashboard and export it to PowerPoint

Who this book is for

If you are a business analyst without developer-level programming skills, then this book is for you. You are expected to have at least a fundamental understanding of Tableau and basic knowledge of joins, however SQL knowledge is not assumed. You should have basic computer skills, including at least moderate Excel proficiency.

Leverage the power of advanced analytics and predictive modeling in Tableau using the statistical powers of RAbout This Book• A comprehensive guide that will bring out the creativity in you to visualize the results of complex calculations using Tableau and R• Combine Tableau analytics and visualization with the power of R using this step-by-step guide• Wondering how R can be used with Tableau? This book is your one-stop solution.Who This Book Is ForThis book will appeal to Tableau users who want to go beyond the Tableau interface and deploy the full potential of Tableau, by using R to perform advanced analytics with Tableau.A basic familiarity with R is useful but not compulsory, as the book will start off with concrete examples of R and will move quickly into more advanced spheres of analytics using online data sources to support hands-on learning. Those R developers who want to integrate R in Tableau will also benefit from this book.What You Will Learn• Integrate Tableau's analytics with the industry-standard, statistical prowess of R.• Make R function calls in Tableau, and visualize R functions with Tableau using RServe.• Use the CRISP-DM methodology to create a roadmap for analytics investigations.• Implement various supervised and unsupervised learning algorithms in R to return values to Tableau.• Make quick, cogent, and data-driven decisions for your business using advanced analytical techniques such as forecasting, predictions, association rules, clustering, classification, and other advanced Tableau/R calculated field functions.In DetailTableau and R offer accessible analytics by allowing a combination of easy-to-use data visualization along with industry-standard, robust statistical computation.Moving from data visualization into deeper, more advanced analytics? This book will intensify data skills for data viz-savvy users who want to move into analytics and data science in order to enhance their businesses by harnessing the analytical power of R and the stunning visualization capabilities of Tableau. Readers will come across a wide range of machine learning algorithms and learn how descriptive, prescriptive, predictive, and visually appealing analytical solutions can be designed with R and Tableau. In order to maximize learning, hands-on examples will ease the transition from being a data-savvy user to a data analyst using sound statistical tools to perform advanced analytics.By the end of this book, you will get to grips with advanced calculations in R and Tableau for analytics and prediction with the help of use cases and hands-on examples.Style and approachTableau (uniquely) offers excellent visualization combined with advanced analytics; R is at the pinnacle of statistical computational languages. When you want to move from one view of data to another, backed up by complex computations, the combination of R and Tableau makes the perfect solution. This example-rich guide will teach you how to combine these two to perform advanced analytics by integrating Tableau with R and create beautiful data visualizations.