Starting with the basics and building toward advanced topics such as multidimensional analysis and user experience, you'll explore pragmatic and creative examples that you can apply to your own data. Staying competitive today requires the ability to quickly analyze and visualize data and make data-driven decisions. With this guide, data practitioners and leaders alike will learn strategies for building compelling and purposeful visualizations, dashboards, and data products. Every chapter contains the why behind the solution and the technical knowledge you need to make it work.
Use this book as a high-value on-the-job reference guide to Tableau Visualize different data types and tackle specific data challenges Create compelling data visualizations, dashboards, and data products Learn how to generate industry-specific analytics Explore categorical and quantitative analysis and comparisons Understand geospatial, dynamic, statistical, and multivariate analysis Communicate the value of the Tableau platform to your team and to stakeholders.
This book will guide you from the basic functionality of Tableau It is full of useful recipes from industry experts, who will help you master your Tableau skills. The complexity of tasks increase gradually, all the way to mastering advanced functionality through bite-sized, detailed recipes.
The best-selling Revit guide, now more complete than ever with all-new coverage on the release Mastering Autodesk Revit is packed with focused discussions, detailed exercises, and real-world examples to help you get up to speed quickly on the latest version of Autodesk Revit.
Organized according to how you learn and implement the software, this book provides expert guidance for all skill levels. Hands-on tutorials allow you to dive right in and start accomplishing vital tasks, while compelling examples illustrate how Revit for Architecture is used in every project. Available online downloads include before-and-after tutorial files and additional advanced content to help you quickly master this powerful software.
From basic interface topics to advanced visualization techniques and documentation, this invaluable guide is your ideal companion through the Revit workflow. Whether you're preparing for Autodesk certification exams or just want to become more productive with the architectural design software, practical exercises and expert instruction will get you where you need to be.
Understand key BIM and Revit concepts and master the Revit interface Delve into templates, work-sharing, and managing Revit projects Master modeling and massing, the Family Editor, and visualization techniques Explore documentation, including annotation, detailing, and complex structures BIM software has become a mandatory asset in today's architecture field; automated documentation updates reduce errors while saving time and money, and Autodesk's Revit is the industry leader in the BIM software space.
Explore and understand data with the powerful data visualization techniques of Tableau, and then communicate insights in powerful ways Key Features Apply best practices in data visualization and chart types exploration Explore the latest version of Tableau Desktop with hands-on examples Understand the fundamentals of Tableau storytelling Book Description Graphical presentation of data enables us to easily understand complex data sets.
Tableau 10 Complete Reference provides easy-to-follow recipes with several use cases and real-world business scenarios to get you up and running with Tableau This Learning Path begins with the history of data visualization and its importance in today's businesses.
You'll also be introduced to Tableau - how to connect, clean, and analyze data in this visual analytics software. Then, you'll learn how to apply what you've learned by creating some simple calculations in Tableau and using Table Calculations to help drive greater analysis from your data. Next, you'll explore different advanced chart types in Tableau.
These chart types require you to have some understanding of the Tableau interface and understand basic calculations. A number of recipes specifically for geospatial visualization, analytics, and data preparation are also covered.
Last but not least, you'll learn about the power of storytelling through the creation of interactive dashboards in Tableau. Through this Learning Path, you will gain confidence and competence to analyze and communicate data and insights more efficiently and effectively by creating compelling interactive charts, dashboards, and stories in Tableau. Milligan Getting Started with Tableau It is also used for BI professionals and data analysts who want to do better at their jobs.
Leverage the power of Tableau The latest release, Tableau Getting Started with Tableau The book starts by highlighting the new functionalities of Tableau You'll learn how to connect to data, build a data source, visualize your data, build a dashboard, and even share data online. In the concluding chapters, you'll delve into advanced techniques such as creating a cross-database join and data blending.
By the end of this book, you will be able to use Tableau effectively to create quick, cost-effective, and business-efficient Business Intelligence BI solutions. Some experience of Tableau is assumed, however, the book also features introductory concepts, which even beginners can take advantage of. Learn how to create effective data visualizations with Tableau and unlock a smarter approach to business analytics.
It might just transform your organization About This Book Create stylish visualizations and dashboards that explain complexity with clarity Learn effective data storytelling to transform how your business uses ideas and makes decisions Explore all the new features in Tableau 10 and start to redefine what business analytics means to your organization Who This Book Is For Got data?
Since the release of Tableau Hyper is Tableau's data-handling engine, which is usually not well understood by even advanced developers, because it's not an overt part of day-to-day activities; however, if you want to truly grasp how to prepare data for Tableau, this understanding is crucial.
Hyper originally started as a research project at the University of Munich in In , it was acquired by Tableau and appointed as the dedicated data engine group of Tableau, maintaining its base and employees in Munich. Initially in It is still true that live connections are not touched by Hyper, but Tableau Prep Builder now runs on the Hyper engine too, with more use cases to follow.
The vision shared by the founders of Hyper was to create a high-performing, next-generation database; one system, one state, no trade-offs, and no delays. And it worked—today, Hyper can serve general database purposes, data ingestion, and analytics at the same time. Memory prices have decreased exponentially. The same goes for CPUs; transistor counts increased according to Moore's law, while other features stagnated.
Memory is cheap but processing still needs to be improved. Moore's Law is the observation made by Intel co-founder Gordon Moore that the number of transistors on a chip doubles every two years while the costs are halved.
In , Gordon Moore noticed that the number of transistors per square inch on integrated circuits had doubled every two years since their invention. While experimenting with Hyper, the founders measured that handwritten C code is faster than any existing database engine, so they came up with the idea to transform Tableau Queries into LLVM code and optimize it simultaneously, all behind the scenes, so the Tableau user won't notice it.
This translation and optimization comes at a cost; traditional database engines can start executing code immediately. Tableau needs to first translate queries into code, optimize that code, then compile it into machine code, after which it can be executed. So the big question is, is it still faster?
As proven by many tests on Tableau Public and other workbooks, the answer is yes! Furthermore, if there is a query estimated to be faster if executed without the compilation to machine code, Tableau has its own virtual machine VM in which the query will be executed right away.
This is due to the unique and innovative technique of morsel-driven parallelization. Executing those steps simultaneously makes it more efficient and more performant, as opposed to traditional systems where those three steps are separated and executed one after the other. To sum up, Hyper is a highly specialized database engine that allows us as users to get the best out of our queries. If you recall, in Chapter 1 , Getting Up to Speed — A Review of the Basics , we already saw that every change on a sheet or dashboard, including drag and drop pills, filters, and calculated fields, among others, are translated into queries.
VizQL, another hidden gem in your Tableau Desktop, is responsible for visualizing data into chart format and is fully executed in memory. The advantage is that no additional space on the database site is required here.
VizQL is generated when a user places a field on a shelf. Two aspects of the VizQL module are of primary importance:. We'll discuss these two aspects in more detail in the following sections. In this section, we'll demonstrate how changing a worksheet's field attribution will allow you more flexibility in your dashboard creation. Let's look at the World Happiness Report. AVG Happiness Score is, of course, treated as a measure in this case.
Lastly, sort the countries by their happiness score, highest to lowest. Both pills should be continuous, hence green-colored.
In order to accomplish this, the user defines Happiness Rank as a Dimension , as shown in the following screenshot:. Please note that Columns and Rows have been moved to the left for better readability. This can be achieved by dragging and dropping the shelves. In order to add steps to your visualization, click on Path in the Marks Card and select the second option, Step. You can view the code generated by Tableau that is passed to the data source with the performance recorder, which is accessible through Help , then Settings and Performance , and then Start Performance Recording.
See Chapter 13 , Improving Performance , for additional details. The takeaway is to note that VizQL enables the analyst to change the SQL code input by changing a field from measure to dimension rather than the source metadata. This on-the-fly ability enables creative exploration of the data that's not possible with other tools, and avoids lengthy exercises attempting to define all possible uses for each field. The previous section taught us how we can manipulate data types in Tableau itself without touching the data source and its metadata itself.
In the next section, we will take a closer look at table calculations. In this section, we will explore how VizQL's table calculations can be used to add data to a dashboard without adding any data to the data source.
In the following example, which can be viewed by opening Sheet 4 on this chapter's workbook, note that Freedom on the vertical axis is set to Quick Table Calculation and Moving Average. Calculating a Moving Average , Running Total , or other such comparison calculations can be quite challenging to accomplish in a data source.
Not only must a data architect consider what comparison calculations to include in the data source, but they must also determine the dimensions for which these calculations are relevant. VizQL greatly simplifies such challenges using table calculations, as seen in the following screenshot:. Taking a look at the relevant portion of SQL generated by the preceding worksheet shows that the table calculation is not performed by the data source.
Instead, it is performed in Tableau by the VizQL module. To reiterate, nothing in the preceding call to the data source generates the moving average. Only an aggregated total is returned, and Tableau calculates the moving average with VizQL. This overview of the Tableau data-handling engine demonstrates a flexible approach to interfacing with data. Knowledge of the data-handling engine is helpful if you want to understand the parameters for Tableau data readiness.
Two major takeaways from this section are as follows:. How to Visualize Data with D3 [Video]. How to Visualize Data with R [Video]. Web Designer UK April Penthouse USA January Score] AS [Happiness. Rank] AS [avg:Happiness. Rank:ok] FROM [dbo]. About Mastering Tableau MIT License.
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