Self-service Business Intelligence Tools For Linux Enthusiasts – This is the second post in a blog series about BI tools. First publication in the 21st century. It was about the evolution of business intelligence in the 20th century. This time we will dive into one of the main tools on the market. We’ll describe what sets Tableau apart from its main competitors, what the platform is all about, what the licensing options are, and much more. We will try to be as comprehensive as possible, but not all features can be considered or mentioned. It is very difficult to describe a BI tool in its entirety in a blog post. Contact us if you need a more detailed evaluation or want to see Tableau in action with real content.
Read our blog posts on the new features introduced at Tableau Conference 2021 and a summary of the Tableau product roadmap based on TC22 and TC21 and the Tableau Goes Minority Report at TC23: Takes a Headless Direction in Augmented Reality, Creative AI, and BI.
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That’s what Tableau refers to as its mission: helping people see and understand. Tableau aims to be easy to use so that everyone can use it and extract actionable insights. The table was originally built on visualization research conducted at Stanford University; how to help people’s natural ability to visually and intuitively understand some graphic presentations.
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Tableau Desktop did a great job of making analysis easier and even fun during the dinosaur era of Enterprise BI (read the previous blog post for the dinosaur reference). The success and market penetration of Tableau Desktop meant that the platform needed to be expanded. Tableau Server, Online, Public, Mobile and Prep have since been released. Today, Tableau’s offering is a comprehensive analytics platform with a definite edge over its competitors.
Tableau Access Knowledge Quickly and Easily Overall, it’s very fast to get from the source to valuable knowledge with Tableau. Analyzing and creating visuals and dashboards is simple and straightforward for the most part. Time hierarchies are available, drag and drop analytical templates to use and create many simple calculations (totals, moving averages, parts of totals, rankings, etc.). Ease of use also extends to preparation and modeling. Both of these can be done without deep technical knowledge and coding skills. Perhaps what I appreciate the most in this area is the way in which new features are released and old ones are deprecated: it somehow works. For example, when the new cache that came out in 2018 replaced the old technology, it was done with minimal impact and maintenance for users. The same thing happened in 2020 when a new semantic model layer was introduced and again, no tedious migration from old to new, everything just worked. Incredibly creative Tableau was originally a tool for visualization and visual analysis, and it remains a powerful tool for that. Tableau empowers users’ creativity and ingenuity when analyzing and developing content. What does this mean? In other tools, you typically first select the result you’re looking for (the display type, such as line, area, bar, pie, etc.) and then assign the fields to roles supported by the display type (such as values, legend, axis, tool – information, etc.). If the display doesn’t support something you need (such as small sizes or multiples), then there’s not much you can do.
Tableau works very differently: you can drag and drop areas on the canvas and Tableau will display them appropriately. Some properties of a field can change instantaneously: dimensions can change to masses, discrete fields can become continuous and vice versa. Almost any field can be assigned to any role and different display types can be combined. This approach is more flexible than any other tool I’ve used. However, it may seem complicated at first. Fortunately, Tableau has a Show menu to help you create different visualizations and understand how the tool works. Once you understand it, you can perform powerful visual analytics like never before.
Mapping and Spatial Capabilities As mentioned above, the different types of visualizations are very diverse and flexible in Tableau, but mapping and spatial analysis in particular are top notch. Here’s a quick list of what makes Tableau’s spatial capabilities so great:
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Detailed map of the city center with a street map background, a building layer with dark gray polygons at the bottom and point layers at the top showing area (size) and heating fuel (color).
User-Visualization Interactions The third strength of Tableau is the ability for users to interact with visualizations and the ability for developers to define exactly where and how those interactions occur. Interactions can be used, for example, to filter, highlight, show and hide layout objects, display tooltips, set parameter values and place objects, drill up and drill down, drill down the dashboard to another or external url. Interactions allow business users, especially non-technical users who consume pre-prepared content, to access more information and insights from a single dashboard without having to create multiple dashboards or go through full-panel mode. The flexibility of desktop infrastructure and governance is the same tool, no matter how and where you choose to deploy it (on-premises, public cloud, or SaaS). You can use Windows or Linux servers (or containers) and Windows and Mac desktop computers. You can use different authentication options, user directories and resources without depending on any cloud vendor.
The same flexibility exists when you create content. models can be created in the same way and functionality regardless of whether they are in output or live mode. And you can even combine output and live mode content in the same panel. The same scripting language is used when preparing and building visualizations. And it is quite a powerful yet simple and easy to use language. Flexibility continues when you publish content to the server/online. You can structure the contents of folders however you want and apply security policies at the level of detail you need.
Active and passionate user community Tableau’s user community is more active and passionate than the user communities of other business tools. For example, Tableau Public has more than 3.7 million visualizations published by more than 1.5 million users. Anyone can explore and use these visualizations to learn about Tableau and how to use it. The community supports and helps with issues and problems related to the tool, but I personally appreciate the work they do to expand understanding and share visualization best practices and examples. Main functions and workflow
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The table has everything you would expect a modern analytics platform to have. There are no major shortcomings, but there are some areas that need improvement, especially with new features. Tableau can be used to own the entire visual analytics pipeline, from preparation to consumption across multiple channels. This is how the Tableau workflow usually goes.
Preparation If you need preparation skills, Tableau provides this in Tableau Prep. This tool can be used as a desktop client or directly on Tableau Server or Online. Tableau Prep is built around the same easy-to-use mindset as the other components of the platform. The creation of manipulation steps and the entire workflow is very visual, the process is easy to understand and it is easy to see what is happening along the way. Tableau Prep provides standard join, merge, rotate, clean, and stack skills. You can also add new rows and use custom R or Python scripts to calculate new information. The result set can be exported to a file, a database, or as a Tableau extract. Already created prep workflows can be shared and reused, and planning and execution can be controlled using the Prep Conductor plugin. modeling Most modeling is done using the Tableau Desktop client. The exceptions are if you use an external tool with Tableau Prep or the Tableau API to create and refresh summaries. With Tableau Desktop, you connect to resources, select the objects you want, and define the connections and relationships between the objects. Table models today have two layers: the physical layer and the logical (semantic) layer. Separating the two allows the same table model to be reused for different purposes. The logic layer functionality was released with version 2020.2 and is a major update to the model.
While modeling, you chose to use direct binding or output to Tableau’s in-memory column store. No matter what you choose, you have the same features and capabilities that you use, and then you can even change the connection type. An option is also to use incremental refresh so that only new rows are inserted when outputting. The best practice is to check and define all field types, the default format
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