Self-service Business Intelligence Tools For Analyzing Linux Server Logs – This is the second post in a blog series about BI tools. The first post was about the evolution of business intelligence in the 21st century. This time we explore one of the leading tools on the market. We describe what sets Tableau apart from key competitors, what the platform includes, licensing options and more. We try to be as comprehensive as possible, but not all features can be considered or mentioned. It is very challenging to describe a BI tool well in a blog post. Contact us if you need a more detailed evaluation or want to see Tableau in action with real materials.
Read our blog posts about the new features introduced at the Tableau Conference 2021 and an overview of the Tableau product roadmap based on the Tableau Goes Minority Report at TC22 and TC21 and TC23 – leading to augmented reality, generative AI and headless BI .
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This is what Tableau refers to as their mission: to help people see and understand them. Tableau aims to be easy to use, so anyone can use it and get useful information. Tableau was originally created based on visualization research done at Stanford University; How do people support their natural ability to think visually and intuitively understand various graphic representations.
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Tableau Desktop has done a great job of making analytics easy and fun in the age of enterprise BI dinosaurs (read previous blog post for context on dinosaurs). Success and market penetration with Tableau Desktop meant that the platform needed to be expanded. Tableau Server, Online, Public, Mobile and Prep have since been released. Today Tableau offers a comprehensive analytics platform with a unique twist compared to competitors.
Implement Tableau quickly and easily with Tableau It’s usually much faster to get valuable insights from a source with Tableau. Analysis and creation of visuals and dashboards are usually very easy and smooth. There are time series available out of the box, drag and drop analytical templates to use and create a good amount of simple calculations (moving total, moving average, proportion of totals, ranks etc.). Easy to use is also for preparation and modeling. Both of these can be done without deep technical knowledge and coding skills. Perhaps what I am most grateful for in this area is how new features are published and old ones are cut: in a way it works. For example, when the new in-memory abstract storage replaced the old technology in 2018, it was done with minimal impact and maintenance work for users. The same thing happened in 2020 when a new semantic model layer was introduced, and again, no laborious migration from old to new, everything works. Extraordinary creativity Tableau was originally a tool for visualization and visual analysis, and it remains very strong for that. Tableau empowers users to be creative and inventive in analyzing and developing content. What does it mean? In other tools, you usually first select the desired result you are looking for (visualization type such as line, area, bar, pie, etc.) and then assign the fields to roles that correspond to the visualization type. supported (eg value, legend, axis, tooltip, etc.). There isn’t much you can do if the visualization doesn’t support what you need (eg size or mini-attributes).
Tableau works very differently: you can drag and drop surfaces into the canvas and Tableau will visualize an appropriate path. Some properties of a field can be changed on the fly: dimensions can be converted to measures, discrete fields to constants, and vice versa. Almost any field can be assigned to any role, and different types of visualizations can be added. This approach is more flexible than any other tool I’ve used. However, it may seem complicated at first. Fortunately, Tableau has a Show Me menu to help you create different visualizations and understand how the tool works. Once you get it right, you’ll be able to perform powerful visual analytics like never before.
Map and Spatial Skills As mentioned earlier, the different types of visualization in Tableau are very diverse and flexible, but maps and spatial analysis stand out in particular. Here’s a short list of what makes Tableau’s spatial capabilities so great:
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Detailed city center map with street map as background, dark gray polygonal building layer below and point layer above showing floor area (size) and heating fuel (color).
Interactions between users and visualizations A third strength of Tableau is the ability for users to interact with visualizations and the ability for the developer to define where and how these interactions occur. Interactions can be used, for example, to filter, highlight, show and hide layout objects, show tooltips, define values for parameters and set objects, drill up and down, drill down to another dashboard. url. Interactivity can especially enable non-technical business users who use pre-built content to get more information from a single dashboard without the need to create multiple dashboards or go into full self-service mode. The flexibility of the infrastructure and governance framework is exactly the same regardless of how and where you choose to deploy it (on-premise, public cloud or SaaS). You can use Windows or Linux servers (or containers) and Windows and Mac computers for desktop. You can use different authentication options, user directories and resources without mandatory dependencies for any cloud vendor.
The same flexibility exists when creating content. Models can be created in exactly the same way and functionality, whether in abstract or live mode. And you can also add abstract and live mode content on the same dashboard. The same scripting language is used when designing and creating visualizations. And it is a quite powerful, but easy to use and simple language. Flexibility continues when you publish content on servers/online. You can structure contents and folders as you wish and the security policy at the level of detail you need.
Active and passionate user community The Tableau user community is more active and passionate than other enterprise tool user communities. For example, Tableau Public has more than 3.7 million published visualizations from more than 1.5 million users. Anyone can view 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 spread understanding and share visualization best practices and examples. Key Functions and Workflows
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Tableau includes everything one would expect from a modern analytics platform. There are no major drawbacks, but there are clearly some areas for improvement, especially in relation to new features. Tableau can be used to master the entire visual analytics pipeline, from preparation to multiple consumption methods, across multiple channels. This is how Tableau’s workflow typically goes.
Preparation If you need preparation skills, Tableau offers these within Tableau Preparation. This tool can be used as a desktop client or directly in Tableau Server or online. Tableau Preparation is built around the same easy-to-use mentality as other parts of the platform. Create manipulation steps and the entire workflow is very visual, the process is easy to understand and it is easy to see what happens along the way. Tableau Prep offers standard wrangling skills to join, union, pivot, clean and perfect. You can add new rows and use custom R or Python scripts to calculate new insights. The result set can be printed as a file, as a base or as a tabular abstract. Pre-designed workflows can be shared and reused, and scheduling and execution can be monitored via the Prep Conductor add-on. Modeling Modeling is mostly done with the Tableau desktop client. Exceptions are if you use Tableau Prep or an external tool with Tableau API to create and refresh extracts. With Tableau Desktop you connect to resources, select the objects you want and define connections and relationships between objects. Tableau models today consist of two layers: the physical layer and the logical (semantic) layer. Separating the two makes it possible to use the same tableau model for different purposes. Logical layer functionality was published with version 2020.2 and is a significant update of the model.
When modeling you choose whether to use live connections or extract tableau columns to memory storage. Whatever you choose, you will have exactly the same functionalities and capabilities in use and you can even change the connection type later. One possibility is also to use an incremental refresh, so that only new rows are inserted into the extract. The best practice is to check and define the default formatting for all field types
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