![]() Tip 1: Group or hide as much information as you possibly can The raw data for the data layout in our example product. Here is a data table I've created for a hypothetical shipping / logistics tracking app that I'll use as an example in this section. Remember to keep in mind how people are actually using the data, or want to be using it, not how you wish for them to use it. I am hoping that the next time you encounter this, you can use these tips to push your product past the obvious and into a great experience for your users. There have been many times I’ve inherited a design that looks like it was copied straight from Excel. Many data-based designs stop at the previous step. Organizing and optimizing data-based layouts This means getting feedback early with your concepts, then later on the execution of that idea, and then finally on the nitty-gritty details before handoff. Good designs get buy-in and feedback from your team, users, and stakeholders throughout the design’s evolution. No matter how much work you put into your design, you likely aren't the one using it. Step 4: Apply basic UI principles to the layout and begin to iterate on your designĭon’t forget to ask for feedback. Note that you can paste data into the Data Grid control straight from Excel or other spreadsheet tools. ![]() Step 3: Add the raw content into the layout Try to approximate the size and space it may need. Use rectangles and Line of Text controls. Step 2: Begin to add rough placeholder content How much is there? What are the pieces of information that will be used most to do the job? Step 1: Create a layout of the screen(s) by sketching blocks or assembling sticky notes The best approach is to start with a high-level layout.įor data-based design projects, start by reviewing the raw data that will populate this new product. ![]() When starting from scratch there is a temptation to start by creating visual designs and writing code, but take a step back. Now that you have the necessary background needed to start, let’s dive into the design of it. You might assume your user only uses your application, but it may be a part of a larger workflow. Their eyes aren’t being guided through the interface in the way it is with the smaller screen. Too much white space can cause users to strain to follow the data from one point to the next. Knowing what space they have available and what other content will be around your product will help guide your design choices, too. Do you know how big their monitor is? Do they use dual monitors? If so, how many windows do they have open while working with your product? Do they have them open at the same time or one at a time? User setups and workflows also affect your design. ![]() If you’re creating an internal product for your company or a new consumer product, you’ll need to answer questions like: What will they do with it once they have it? Do they want to find the status of something? Generate a report? Enter new data? When you're tasked with designing an interface with lots of data, it must not overload the user's senses so much that it slows them down or increases the chance of mistakes. Good data design lets you scan, decide and act efficiently. Then make smart design choices to organize the data logically and prevent it from being overwhelming. With more and more products being powered by piles of data, how do you present it in an easy-to-understand format? Start by following the same approach as for any other design project: Understand how the user needs to interact with or use the content. Here are some easy-to-understand tips to ensure that your data applications are easy to use. Big data can cause big problems for clean, usable interface designs.
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