In today’s connected world, there are tons of data being collected from oil pressure sensors to GPS and even heart rate monitors in wearables. This data has value only if we can act on it. One of the more traditional ways of understanding all this data is with data visualization tools such as charts and graphs. Visualizing data on a mobile device can be tricky to do well and there are many tools to choose from. Here are some important factors to consider when evaluating your options.
Having good graph performance is essential to having a good user experience. Do you need to trend a million points or a hundred? Maybe you will trend 20,000 points on ten different trend lines? Both the amount and type of data you show will play into how each tool performs in plotting the graph, panning and zooming. Some graphing suites can aggregate the data up if you have lots of data, but each one has different algorithms. Even the task of picking the type of X-axis to have drastically changes the performance. Infragistics says if you have over a thousand data points, don’t use a Date Time axis and use a String Label axis instead, which makes your implementation more complex. Some tools boast about their abilities for real-time data and others are great for historical data, but each tool will have different limits. The best advice is to build a test application that mocks up your expected data to see which tool can handle your desired implementation.
Flexibility To Meet Your Design
Another important aspect to your application is its design. When a few tools can handle your performance, another way to narrow them down is the UI and graphing options. Picking a tool with the flexibility to meet your design makes life much easier. Creating a design for how the graph will look before you start trying tools is crucial. Shinobi, for example, cannot change something as simple as having unique patterns for dotted lines. Other tools might let you change something, but give you very limited options. Test the UI limits early in your test application, otherwise you may end up with a graph that looks very generic or fails to match the rest of your application’s UI principles.
Support and Documentation For Platform
All of the big paid graphing platforms come with some level of support. Some are direct communication like phone or email while others use public communication in forums. I like to check out the forums of a product to see common issues and feature requests along with how the company has responded and progressed their product. Another very import aspect is documentation. When you are building your test application, you will see a varied degree of examples and API documentation between tool sets. Sometimes the documentation isn’t helpful at all and you can’t find an example on how to add multiple plot lines to multiple Y-axis or how to change the pattern of a line. The better the documentation and examples, the faster your development will be.
Choosing A Data Visualization Tool
Hopefully, exploring these criteria will help you see there is no one graph platform to trend all data. Each mobile application is different and requires research into the best platform for your project and company. Telerik, Shinobi, and Infragistics are the big graphing tools most people will start with. They each offer good but very different products, support, and pricing. My favorite tool for cross-platform graphing is OxyPlot. It is open-source (free) and has one of the best example libraries I have ever seen. It has decent online support because the community is pretty active. OxyPlot’s biggest advantage to the other paid solutions is if you need a feature that is not there, you can add it yourself because you have access to all the source code. At the end of the day, all of the tools require a good look to find the best fit for your application.