Log in to like this post! How To Choose the Best Angular Data Visualization Library Zdravko Kolev / Tuesday, November 15, 2022 Businesses run on data. The world runs on data. Your Angular app also runs on data. And people have to process it. But if the human brain can take about 11 million bits of information in a second, how can you help the conscious mind handle the critical 40 to 50 bits of information in a second that remain? In the world of Angular programming, this happens with the help of Angular data visualization libraries. So, straight to the question, how to choose the best angular graph visualization library for your project? Now, this may sound like any-popular-charting-library-can-do-it sort of thing. But there are several key factors in one such library that we want to point out in this blog as being extremely critical and vital. Our quick guide will: Show you what an effective data visualization in Angular looks like. Highlight the top features of a genuinely powerful library that you must keep an eye on before you make up your mind and go with one option or another. Read further. The Ideal Angular Data Visualization Library – What It Looks Like? Behind any powerful Angular data visualization there is a powerful charting library. And it’s the highly visual, data-driven era that we live and work in that demands the use of it. The main reason for implementing graphs and charts in your Angular app is to display data in the most consumable and lively way so users can not only easily comprehend it but manipulate it as well whenever they have to. In this regard, I say that the best tools are packed with a variety of visualization styles, can render heavy data sets quickly, and offer simplicity and easiness in terms of how you use them. Here is a well-done Angular data visualization example that takes the given data and presents it efficiently and strategically. What you see is a simple but informative Angular Financial Chart, enabling users to read data sets of any size at a quick glance and use different Indicators like Bollinger Bands, RSI, Price Oscillators and a lot more. This leads us to the question, what to look for in data visualization tools to set apart the one that fits your application? The Top Features & Factors to Consider Before Plotting Your Data Most of us will decide on a chart based solely on how nice it looks, however, there is an established science that goes along with the art of meaningful, and beautiful data visualization. It is important to establish a criterion that will help you distinguish between the right choice and the one that may turn out inefficient (though perhaps beautiful) once you start developing your data-driven Angular project. Here’s what to pay close attention to: 1. Chart & Graph Types When working on large projects for multiple sectors, you need a library that includes a rich set of chart types for any scenario to create anything - from a single chart display to an interactive dashboard. There are 4 basic charts and graphs categories: Comparison Charts Comparison chart Relationship chart Distribution chart Composition chart And within a comprehensive Angular Graph Visualization library you must look for the following types – Area chart, Bar chart, Pie chart, Donut chart, Line chart, Bubble chart, Scatter chart, Treemap, and so on. A more detailed overview about them can be found in this How to Choose the Best Angular Chart for Your Project blog post. 2. Features & Customizations Performance, High volume data points, Interactive panning, Mouse, Keyboard and Touch controls, Highlighting, Zooming, Animation - these are all must-have features that you should require from every charting library to create better Angular visualization scenarios. Enabling Performance, it will render millions of data points and updates them every few milliseconds. If you decide to implement the highlighting feature, then this will compare and distinguish between two or more categories of products to see which sells better, for example. Then, you might need to define new modes, apply visual customizations, and custom interactions, depending on the complexity of the chart design. So, check if there are things like: Real-time data support, Advanced Tooltips, Data point Event Handlers Interactivity because interactive charts are much better than static JPG images Does the Angular graph visualization library you’re looking at have all these? Then, go for it. 3. Data Binding & Efficient Data Handling One of the most crucial things to consider is how easy it is to work with local or remote data integration when using one or other angular graph visualization platform. And most importantly, does the library support it at all? It’s simply mandatory for your Angular graph visualization library to be able to effortlessly connect to any data source. 4. Flexibility vs Usability Angular graph visualization tools that deliver flexibility are usually fully featured because their goal is to grant you full configuration control, customizable UX/UI elements and styles, and advanced analytical capabilities. But if you’re less technical and want to get started quickly, you may want to consider an Angular visualization library that aims at providing ease-of-use instead, with must-have features like panning, zooming, selection, and not so many options for detailed fine-tuning. These also focus on reusability. Which is great because they let you reuse code that defines components and services and easily import it from one project to another. 5. Documentation & Learning Resources The final segment to consider is what sources of information and guides are available within the charting library that will help you get started. Things to look for: well-written documentation, sample charts, video tutorials, support, blogs, forums, GitHub transparency. Angular Data Visualization Use Cases Angular charts are fundamental when you want to design and build data viz experiences, helping achieve business, scientific, financial, marketing goals and so forth. They are ideal when you aim at: Transforming boring graphs and charts into interactive data-rich insights. Taking complex data (often KPIs) and making it consumable, so it conveys information properly. Comparing products and services. Showing team progress, market growth, sales, marketing advantages. Visualizing scenarios, results, and even specific processes and phases like in the “product-market-fit” process. Providing a great mobile-first approach for building beautiful interactive charts and dashboards with a single code base. Enabling interactions and offering systematized, consumable data. Building responsive architecture that works great on every modern browser and device. Questions To Consider: What type of data do you have to visualize? Is it complex and voluminous? Are you going to use the library for visual analytics/exploration or data storytelling/explanation What industry will the app serve and what is the purpose? For internal reporting, financial and post-trading analysis, stock evaluation, emphasizing trends/changes in data over time, or something else? Do you need standard features or something out-of-the-box that is fully packed? Is there going to be multiple-view options like zooming, grid-view, right-click menu, chart scroll, etc.? What are the users? Data analysts and data scientists, Business users, consultants, website page visitors, marketers? Why Should You Choose Ignite UI For Angular Charts For Your Next Project? On a final note, Ignite UI for Angular visualization library packs more than 65 different chart and graph types, including Pie, Bar, Area, Line, Point, Stacked, Donut, Scatter, Gauge, Polar, Treemap, Financial/Stock, Geospatial Maps and more for your mobile or web apps. What makes our Angular chart so great and distinguishes it from others is the full support for chart features like: Responsive Web Design built in Interactive Panning and Zooming with Mouse, Keyboard and Touch Full Control of Chart Animation Chart Drill-Down Events Real-Time Streaming Support High-Volume (Millions of Data Points) Support Trends Lines and other Data Analysis features Using it, you are empowered to go from a simple chart with a single data series to more complex data stories with multiple series of data, having multiple axis in composite views, and more.