What’s a Data App?
What are data apps?
Put simply, a data app is an application that allows its users to interact with data. With more and more people now working with data daily, they need effective ways to present and share insights. An application needs to tick off just two requirements to be considered a data app.
- It has to be an online application based on data
- It has to have a user interface designed to help the user draw conclusions or take action
As you can see, this is quite a broad definition—hence the continued growth.
Why do we need them?
Data apps can be classified into two categories: 'general-purpose' and 'bespoke'. A general-purpose data app, like Excel or Tableau, allows users to import data and perform their own analysis, provided they have a certain level of skill and understanding.
Growth has largely come via the bespoke bucket. These are the apps that democratize analysis, allowing non-expert users to process the data and extract their own insights. They act as a conduit between data experts and non-technical users, meaning they need to be easily used, shared, and scaled for maximum effect.
For teams within a business, data apps serve as a single source of truth. They connect each member to the same dataset and provide a tailored experience (think Google Analytics). Customer-facing data apps, meanwhile, allow businesses to show potential clients the personalized offering they can provide, like a financial services company creating a customizable planning calculator.
Data Apps vs. BI Tools
Based on the definition that data apps are simply based on data and contain a user interface, there is clear overlap between these apps and traditional Business Intelligence (BI) tools. BI tools emerged as a way for businesses to analyze and visualize data, then share insights across the organization. This often involved static reports and basic visualizations, with little regard to speed and performance.
In many ways, this new wave picks up where BI tools left off. The objective is still to make data more accessible and easily interpreted, however, data apps are defined by dynamic interfaces and real-time data interactions, serving targeted data that is relevant to each individual user. BI tools typically present historical data, while data apps look forward and provide predictions based on dynamic data. Modern solutions provide users with greater control over the data and are easier to build than ever before.
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Examples
One of the most common examples of a bespoke app is an interactive dashboards. The sophistication of these dashboards varies greatly. At the simpler end of the spectrum are dashboards you would typically see generated by Business Intelligence (BI) tools. These tend to be based on a small amount of data and only perform simple analysis and visualization.
This then moves into larger enterprise-grade data apps. An ecommerce company may build a data app to forecast stock shortfalls, or a rideshare business could build an app to identify regions in a city with higher demand for drivers. Displayr has powered countless examples of enterprise-grade interactive dashboards, ranging from NPS tracking to Product Preference dashboards.
Another popular type of app is an online calculator. Australian bank NAB has launched a series of home loan calculators that allow prospective homeowners to see their borrowing power and calculate monthly mortgage repayments based on current interest rates. Users can also book an appointment with a banker straight from the calculator, saving all the information they have provided and ensuring a smoother experience.
Displayr offers an all-in-one data app builder, allowing users to build, customize, and host their entire app with one solution. It is scalable for your skillset, with drag-and-drop solutions and full R integration for those who prefer to code.
