On code_n last week I had conversations with quite a few people, from both, big and small companies and from various industries. While many exhibitors demoed very cool artificial intelligence apps for all sorts of contexts, our mantra was “tell stories with data”.
A great opening line to converse about experiences, or lack thereof, that people have with data. Data is the new messiah for all the hopes and dreams of becoming more effective and efficient in our everyday lives. And while people agreed that the complex challenges we are all facing, can only be responded with data technology and data science, it was also clear that we are miles away from granting non-data-experts easy access to insights, as well as from providing transparency into the quality of the data that drives our intelligent machines.
There is no such thing as an easy way to dip one's toes into the sea of data to explore.
This needs to change. And it will change, once people have had the opportunity to look behind the scenes, to understand the challenges and the opportunity that lies in combining data science, data engineering and design in a simple approach to effectively get valuable data insights.
Start simple, explore and expand.
Telling stories with data can come in many shapes and forms. A simple explanatory visualization, if it drives sensible action, is a good start to deliver value right then and there. An assembly of interconnected charts that address various angles of a topic - like a report, can provide grand insight into how things are related to one another. Something interactive that people can explore freely - like an analysis or predictive application to become more pro-active. A monitor that visualizes the state of the system and its underlying data, can foster trust and give the good feeling of being in control. Even language provides natural interaction with- and a narrative thru data.
The process of transforming data into meaning and stories by adding empathy to technology is unique and universal at the same time. It can be applied to any subject matter, while considering usage context and related topics, such as data confidentiality.
It is an iterative process with the following basic components: 1) design methods – to filter out what’s relevant, 2) data technology – to model and process various data types, 3) data science – to transform data and to build prediction models, 4) design – to visualize data in a way that it enables people to draw the right conclusions, 5) testing and user validations – to ensure, that the solution is inline with goals and people’s needs, 6) full stack development – to automate the process and build data driven applications, and last but not least, 7) a positive service experience – that supports people when they get stuck.
Our design is enabled by technology. Our technology is driven by empathy for people and their needs. incontext.technology and DATA and YOU. The owl that can see in the dark and hear from afar, now has a heart that stands for human needs.
Telling stories with data means to connect with data in a human way. It is a new way of looking at the world.