Can you make your data more presentable simply by changing a few elements of its design, while also avoiding major pitfalls along the way?
Awareness and demand for data-driven insights is at an all-time high. Speaking to DBS employees at DAX U held at DBS Asia X, Tableau’s sales consultant Andrew Hill highlighted how the company makes databases and spreadsheets understandable through simple visualisation.
What is the role of visual analytics for the fintech industry at large?
The role of visual analytics has changed in the last decade. Rewind a decade and you’ll find that most people didn’t even know what visual analytics was. In the past, it was often mixed with the idea of enterprise-ready business intelligence, which really has nothing to do with the topic. From there, we’ve seen it grow into a special set of skills.
Within the fintech industry, data remains one of the core elements that drives how financial institutions can provide more efficient services for their customers. With businesses becoming more data driven, the centrality of data is becoming more apparent.
It was eye-opening to learn how the same piece of data can be presented differently, generating a whole different set of insights
Why is the democratisation of data so important? What is the biggest demand/application of visual analytics?
Traditionally, the ability to ask questions about data lies with the elite few – those well-versed in data science. The constant back-and-forth between the people who know data and those who don’t is a lengthy process, simply because both parties never quite understand each other’s jobs. The democratisation of data aims to solve that by giving everyone the ability to ask questions about their data.
The use cases for visual analytics are becoming broader as we discover its applications – from front office to back office implementations. The biggest draw is allowing everyone, regardless of their familiarity with data science, to gain actionable insights from data.
Is there any bias that gets in the way of how you represent data? How do you avoid these situations?
Authors will inherently add their own bias to dashboards, sometimes enriching data according to their needs. While we can’t entirely stop this, it is important that people are aware that this happens, and are always critical of how data is being represented. Administrators can decide who has access to certain dashboard functions, allowing them to double check their work or prevent queries that only highlight favourable trends. It is a balance between providing convenient access to everyone and maintaining the integrity of the data being represented.
What are your top predictions for the next 5 years?
Bill Gates has a great quote I love, “We always overestimate the change that will occur in the next two years and underestimate the change that will occur in the next 10.”
We’re seeing an overestimation and over reliance on Machine Learning (ML) and Artificial Intelligence (AI) as a tool that will answer all our questions and problems. Regardless of how these technologies develop, they will still have a human element.
I like to use the analogy of a doctor – analytical models have been developed to diagnose and predict illnesses better than human doctors, but you still need actual doctors, much like how you need a chef in the kitchen.
But AI aside, the biggest change in the future within the business intelligence space is augmented intelligence. These are the tools that will assist us in performing our jobs, complementing our roles and making us more efficient at what we do.
How do you think a company can leverage data more effectively?
Data is a company’s competitive advantage, especially for financial services, as it empowers them to make decisions faster and accelerate their speed to insight. We are increasingly seeing a shift in focus to the customer, creating unique experiences and delivering outstanding customer service. Data on customers will help companies to retain users by providing unique experiences.
Do you think a right-brainer can function well as a data analyst?
It doesn’t matter if you’re left- or right-brained. You need both to do this job well. Let’s take myself for example – I can get the answer to almost any question you have using Tableau Desktop. But I’m not an expert in making it look good. I just need the answers, and it doesn’t matter to me if the colour scheme is nice. But no matter how reliable your data is, the inability to present it well makes it unusable.
Design and visuals are an important part of dashboards because our reactions to well-presented data are visceral – a good dashboard makes you want to dig in and find out more. We’ve found that changing the design of dashboards without editing any of the data results in increased adoption and subscription rates. If you download a new programme, and the first screen you see looks like Windows 3.1 with 600 drop-down menus, it’s an immediate turn off. The same is true of a dashboard.
Any words of wisdom for data science/analytics students starting their career?
You’re in a great industry. The pie is getting bigger, but it is also more competitive than it has ever been. You won’t be able to get away with what I did, which is to learn one tool very well. To stay on top, you will need to learn a breadth of skillsets, such as data science, business intelligence, and knowledge of Extract, Transform, Load (ETL) tools. Even now I am having to learn all these skills. As long as an organisation chooses to go the route of easier data discovery and data democratisation, it doesn’t matter what tool you use – everybody wins!
DAX U is a series consisting of curated curriculum about innovation in different fields, offering DBS staff and the innovation community additional learning resources. Topics ranging from technology in animation to photography are shared via brown bag sessions and mini-workshops conducted at DBS Asia X.