Fulfilling roles in data
AS accountants, we apply the language of business to bring much-needed clarity into the decision room. It helps us provide insight and report on tax, budgeting, profitability and other incidental concerns. There is plenty to keep us ticking along.
For a growing subset, however, curiosities extend beyond the natural boundaries of our domain. The allure of data and tech has fascinated many of us for some time.
“It’s like learning a new language,” says Luxembourg-based Alexander Belov FCCA, data engineer at Revantage Europe. He says of shifting the mindset from accounting lexicon to programming, “you sweat and grind for a long time and eventually you learn to say ‘Hello, world’.”
Belov attributes achieving this level of knowledge and skill so quickly to “moving around a lot. I took on new opportunities and challenges.”
He says he had to make trade-offs between career progression in traditional accounting and his own development as a data expert, and that the experience forced him to learn and grow.
Belov’s best work, he says, is a tool he created to give senior stakeholders real-time insight into business activity. The solution pooled transactional data from unrelated systems, cleaned and stored it in a custom database, and presented it in an interactive dashboard. The best part is that it was all automated.
He says that making the progression from an entry-level developer to a more confident, mid-level one needed the support of his manager: “He took a chance on me.” Being given his first proper data analyst role allowed him to develop the skills and confidence that have carried him throughout his data career. The tasks were simple enough to understand and conceive, yet challenging enough to stretch and develop his abilities; it was, he says, a period of exponential growth.
Sarada Lee FCCA, co-founder of Perth Machine Learning Group in Australia, agrees that having encouragement from colleagues is vital in the tech learning journey. “I met some really amazing people who encouraged me to take my studies further,” she says.
Lee’s journey in machine learning and artificial intelligence (AI) started when she was between roles with some free time and decided to pursue a nagging interest in AI. A self-confessed introvert, she challenged herself to participate in hackathons and showcase her work. Through her endeavours, she found a community that supported this exciting new venture.
She eventually got into a fellowship programme that saw her applying her newly acquired skills to real-world needs. It led her to co-author an academic paper that applied a machine learning algorithm in counting human immune cells, a much faster approach compared to using human counters. “It’s one of my proudest moments,” says Lee.
Community and connection have been important to Lee. To pay it forward, she co-founded the Perth Machine Learning Group to support anyone looking to delve into this field. In 2019 she was recognised for this and other contributions, and received the Women in Technology WA Tech [+] 20 Award.
So, what attributes in accountancy professionals carry over into programming? “We are very detail-oriented, and programming requires a lot of attention to detail,” says Lee. This is especially crucial in debugging code, arguably a programmer’s worst nightmare.
Lee also points out that accountants’ natural audit and compliance abilities fit well with data governance. This growing field deals with pressing questions around data access, use, integrity and security.
Her advice to others looking to dive into programming: “Have a go. Be vulnerable and ask for help, and be open to failure.”
Professional accountants are already well versed in one form of tech, at least: Excel. Chong Yu Tee, FCCA, a Singapore-based director of data analytics and a lecturer in two of the city-state’s leading universities, points out that there is transferable learning from this software to more sophisticated data analytics.
“For example, when you use ‘vLookup’ in Excel, you are essentially exploring table relationships, a foundational concept in data analytics,” he says, adding that “pivot tables enable exploratory data analysis, another core concept”.
The foundational ideas around data are readily accessible to accountants through Excel, but for the more advanced users, Chong Yu points out that the Visual Basic Editor, used to automate tasks in Excel, feels like Python, SQL and any other programming language.
Chong Yu has built a career helping audit clients peek into their data and has contributed novel insights into management reports, a less inspiring part of the financial statement audit for many.
He says that switching to a data-focused role is easier to do early in a career. But for those more advanced in their careers and wanting to avoid starting from scratch, he recommends finding a niche opportunity that combines existing industry knowledge with new skills to add value at a high level.
In either case, his advice to anyone looking to step into data and tech is to pursue it out of a genuine interest in learning and growth.
If you’re looking to apply your skills in new and exciting direction, data analysis might be the place for you.
Author: Dean Hezekiah FCCA is an accountant who writes on business and professional themes
Source: ACCA, Accounting and Business magazine