Why asking questions is key to becoming a data leader
At Collibra Data Citizens 2021, Bank of America’s Jacklyn Osborne discussed data as an asset for growth and how to become a data leader. …
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Sitting in a swivel chair during the virtual Collibra Data Citizens 2021, Jacklyn Osborne felt transported back to her first job out of college at the Department of Homeland Security, where she swiveled to ask someone nearby if they needed help. The connection ignited her career and taught her the value of a learning opportunity, which has proved vital in today’s evolving data landscape.
Collibra chief data citizen Stijn “Stan” Christiaens, who was hosting the fireside chat, understood her point immediately: “The one thing I’ve seen over 13 years is that data changes seem to be constant.”
Throughout the chat today, Christiaens and Osborne, who is the top risk and finance technology executive at Bank of America, explored data as an asset for driving growth. They also discussed successful data leadership, citing the need to continue learning and to focus on the data and business processes that will provide maximum value.
“It’s a marathon, not a sprint,” Osborne said. “I would rather be 100% for that critical few than try to be 80% doing everything for 100% of the information.”
Throughout the conversation, titled “Accelerating a data-driven information transformation,” Osborne went on to share a range of insights, including upcoming challenges in the data landscape and advice for rising professionals. Below are some highlights from the chat.
From defense to offense
When it comes to breaking down data silos, Christiaens said everyone is trying to figure out data products and remarked on the pull between transformation and the compliance aspect of defense. Osborne agreed the shift from defensive to offensive data practices — turning data from a liability into an asset — is absolutely happening. And it all comes down to the core basics: What data do I have? Where does it come from? Is it of high quality?
“If those three questions can’t be answered, no matter what pretty veneer, no matter what visualization, no matter what models, no matter what AI, it’s still our favorite old saying of ‘garbage in, garbage out,’” she said.
Those three core considerations, she said, are also her measures for success: “I think those who work with me might get sick of those three basic questions because I refer back to [them] for just about everything.”
Delving deeper, she said these core fundamentals include the number of processes, business elements, and golden or authorized sources. When it comes to the sourcing framework, or consuming the right data from the right space, the percent adopted is a huge measure of success. Around the third question, data quality, there’s the number of data dimensions, of data quality rules, of data quality rules passing threshold, and of data quality issues that arise.
Data then and now
Osborne also thought back to her time six years ago at investment banking company UBS. Her work has stayed the same in many ways, she said, but the maturing landscape is changing the day-to-day work of many data professionals.
“The [number] of vendors, products, institutions, industry collaborations, and certifications was non-existent,” she said. “It was really a new domain. It was a new field and in those early days, it was really around defining and designing.”
She said she spent a lot of time writing standards and policies. Thanks to Google, she — and data professionals around the world — can now spend less time defining “what good looks like.”
“My focus is more on that execution, the ‘how do we take those standards and make them real?’ And I think that’s the biggest difference, is turning from defining theory and articulating that strategy of what good looks to actually implementing it and measuring success,” she said.
“Everybody has a strategy until they punch you in the face, I guess,” Christiaens replied. “And indeed, it’s something that in practice, I’ve learned those strategies are important, but in the end you still need to execute on all of it.”
Keeping with the trend of changes, Osborne cited having to navigate the constant evolution in the field while “staying at the top of your game” as the biggest challenge for enterprises. Everything from the role and remit to the responsibility and technologies is changing, more so in the data space than others.
“It is so important, specifically in the data space, to stay in the know,” she said to Christiaens. “Because what was when you and I, Stan, first met in those days at UBS, is no longer today.”
Osborne recommends joining conferences like this one, reading up on what’s happening in the space, and participating in industry insertions. She also dove a little deeper on the unique challenges for financial services companies, mentioning the regulatory environment and extra complicated data.
“The large, multinational cultural banks, the legacy banks, they’re made up of acquisitions and acquisitions and acquisitions, and that means their data is complex. The inter-spider web, as I call it,” she said. And while data-driven companies like Airbnb and Netflix set themselves up that way from the beginning, she said these banks need to “unweave and unwind” years of complexity.
Advice for rising data professionals
After recounting her earlier experience at the Department of Homeland Security, it’s no surprise Osborne’s biggest piece of advice is to ask questions and “get comfortable with the uncomfortable.”
“On the personal, it allows you to take control and take risks and be vulnerable,” she said. “But from a professional data perspective, it allows you the opportunity to investigate the information and find things that others aren’t seeing, and more importantly, explain them in a way that others haven’t thought [of].”
She believes data storytelling is an important skill set in the field. “I don’t even know if that’s taught, but being able to bridge the gap between the business and technology, and being able to explain data literacy in a way that everyone can understand, is so paramount.”
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