Why asking questions is key to becoming a data leader


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Sitting in a swivel chair during the virtual Collibra Data Citizens 2021 event, Jacklyn Osborne said she felt transported back to her first job out of college at the Department of Homeland Security, where she swiveled to ask someone if they needed help. That connection ignited her career and taught her the value of learning opportunities, something vital in todays ever-evolving data landscape.

Collibra chief data citizen Stijn Stan Christiaens,who was hosting the fireside chat, understood her point immediately: The one thing Ive 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.

Its 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 shared 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 she noted the pull between transformation and compliance aspects of defense. Osborne agreed the shift from defensive to offensive data practices turning data from a liability into an asset is absolutely happening. And she said 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 cant be answered, no matter what pretty veneer, no matter what visualization, no matter what models, no matter what AI, its still our favorite old saying of garbage in, garbage out,’ she said.

Those three core considerations 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 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, theres the number of data dimensions, data quality rules, data quality rules passing threshold, and 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 thats 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, its something that in practice, Ive learned those strategies are important, but in the end you still need to execute on all of it.

Emerging challenges

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, perhaps more so in the data space than in others.

It is so important, specifically in the data space, to stay in the know, she said to Christiaens. Because what was [there] 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 whats happening in the space, and participating in industry insertions. She also dove a little deeper into the unique challenges facing financial services companies, mentioning the regulatory environment and extra complicated data.

The large, multinational cultural banks, the legacy banks, theyre 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 banks need to unweave and unwind years of complexity.

Advice for rising data professionals

Osborne said her 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 arent seeing, and more importantly, explain them in a way that others havent thought [of].

She believes data storytelling is an important skill set in the field. I dont even know if thats 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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