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Forbes
15-05-2025
- Business
- Forbes
What It Takes To Foster A Data-Driven Culture
Written by Christina Egea, MVP, Product Management, Enterprise Data, Capital One It's well known that having plentiful, high-quality data is necessary to becoming a data-driven organization. After all, data powers strategic decisions across any business function, ranging from marketing to risk management, and it serves as the foundation for enhancing customer experiences. But at the heart of the most successful organizations that use and elevate data is one thing – a strong data culture. Gorodenkoff Productions At Capital One, data has been at the heart of our business strategy since our founding days. As a company, we've long adopted the mindset that data-driven decision making is a key business unlock. And, that's why we continually invest in data and foster a culture that encourages people across all levels and areas of the business to make valuable use of data. After reflecting on what's worked at Capital One, a few investments emerge as fundamental to fostering this culture: building a platform-based data ecosystem, bringing a product mindset to data, and elevating data talent. Adopting these elements are paramount for organizations looking to build their own thriving data culture. Ask any business leader if they want to use data to make decisions – the answer is always yes. But the path to getting data, especially readily available, high-quality data, is often the opposite of easy. Tackling this challenge is at the heart of a data platform strategy, which develops the collection of platforms that enable users across the company to find, understand and make use of data to power decisions. Building a central set of platforms requires investment in company-wide standards for data development. These standards should define the data lifecycle, establishing protocols for how data is gathered, stored, and shared. This framework can be enforced across the organization through central platforms that enable automation, supporting the lifecycle from the moment data is created to when and where it gets used. Investing in central platforms democratizes data access, while ensuring data is well-governed across the lifecycle, even as it's locally owned. Democratizing data access is essential to a thriving data culture. Platforms should empower every employee—given appropriate access controls are in place—to use data with minimal friction. This can make leveraging data a natural extension of every employee's daily life. On the shoulders of great platforms, organizations must invest in the underlying quality and definition of data itself. Too often organizations have held a mindset of treating data as a "byproduct" of other business or system processes. We can quickly, especially in today's age, end up in a world where our data lake becomes a data swamp full of mass quantities of data that's hard to use or understand. To ensure you're making valuable data available to employees, you should treat data as you do any other product. Data isn't a secondary asset that happens by accident, it's a vital resource. Bringing a product mindset to data requires building an understanding of your customer, current and potential, and curating data to meet their needs. Those customers aren't always external – most data customers will be your own employees. You need to think about their pain points, what they need, and where data can support them. Managing data as a product requires the same investment as any other product you build. You wouldn't expect a great product to appear without product managers there to problem solve and identify use cases. The same goes for data. Organizations need a clear accountability structure and investment in the teams that are managing and making data available. It can't be a side of desk job or afterthought, but rather a primary focus of investment. This is how you ensure that the data being made available on the established platforms is of the best possible quality. The ultimate data strategy and culture comes to life through people. An organization with a thriving data culture invests in developing the best talent to fuel its ecosystem with the right data – and even more talent to engage with that data. This is why a strong data culture calls for companies to invest in data talent and education. Everyone, from senior leaders to new junior hires, should understand the power of data-driven decision making and the ecosystem that enables it. Part of this will come through developing roles that attract strong data talent across a variety of disciplines. It's not enough to simply add data as a focus to pre-existing roles – you need roles where data is the sole focus. This requires building specific job profiles for these data roles that work back from business needs and recruiting specifically for those roles. Beyond hiring, you also need ongoing training and upskilling to cultivate talent, especially given how rapidly data technologies change. Data roles are constantly evolving, and even more specialties are emerging as AI advances. Staying on top of those trends and adapting to them is key. There are many strategies for doing this. For example, an in-house learning platform can engage employees with classroom-based learning. Meanwhile, internal workshops and forums, alongside external events, can help talent share best practices and build knowledge. At Capital One, our data strategy is our business strategy. This alignment ensures that data initiatives are baked into real-world objectives and that business decisions are consistently backed by data-derived insights. Cultivating a strong data culture like this doesn't happen overnight or by accident. It requires a commitment to building a platform-based data ecosystem that lowers the barrier to data access, promoting a product mindset to develop high-quality, trustworthy data, and investing in the data talent that fuels this ecosystem. These interconnected elements of a strong data culture must be continuously reinforced. It's not easy, but it's well worth the effort. When data is celebrated, curiosity is encouraged, and employees are empowered to do more with data, new possibilities for driving business value and innovation open up across every function.
Bloomberg
02-04-2025
- Business
- Bloomberg
Finding Signal in the Noise: the Enterprise Data Offering at Bloomberg
The ability to analyse markets utilizing clean, structured and unstructured, high-quality data is imperative for firms. Hear from our leading subject matter experts on the latest themes and trends and how our solutions have been built, what differentiates us from the market and why that matters. They'll be talking through our newest releases, spanning every asset class including Equities, Macro, Credit, Fixed Income, Commodities, and what this next year holds. We'll review our best-in-class point in time offering, machine-readable news and data integration tools, to allow any research workflow time to focus on what matters most. Speakers Nora Assad-Russo Data Sales Specialist - Research and Quantitative Finance Bloomberg Nora Assad-Russo works as a research and data science specialist within Bloomberg's Enterprise Data division. She joined the firm two years ago and has 10+ years in the industry, previously working on the Equity trading floor in Morgan Stanley in their Non-Market Risk and Algorithmic Trading Risk teams. She has an MSc in Data Science, another in International Relations and a deeply curious mind. Jerome Barkate, CFA Quant and Data Scientist Bloomberg Jerome Barkate, CFA is a Quant and Data Scientist at Bloomberg. His team showcases the possibilities of Bloomberg Enterprise Data to Clients. Before joining Bloomberg in 2023, Jerome spent 18 years in Asset Management (Amundi, Nomura, Unigestion) in senior roles as lead portfolio manager and quant, trading multiple asset classes. He holds Masters of Science in Statistics and Finance from ISAE Supaero and Paul Sabatier University. He is a CFA Charterholder since 2011 and holds multiple AI/ML certificates.
