Virginia Dsouza started her career in the hospitality sector before transitioning to real estate. She has been with Knight Frank for the past nine years and has held several positions within the organization, contributing to its growth. Currently, Virginia is the Sr. Vice President - Data Office, a department instrumental in enhancing client service, optimizing internal operations, and conducting market research.
In a conversation with Women Entrepreneurs Review Magazine, Virginia shares her insightful views on evolving expectations from data professionals, building next gen data leaders and need for ethical use of data.
In the current data-driven landscape, how do you see the evolving expectations from data professionals influencing the industry’s future, especially considering the rise of AI and machine learning?
Data professionals play a crucial role in the evolving data industry, enabling them to derive actionable insights and contribute to strategic business decisions. They need a deeper understanding of the business context to translate data into meaningful outcomes. As AI and machine learning continue to evolve, there will be more demand for professionals in these areas. Data professionals must ensure ethical use of data, as learning models can perpetuate bias and lead to unintended consequences.
In the future, data ethics will be more stringent, with GDPR for specific regions becoming more important. Data professionals must be well-versed in data security and privacy, as the consequences could be significant if not considered. Collaboration and interdisciplinary skills are essential, with data professionals working with IT teams, business teams, stakeholders, and domain experts. This collaboration will drive innovation and align with organizational goals.
In conclusion, data professionals must not only clean data but also provide valuable insights, while maintaining ethical considerations through collaborative roles and continuous learning.
As data becomes increasingly pivotal in decision-making across industries, how should leaders redefine their strategies to empower and motivate the younger generation of data scientists to drive innovation while ensuring ethical use of data?
To encourage the younger generation in data science, leaders must create a culture of innovation. This involves encouraging them to experiment, collaborate with other departments, recognize and reward innovation, and continuously hold training programs. Mentorship programs can help pair newer data professionals with seasoned professionals, fostering both learning and growth. Learning labs, innovation hubs, and real-time project progress can also be beneficial.
Ethical use of data is also a focus, with continuous learning and awareness of data ethics being shared. Leaders should embody ethical behavior, allowing the younger generation to learn from their seniors. By fostering an environment where they see their seniors making ethical decisions, they can be encouraged to take risks and innovate in their respective fields. This will ultimately lead to more innovative and successful data professionals in the future.
With rapid advancements in data analytics, what trends do you believe the younger generation of data professionals should be prepared to lead?
The integration of AI and advanced analytics is becoming integral to data analytics, requiring the younger generation of data professionals to adapt and master these tools. As automation of routine data tasks continues, data professionals must free up more time for strategic analysis. Leaders should invest in training programs for the younger generation, such as certifications, boot camps, or workshops, to deepen their technical expertise and gain real-time working experience.
Real-world AI projects and live-streaming analysis will be increasingly prevalent, and leaders should train their younger generation in data storytelling, visualizing, and presentation skills to help them communicate their data insights to non-technical stakeholders. Encouraging regular presentations of findings to different departments will help build confidence and communication skills.
The next trend will be data visualizing and user experience, with data professionals needing to understand user points of view and UX principles to design functional and user-friendly data products. Leaders should support continuous learning, encourage innovation, and empower these professionals to drive the future of data analytics in the industry.
Data-centric cultures are becoming more prevalent, but they often face resistance. How can the younger generation of data professionals be instrumental in driving cultural transformation within organizations, and what strategies should leaders adopt to support this shift?
The younger generation, who is at the peak of knowledge, should act as data evangelists and advocates for data-driven decision-making. They should demonstrate how data can improve outcomes, streamline processes, and uncover opportunities that older generations may not have seen. By using data visualization skills, they can make data more accessible to non-technical stakeholders, demystifying data and showing its practical value. Leading by example, they can inspire others to embrace new data-driven approaches.
Leaders should help bridge the gap between data teams and other departments, promoting communication and collaboration to integrate data into core business operations. Data literacy programs should be initiated to educate employees and stakeholders on data analytics, interpretation, and decision-making value. Supporting cultural transformation by providing a platform for innovation and collaboration across all levels of the organization is crucial.
In conclusion, younger data professionals are more powerful agents for change by leveraging their technical expertise, passion for innovation, and commitment to ethical practices. Leaders should support these efforts through initiatives like trainings and encouraging collaboration across all levels of the organization.
In a field where technology evolves rapidly, how can industry leaders create impactful mentoring programs that not only transfer knowledge but also instill a sense of responsibility and creativity in the younger generation?
Mentoring is a crucial aspect of fostering growth in data professionals. It involves setting clear goals, focusing on not just technical knowledge transfer but also creativity cultivation and ethical responsibility. It is essential to communicate these goals clearly to both mentors and mentees, ensuring they align with organizational values. Mentors should match mentees' skill sets, interests, and career goals, ensuring they guide ethical decision-making and translate creative problem-solving examples.
Continuous learning is also crucial, with mentors providing continuous teaching and support to mentees beyond training programs. Challenges like hackathons can help foster creativity. Communication and collaboration are also essential, as delivering technical expertise can be challenging for younger generations.
Reverse mentoring is also important, encouraging both mentors and mentees to take the lead in certain areas. Incorporating real-world problem-solving is essential for fast-paced, agile data requirements. Providing feedback are also crucial, as well as creating networks between mentors and mentees.
In addition to training programs, organizations should foster inter-organizational committees where data professionals can connect and share new technologies, fostering growth and collaboration.
As the role of data expands, how can the next generation be guided to balance the drive for innovation with ethical considerations, and what frameworks should industry leaders put in place to support this balance?
Incorporating ethics in data education and curriculum is important. Courses should focus on topics such as data privacy, algorithm bias, and the societal impact of technology. Discussions on case studies help data professionals to navigate complex ethical issues. A comprehensive code of ethics should be developed and enforced, outlining standards for data use, transparency, and accountability. Data professionals should consider AI ethics frameworks or the FAIR framework, which promote findable, interoperable, and reusable data principles.
Fostering a culture of ethical innovation is crucial, with leaders prioritizing ethics and setting a standard for the entire organization. Open discussion spaces, workshops, ethics committees, and regular forums can facilitate these conversations. Collaboration between data professionals and experts in fields like ethics, law, and social science is also essential.
Promoting data transparency and communication with stakeholders about data usage and implications is crucial. Mechanisms should be in place to hold individual teams accountable for ethical breaches and emphasize clear consequences. Education and awareness should be promoted, and innovation labs should be created to encourage responsible innovation practices. Balancing innovation with ethical consideration is essential as data roles continue to expand.
Message to Readers
I would also like to emphasize that inter-organizational collaboration is crucial for today's generation to continuously learn and adapt to rapid technological advancements. Seeking role models, joining forums, and participating in communities are essential to stay updated and capitalize on opportunities like automation and data.
