Sadie St. Lawrence, Data Scientist and Founder & CEO of Women in Data, joined us last month at our Digital Enterprise and Transformational CISO Assembly in Las Vegas to lead key sessions in our program. We had the opportunity to hear from Sadie post-event about her organization that she created from the ground up, new technologies she’ll be utilizing to improve strategic initiatives, and her hopes for the future in the digital revolution.
You are an instructor of SQL For Data Science with UC Davis and Coursera, becoming the first female instructor for Data Science on the Coursera platform. How have these opportunities shaped and influenced your career in data?
I took my first data science course with Coursera in 2014, this class was pivotal for me because it gave me an easy way to test my interest and ability in Data Science at a low cost with easy access. After taking Massive Open Online classes (MOOCs), I went on to get my masters in analytics and began working in the field. When UC Davis approached me to teach Data Science for SQl on the Coursera platform, I knew I had to say yes. First, because I wanted to give back to a platform and community that gave me my start, but second, because in all of my MOOC courses and master’s courses I only had 1 female data science teacher. I understand how important it is for females to have role models in technology, so when this opportunity came about I knew I had to say yes. I’m so thankful for UC Davis for giving me this opportunity and from this, the course is now on it’s way to becoming a series with three additional courses, all of which will be taught by women. I think this example speaks heavily to the fact that we need female leaders in this area, because when we have leaders in this area we create opportunities for others to break the mold.
It is new year, so that means it is a new chapter for women involved in the data revolution. Tell us about your role in Women in Data and how your organization is creating the platform for diversity in the AI and data science fields?
I started Women in Data in 2016 and took a crawl, walk, run approach. In the first few years of the organization we used this time to understand the community’s needs, problems, and goals. From taking this approach, we have had over three years of experience understanding the obstacles facing women in data careers and have designed programs to meet these needs. In short, it comes down to awareness, education, and opportunity, and from this research we have and are continuing to develop the programs to fulfill these needs. We know there is the demand for these programs because in over a year we have gone from 800 members to 4,000 and growing! Our goal is to take people from an understanding of the careers available in data to getting the supplementary education needed to fulfill these roles, and final getting a job in one of these careers. Getting a more diverse workforce in these roles is what is needed to not only change the diversity numbers in technology, but also help people transition their skills for the digital and AI revolution.
Is there a specific action plan individuals should follow when looking to get into data science? What advice would you offer them?
First and foremost, understand data science is not just a career but rather a tool and a new way of doing business. I truly believe the data science profession will continue to evolve and change in the coming years. Therefore, for new and aspiring data scientists, I think it’s important to understand that data science is just a new way for businesses to operate (on data) and can be applied to any industry. Therefore, if you are interested in gaining this tool, it’s important to do a self-assessment to understand what you know and what areas you need to gain knowledge in, then decide on an industry or area of business you would like to apply it to. By filling in your knowledge gaps and deciding on a particular area of focus, you can start to apply yourself right away, and the best way to get a job in this area is to get work experience to prove your chops.
AI and machine learning are just some technologies that are impacting how data is used within an organization. Where do you see companies like VSP Global taking advantage of these technologies to improve business functions and strategic initiatives?
As I mentioned, data science is really just a tool that can be applied to business, so it has the potential to affect all areas of the business. In terms of strategy though, in order to be a data driven organization the normal ways of operating have to be flipped. In typical companies, an executive will set the strategy, convey that strategy to a business area, and then that business area with work with IT and analysts to carry it out. Because of the advances in AI and machine learning, technology and analytics can no long take a back-seat approach. The insights from the data drive the strategy, and business groups simply act on the models created by the data science team. This changes the whole mold of operating and the business begins to be managed from a network/model approach through the data. This is the only way data can be used to improve an organization’s strategic initiatives.
From what you have seen and experienced, how has real-time data improved decision making, especially when looking to develop cross functional technology platform solutions?
A rule I like to live by is you only need real-time data if you can take real time action on that data, and for the vast majority of use cases this isn’t necessary. However, in the case that it is, real time data is only valuable in the decision making process if that data has been distilled, interpreted, and presented in a manner that is easy to digest, by the application or person taking an action off of it. In this case, the impact is great because the data becomes a sixth sense. Never before have we had access to the wealth of information at our fingertips but distill in an easy to use real time format.
Although it is hard to predict, where do you see the future of data heading?
We live in a world with information overload but a lack for wisdom. As the number of devices connect to the internet continues to grow, the overall growth of data isn’t stopping anytime soon. What will be most necessary for the future of data is first, people who can interpret this data from information to wisdom, second, computing power to process all of the data (quantum computing), and third, security, governance, and ethics to insure it is used in a harmless and safe manner. If anyone looking to have a career in data, focusing on one of these three areas will be essential.
We were quite thrilled you were able to attend our Digital Enterprise and Transformational CISO Assembly last month. What do you think are the benefits of a small, intimate, C-Suite program like ours at The Millennium Alliance?
If you are looking for a place to have dialog with peers and industry leaders, then The Millennium Alliance is your place. The assembly was an intimate event with access to some of the best thought and industry leaders. Executives will gain valuable insight and dialog, and come back to their business with a fresh perspective.
About The Digital Enterprise and Transformational CISO East Coast Assembly
Thanks to the success of our Digital Enterprise Transformation Assembly series, The Millennium Alliance in partnership with our Advisory Board, is adding more events to the list! Digital Enterprise Transformation East Coast will be heading to Charlotte, NC this March.
This exclusive Assembly will bring industry experts and the best solution providers to our Senior Members based on the East Coast.
Are you a CIO or CTO interested in attending this event? Enquire here today to find out if you qualify for Millennium Membership >>