The spotlight on #bigdata, #machinelearning, #artificialintelligence is getting brighter, especially among Washington D.C.’s community of #datascientists. In fact, this community has taken advantage of the spotlight by once again holding its annual event,
DCDataCon.
DCDataCon is a conference that encourages conversations about the present state of data science as well as its future.
The 2017 DCDataCon was held October 3 at George Washington University’s Marvin Center. The forum focused on elevating the importance of data throughout an enterprise and having a data-driven business strategy. It also addressed the region’s significant contributions to data science, such as the region's ability to drive, research, development, and investment as well as its pool of talented and skilled workers.
The sessions at the event discussed
applied research and development, mature data science practice
careers in data science
geospatial innovation
the ethics of advanced technologies and public policy challenges
the activities of a chief data officer
streaming #analytics
investing in #datascience
The next day participants had the opportunity to take a few of crash courses on topics like #datavisualization and big data software.
Here are some of the highlights from the event.
Keynote: Leading in an Artificial Intelligence World
Keynote Speaker Angela Zutavern, Vice President at Booz Allen Hamilton, addressed the significance and impact of artificial intelligence, or AI, revealing how investments in new AI technologies and startups have reached billions of dollars.
The competition regarding the ability to effectively use AI technologies has grown, and the success is largely dependent on a well-developed strategy.
Business leaders are becoming more familiar with AI as a result of the advancements made in the areas of big data and machine learning. AI has and will continue to transform our world with technological advancements designed to improve lives, solve challenges, and resolve inefficiencies. Interest is only growing in this area. AI technologies have created new markets and opportunities and outperformed humans on certain tasks.
When you think of it, the race to become the first AI and machine learning superpower is quite similar to the space race in the 1960s. Policy makers in both China and Japan have announced their AI national development plan. Even government leaders in Canada have indicated plans to invest in developing a strategy. Meanwhile, the leaders within the United States have several components for a strategy, but more needs to be done. According to The Atlantic article sponsored by Booz Allen Hamilton, the U.S. strategy needs to maintain its technological advantage, advance the economy, and protect the social norms, values, and citizens.
Many have feared that AI has the potential to take over the labor force, but Zutavern attempted to calm concerns by indicating how AI technologies can support present jobs. She mentioned how AI can be used to fill labor shortages or launch a second career. In fact, Zutavern pointed out that AI will create new jobs, industries, and expand our knowledge.
She described how truck drivers are using their first-hand experience to help tech teams of self-driving vehicles. For example, an article in Wired magazine explained how the startup Starsky Robotics is using a driving system where trucks on a highway navigate tricky roadways with the help of humans who work remotely.
After the keynote, several sessions were held. Some were held concurrently.
Read more about artificial intelligence:
Building a Mature Data Science Practice
John Eberhardt, a professor at George Mason University and chief technology officer at ATA, LLC explained that data science is a combination of disciplines that include math, business, computer science, and statistics. Data scientists use contextual data in order to address challenges, solve fundamental problems, and make better decisions.
In the early 1980s, people wrote custom databases, but data science has significantly evolved since then. Its evolution has altered the path to a mature data science practice.
Eberhardt discussed the steps needed to reach maturity, such as finding and understanding the context of data, how the data should be stored, and how to run analytics.
One important underlying factor needed to reach maturity is a strong multidisciplinary team of people who can not only understand the data, but also help collect the data, automate this process, and prepare the information for analytics.
Eberhardt emphasized this by discussing the importance of developing a good recruiting strategy, investing in each team members’ education, and letting members participate in small research and development projects so they can improve their skills and learn the technology.
Eberhardt also shared a couple of indicators to help identify when maturity is reached. It’s when more problem solving occurs rather than troubleshooting and more customers show that they are engaged.
Read more about big data:
Chief Data Officers
The job of the Chief Data Officer, or CDO, takes on its own meaning in each industry and within each organization.
The Chief Data Officer panel demonstrated how often these leaders are self-made. The panel was moderated by Dr. Kirk Borne, a principal data scientist at Booz Allen Hamilton and included Brandon Brown, CDO of the Wage & Hour Division at the U.S. Department of Labor and Dr. Pat Dunn, a program manager for Health Tech and Innovation at the American Heart Association. The panelist discussed how they took on the initiative within their organizations to develop systems and processes for data. They disclosed some of the ways that they've transitioned into the job and stayed in their respective roles.
Read more about CDOs and data science careers:
Investing in Data Science
An audience that included leaders from tech startups were able to ask representatives from investment organizations a series of questions. Their inquiries included topics like the best ways to receive funding for their projects, and how to navigate the D.C. tech environment.
The panel was led by Rob Quartel, chairman and CEO at NTLEX. It included Mourad Yesyan, principal at Paladin Capital Group; Adella Toulon, FINTECH Legal Department, Cogent Law; and Jen O’Daniel, Investment DIrector, CIT Gap Funds.
Quartel began with a conversation about investment failures. The panelists then shared their thoughts on how they choose to invest in a startup and offered some helpful advice on the ways startups can stand out in Washington D.C., the value of prototypes, and how to make strong pitch for a product or service.
Read about helpful tips for startups:
Participants at DCDataCon either received a refresher or an introduction to data science. The event had an information-packed agenda relevant to the news and business activities of the day.
The panelists offered clear and insightful information, the discussions were substantive, and the information presented was about the most recent trends. Exhibitors were also present sharing information about new storage capabilities, certification courses, analytics platforms, and more.
Since participants had the opportunity to build upon their knowledge with a crash course the next day, they were able to gain more insight into the topics by applying class lectures to the real world examples discussed during the sessions.