5 Lessons from a Data Science Chat
Data science applications, key challenges, appropriate skills and more – key takeaways from a data science Tweet chat.
By Steve Mills (Booz Allen).
In conjunction with Data Science Innovation Day on January 22, 2015, the Booz Allen data science team decided to host its first-ever Twitter chat. In the span of an hour, more than 170 Twitter users from around the world started asking and answering questions or otherwise engaging and sharing their perspective on the industry and the work of the data science community.
Topics included defining data science, making predictions about the future of the field, and addressing some of the challenges faced by data scientists. As both a participant and a “listener” in the chat, I decided to share my 5 key takeaways;
Data science comes in all shapes and sizes. In talking about the impact of data science to-date, the range of answers we received demonstrated the diversity of how and where data science is applied. I shared a few simple, everyday applications, like the creation of a model for the seating arrangement at my wedding reception and a method to align the hardwood floors in a kitchen. Others talked about medical advancements that wouldn’t be possible without data science, such as algorithms for prioritizing vaccine aid and the ability to detect and predict seizures, and environmental solutions such as assessing forest fire damage and the impact on the field of oceanography. @RockleyMark even mentioned using data science to optimize the learning process for children. Absolutely amazing!
We need more data. Compared to six months or six years ago, the amount of data that we have available at our fingertips is staggering. But, we can do even more if more data is made available to us. As @DrZeydy pointed out, it doesn’t just need to be government data. It can be any type of data, as long as it’s open, transparent and accessible. Perhaps the consumer will be the one giving us that data, if @joshdsullivan vision for an opt-in culture for data collection and analytic transparency comes to life.
Keeping up with the (data) Jones’ is hard. One of the most exciting things about working in a field like data science is that there’s always something new happening – a new tool launching, a new code being written or a new layer being added. While the industry pushes forward at an incredible rate, we are forever challenged to stay abreast of the latest developments. Interestingly, every single participant, from across fields and business sectors echoed this same sentiment. The acceleration of technology is happening so unbelievably fast, we need new processes to monitor, innovate, and keep pace.
Data scientists aren’t just computer nerds. Quite the opposite, actually. While many of us have taken more calculus classes than we can count, we’re also tapping into new ways of thinking via artists, musicians and creatives. In fact, we would argue that being data scientist requires a mix of art and science, right brain and left brain. @KirkDBorne refers to it as “the three Cs” -communications, curiosity and creativity.
Behind every Twitter chat is a great data visualization. Being data scientists, of course, the community had to gather the findings from the Twitter chat and develop a data visualization (thanks @marc_smith!).
What it shows is that this relatively small community, while growing, is extremely connected. We may not have identified ourselves as data scientists five, ten, even fifteen years ago, but we were building the human foundation and network for what technology is allowing us to do today.
Thanks to everyone who participated in the Twitter chat, including @wcukierski from @kaggle who broke his 30-year vow of Twitter silence to take part.
To check out the full conversation, search #datascichat on Twitter.
Steve Mills is a senior associate at Booz Allen Hamilton with expertise in Operations Research, Modeling and Simulation, and Data Science. At Booz Allen, Mills leads a team of data scientists in the firm’s Strategic Innovation Group, working across the defense, health, and financial services markets to help clients solve their toughest challenges.
Related:
In conjunction with Data Science Innovation Day on January 22, 2015, the Booz Allen data science team decided to host its first-ever Twitter chat. In the span of an hour, more than 170 Twitter users from around the world started asking and answering questions or otherwise engaging and sharing their perspective on the industry and the work of the data science community.
Topics included defining data science, making predictions about the future of the field, and addressing some of the challenges faced by data scientists. As both a participant and a “listener” in the chat, I decided to share my 5 key takeaways;
Data science comes in all shapes and sizes. In talking about the impact of data science to-date, the range of answers we received demonstrated the diversity of how and where data science is applied. I shared a few simple, everyday applications, like the creation of a model for the seating arrangement at my wedding reception and a method to align the hardwood floors in a kitchen. Others talked about medical advancements that wouldn’t be possible without data science, such as algorithms for prioritizing vaccine aid and the ability to detect and predict seizures, and environmental solutions such as assessing forest fire damage and the impact on the field of oceanography. @RockleyMark even mentioned using data science to optimize the learning process for children. Absolutely amazing!
We need more data. Compared to six months or six years ago, the amount of data that we have available at our fingertips is staggering. But, we can do even more if more data is made available to us. As @DrZeydy pointed out, it doesn’t just need to be government data. It can be any type of data, as long as it’s open, transparent and accessible. Perhaps the consumer will be the one giving us that data, if @joshdsullivan vision for an opt-in culture for data collection and analytic transparency comes to life.
Keeping up with the (data) Jones’ is hard. One of the most exciting things about working in a field like data science is that there’s always something new happening – a new tool launching, a new code being written or a new layer being added. While the industry pushes forward at an incredible rate, we are forever challenged to stay abreast of the latest developments. Interestingly, every single participant, from across fields and business sectors echoed this same sentiment. The acceleration of technology is happening so unbelievably fast, we need new processes to monitor, innovate, and keep pace.
Data scientists aren’t just computer nerds. Quite the opposite, actually. While many of us have taken more calculus classes than we can count, we’re also tapping into new ways of thinking via artists, musicians and creatives. In fact, we would argue that being data scientist requires a mix of art and science, right brain and left brain. @KirkDBorne refers to it as “the three Cs” -communications, curiosity and creativity.
Behind every Twitter chat is a great data visualization. Being data scientists, of course, the community had to gather the findings from the Twitter chat and develop a data visualization (thanks @marc_smith!).
What it shows is that this relatively small community, while growing, is extremely connected. We may not have identified ourselves as data scientists five, ten, even fifteen years ago, but we were building the human foundation and network for what technology is allowing us to do today.
Thanks to everyone who participated in the Twitter chat, including @wcukierski from @kaggle who broke his 30-year vow of Twitter silence to take part.
To check out the full conversation, search #datascichat on Twitter.
Related: