What's new in data science? Flip through this week's Top 5 to read about key insights and innovations for business leaders: how to build a data science dream team, how Walmart uses NVIDIA GPUs for better demand forecasting, insights from Capital One on reaping success with enterprise machine learning, new data science platforms announced at the GPU Technology Conference, and what business leaders should know about data science.

1. INSIGHTS AND INNOVATIONS
FOR BUSINESS LEADERS
MARCH 29, 2019
DATA SCIENCE
TOP 5

2. 2
THE RACE TO
STAY AHEAD WITH
DATA SCIENCE IS ON

3. 3
BUSINESS LEADERS HAVE TURNED TO
DATA SCIENCE TO DELIVER THE BEST
SOLUTIONS AND BEAT THE
COMPETITION.
SEE THIS WEEK’S TOP 5 HEADLINES
ON WHAT’S NEW IN DATA SCIENCE.

4. 4
DATA SCIENCE
TOP 5
Gartner identifies AI as top megatrend
Deep learning is changing the world of sports
Opinion: “I was worried about AI until it saved
my life”
PayPal uses AI to protect payments and performance
AI predicts melting of sea ice to save communities
#1
#2
#3
#4
#5
#1 HOW TO BUILD A DATA SCIENCE DREAM TEAM
#2 HOW WALMART USES GPU-ACCELERATED DATA SCIENCE FOR
BETTER DEMAND FORECASTING
#3 INSIGHTS FROM CAPITAL ONE ON REAPING SUCCESS WITH
ENTERPRISE MACHINE LEARNING
#4 NEW DATA SCIENCE PLATFORMS ANNOUNCED AT THE GPU
TECHNOLOGY CONFERENCE
#5 EVERYTHING YOU NEED TO KNOW ABOUT DATA SCIENCE AND
HOW BUSINESSES ARE USING IT

5. 5
HOW TO BUILD A DATA SCIENCE DREAM TEAM
“The go-to method in data collection for many
has been to ‘collect it all’ and sort it out later,
though this data strategy brings up several issues
for managing, qualifying, and processing data
later on.
“The solution? Strong collaboration between data
scientists and subject-matter experts (SMEs) on
the data is essential for building an infrastructure
of capturing data for rapid, accurate decisions.”
SOURCE: https://www.forbes.com/sites/nvidia/2019/02/26/how-to-build-a-data-science-dream-team/#b61b1fa5b2d5
#1
LEARN MORE

6. 6
HOW WALMART USES NVIDIA GPUS FOR BETTER
DEMAND FORECASTING
“Walmart’s JDA system is currently responsible
for crunching historical sales data on a weekly
basis to come up with demand forecasts for
roughly 500 million item-by-store combinations in
the US, said Walmart Labs‘ Distinguished Data
Scientist and Director of Data Science John
Bowman.
“Crunching all that data is computationally
challenging, but the reward – more product on
the shelves, fewer out-of-stock situations, and
increased sales – are worth the cost.”
SOURCE: https://www.datanami.com/2019/03/22/how-walmart-uses-gpus-for-better-demand-forecasting/
#2
LEARN MORE

7. 7
INSIGHTS FROM CAPITAL ONE ON REAPING
SUCCESS FROM MACHINE LEARNING
Organizations in every industry are rapidly
embracing machine learning to enable and
accelerate their business transformation fueled
by data. With the advent of GPU-accelerated
data science, businesses are realizing faster time-
to-insight, making organizations more productive
and cost-efficient, gaining competitive
advantage.
Capital One senior director Zach Hanif shares his
insights on what every business should know as
they seek to tap into the power of AI and
machine learning.
SOURCE: https://www.forbes.com/sites/nvidia/2019/02/27/reaping-success-with-enterprise-machine-learninginsights-from-capital-one/#7c7a000e265d
#3
LEARN MORE

8. 8
NEW DATA SCIENCE PLATFORMS ANNOUNCED AT
THE GPU TECHNOLOGY CONFERENCE
“The number of data scientists has exploded and
is instrumental in helping almost every vertical
digital transform. One of the challenges for
companies is giving data scientists the right
technology to do their jobs, which require
massive computing power.”
At the GPU Technology Conference (GTC), NVIDIA
announced several data science platforms, from
high-performance workstations to optimized
enterprise servers, to support data scientists in
their work and help businesses improve
productivity and performance.
SOURCE: https://www.eweek.com/pc-hardware/new-data-science-platforms-highlight-nvidia-s-gpu-conference
#4
LEARN MORE

9. 9
WHAT BUSINESS LEADERS NEED TO KNOW ABOUT
DATA SCIENCE
Enterprises and their leaders who are looking to
get started should first get familiar with the
fundamentals of deep learning and the
corresponding terminology, as well as understand
the current challenges to AI adoption and how to
address them. This Forbes article provides a
definitive overview of the topic, along with links
to several resources that you may find useful.
SOURCE: https://www.forbes.com/sites/nvidia/2019/02/28/from-deep-learning-to-data-science-everything-you-need-to-know/#340676693bf9
#5
LEARN MORE

10. STAY CURRENT ON THE
LATEST INNOVATIONS IN DATA
SCIENCE
LEARN MORE