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The State of Spatial Data
Science in Enterprise 2020
Follow @CARTO on Twitter
CARTO — Unlock the power of spatial analysis
Introductions
Florence Broderick
VP Marketing
Miguel Álvarez
Data Scientist
CARTO — Unlock the power of spatial analysis
https://go.carto.com/ebooks/state-spatial-data-science-2020
How does your
organization’s
Data Science and
GIS setup compare
to other enterprise
organizations?
CARTO — Unlock the power of spatial analysis
APAC 9.8%
Industry
Participants
Seniority Region
43% individual contributors
45% Mid management
12% Senior management
North
America
47%
EMEA
38.6%
Latin America 4.5%
CARTO — Unlock the power of spatial analysis
What is Spatial Data Science?
"Spatial data science can be viewed as a subset of generic "data science" that focuses on the special
characteristics of spatial data, i.e., the importance of "where." Data science is often referred to as the
science of extracting meaningful information from data. In this context, it is useful to stress the difference
between standard (i.e., non-spatial) data science applied to spatial data on the one hand and spatial data
science on the other. The former treats spatial information, such as the latitude and longitude of data
points as simply an additional variable, but otherwise does not adjust analytical methods or software
tools. In contrast, "true" spatial data science treats location, distance, and spatial interaction as core
aspects of the data and employs specialized methods and software to store, retrieve, explore, analyze,
visualize and learn from such data. In this sense, spatial data science relates to data science as spatial
statistics to statistics, spatial databases to databases, and geocomputation to computation."
Luc Anselin PhD, Center for Spatial Data Science Senior Fellow, University of
Chicago
CARTO — Unlock the power of spatial analysis
Why?
Can we model the patterns and
movements of tourists to improve
operational efficiencies?
You need to use an LI Platform
Where?
Where are tourists staying and
going to?
You’re likely using a BI
platform
CARTO — Unlock the power of spatial analysis
Who is doing spatial analysis?
CARTO — Unlock the power of spatial analysis
Results
CARTO — Unlock the power of spatial analysis
Data Science and GIS teams at organizations
CARTO — Unlock the power of spatial analysis
Data Science and GIS teams at organizations
CARTO — Unlock the power of spatial analysis
How many Data
Scientists
actually know
about spatial?
CARTO — Unlock the power of spatial analysis
Which
technologies
and
languages
are preferred
in the
industry?
CARTO — Unlock the power of spatial analysis
Discovering data useful
for their analysis
Evaluating and
purchasing data
ETLing the data
into common
structures
Analyzing, doing
feature extraction and
modeling
30% 30% 20% 20%
Where do SDS spend time?
CARTO — Unlock the power of spatial analysis
A Data Scientist needed demographics and zip code data for Portugal to perform a
particular market analysis:
An example:
CARTO — Unlock the power of spatial analysis
Geocoding/
Isochrones
Spatial lags
Discovery &
data access
Sharing Spatial
Modelling
Changing
geographic
support
Projecting
Model
Spatial Data
Enrichment
But there is a lot more to do...
CARTO — Unlock the power of spatial analysis
How difficult
is it to hire
Data Scientists
with expertise
in spatial
analysis?
CARTO — Unlock the power of spatial analysis
What are the
most valued
skills to hire
relevant talent
in Spatial Data
Science?
1. Strong background in statistics
2. Extensive experience in coding skills relating
to Data Science (Spark, SQL, Python, R,
Tensorflow, Pytorch)
3. Experience developing production-quality
data products using the results of
quantitative research
4. Extensive experience in data visualization (in
Python and R or other applications)
5. Effective application of Data Science
workflows to business problems, and the
ability to storytell around results
6. Familiarity with data pipelines and ETL
practices (Airflow, scheduled notebooks,
Google DataFlow, etc.)
7. Familiarity with neural networks and deep
learning (e.g. Tensorflow, PyTorch)
8. Experience working with distributed
computing systems like Spark or Google
BigQuery
9. Experience working with GIS software such
as CARTO, QGIS, or ArcGIS
CARTO — Unlock the power of spatial analysis
https://go.carto.com/ebooks/spatial-data-science
Ready to become
a Spatial Expert?
CARTO — Unlock the power of spatial analysis
47% of participants do not find
it challenging to identify the
right software & data to
support Spatial Data Science
projects
How difficult
is it to find the
right software
and data?
CARTO — Unlock the power of spatial analysis
How will
investment in
Spatial Data
Science
initiatives
expand?
68% of organizations
are likely to increase
their investment in
Spatial Data Science in
the next 2 years
CARTO — Unlock the power of spatial analysis
Conclusions Shifts and trends transforming the
field:
1. The global proliferation of Spatial Data
Science programs, will provide training at
the undergrad, post-grad, and doctoral
levels.
2. The de-siloing of GIS will allow traditional
GIS professionals to up-skill on Python, R,
and other skills that will enable them to
more effectively perform Spatial Data
Science functions.
3. The increasing accessibility of tools and
resources will allow traditional Data
Scientists to integrate Spatial into their
workflows.
Thanks for listening!
Any questions?
Request a demo at CARTO.COM
Miguel Álvarez
Data Scientist // malvarez@carto.com
Florence Broderick
VP Marketing // flo@carto.com

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The State of Spatial Data Science in Enterprise 2020

  • 1. The State of Spatial Data Science in Enterprise 2020 Follow @CARTO on Twitter
  • 2. CARTO — Unlock the power of spatial analysis Introductions Florence Broderick VP Marketing Miguel Álvarez Data Scientist
  • 3. CARTO — Unlock the power of spatial analysis https://go.carto.com/ebooks/state-spatial-data-science-2020 How does your organization’s Data Science and GIS setup compare to other enterprise organizations?
  • 4. CARTO — Unlock the power of spatial analysis APAC 9.8% Industry Participants Seniority Region 43% individual contributors 45% Mid management 12% Senior management North America 47% EMEA 38.6% Latin America 4.5%
  • 5. CARTO — Unlock the power of spatial analysis What is Spatial Data Science? "Spatial data science can be viewed as a subset of generic "data science" that focuses on the special characteristics of spatial data, i.e., the importance of "where." Data science is often referred to as the science of extracting meaningful information from data. In this context, it is useful to stress the difference between standard (i.e., non-spatial) data science applied to spatial data on the one hand and spatial data science on the other. The former treats spatial information, such as the latitude and longitude of data points as simply an additional variable, but otherwise does not adjust analytical methods or software tools. In contrast, "true" spatial data science treats location, distance, and spatial interaction as core aspects of the data and employs specialized methods and software to store, retrieve, explore, analyze, visualize and learn from such data. In this sense, spatial data science relates to data science as spatial statistics to statistics, spatial databases to databases, and geocomputation to computation." Luc Anselin PhD, Center for Spatial Data Science Senior Fellow, University of Chicago
  • 6. CARTO — Unlock the power of spatial analysis Why? Can we model the patterns and movements of tourists to improve operational efficiencies? You need to use an LI Platform Where? Where are tourists staying and going to? You’re likely using a BI platform
  • 7. CARTO — Unlock the power of spatial analysis Who is doing spatial analysis?
  • 8. CARTO — Unlock the power of spatial analysis Results
  • 9. CARTO — Unlock the power of spatial analysis Data Science and GIS teams at organizations
  • 10. CARTO — Unlock the power of spatial analysis Data Science and GIS teams at organizations
  • 11. CARTO — Unlock the power of spatial analysis How many Data Scientists actually know about spatial?
  • 12. CARTO — Unlock the power of spatial analysis Which technologies and languages are preferred in the industry?
  • 13. CARTO — Unlock the power of spatial analysis Discovering data useful for their analysis Evaluating and purchasing data ETLing the data into common structures Analyzing, doing feature extraction and modeling 30% 30% 20% 20% Where do SDS spend time?
  • 14. CARTO — Unlock the power of spatial analysis A Data Scientist needed demographics and zip code data for Portugal to perform a particular market analysis: An example:
  • 15. CARTO — Unlock the power of spatial analysis Geocoding/ Isochrones Spatial lags Discovery & data access Sharing Spatial Modelling Changing geographic support Projecting Model Spatial Data Enrichment But there is a lot more to do...
  • 16. CARTO — Unlock the power of spatial analysis How difficult is it to hire Data Scientists with expertise in spatial analysis?
  • 17. CARTO — Unlock the power of spatial analysis What are the most valued skills to hire relevant talent in Spatial Data Science? 1. Strong background in statistics 2. Extensive experience in coding skills relating to Data Science (Spark, SQL, Python, R, Tensorflow, Pytorch) 3. Experience developing production-quality data products using the results of quantitative research 4. Extensive experience in data visualization (in Python and R or other applications) 5. Effective application of Data Science workflows to business problems, and the ability to storytell around results 6. Familiarity with data pipelines and ETL practices (Airflow, scheduled notebooks, Google DataFlow, etc.) 7. Familiarity with neural networks and deep learning (e.g. Tensorflow, PyTorch) 8. Experience working with distributed computing systems like Spark or Google BigQuery 9. Experience working with GIS software such as CARTO, QGIS, or ArcGIS
  • 18. CARTO — Unlock the power of spatial analysis https://go.carto.com/ebooks/spatial-data-science Ready to become a Spatial Expert?
  • 19. CARTO — Unlock the power of spatial analysis 47% of participants do not find it challenging to identify the right software & data to support Spatial Data Science projects How difficult is it to find the right software and data?
  • 20. CARTO — Unlock the power of spatial analysis How will investment in Spatial Data Science initiatives expand? 68% of organizations are likely to increase their investment in Spatial Data Science in the next 2 years
  • 21. CARTO — Unlock the power of spatial analysis Conclusions Shifts and trends transforming the field: 1. The global proliferation of Spatial Data Science programs, will provide training at the undergrad, post-grad, and doctoral levels. 2. The de-siloing of GIS will allow traditional GIS professionals to up-skill on Python, R, and other skills that will enable them to more effectively perform Spatial Data Science functions. 3. The increasing accessibility of tools and resources will allow traditional Data Scientists to integrate Spatial into their workflows.
  • 22.
  • 23. Thanks for listening! Any questions? Request a demo at CARTO.COM Miguel Álvarez Data Scientist // malvarez@carto.com Florence Broderick VP Marketing // flo@carto.com