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Growing a Data Driven Government - The Commerce Data Academy

Photo of training class.As "America's Data Agency", the U.S. Commerce Department has made open data a central part of its mission.  Over the last year, the department has taken a number of steps to move this mission forward, including the hiring of a Chief Data Officer, Deputy Chief Data Officer and Chief Data Scientist. Last fall, the department also formally launched the Commerce Data Service, an in-house data science and consulting service, to help maximize the value of the vast data resources across the department. 

But to truly develop a data-driven government, we need to make sure that concepts of open-data percolate through all levels of the department. That means making sure Commerce Department employees obtain data skills necessary to keep up with the growing information economy.

To facilitate this training, we recently launched the Commerce Data Academy pilot program. Through a collaboration with General Assembly, the Commerce Library and LINC (Leadership & Innovation Network in Commerce), the Academy offered four initial  courses: "Agile Development", "HTML + CSS", "Storytelling with Data", and "Excel at Excel". The pilot courses provided essential information on how to create effective data training programs for Commerce employees.

As we have done through other Commerce Data Service products, we launched the Academy utilizing the lean start-up methodology – a technique used by several new and innovative technology companies in the private sector to deliver useful products to market quickly.

Lean Startup Methodology (Build-Measure- Learn)

We launched the pilot in three phases:

  1. Analysis & Preparation
    • An inventory of the skills of Academy participants was compiled.
    • Introductory courses were offered for individuals with no prior background in data.
  2. Training via an extensive Data Bootcamp
    • Participants spend two weeks in extensive and intensive classes learning skills in either "Data Analysis & Discovery" or "Data Viz for Policy".
  3. Forward Deployment via Data Service
    • Training is extended through project-based work alongside expert technologists within the Commerce Data Service.

Interest in the Data Academy was beyond even our expectations. Our initial goal was to have 30 people in each class. Instead we nearly doubled that attendance goal in the first session and continued to increase participation in each subsequent session. In total, over 300 people participated in the four sessions.

  Agile Development HTML + CSS Storytelling with Data Excel at Excel Agency Totals
OS 6 5 12 18 41
ITA 5 11 16 24 56
BEA 2 6 9 10 27
CENSUS 7 8 22 9 46
USPTO 0 0 1 0 1
NTIA 5 5 3 5 18
NTIS 0 0 3 2 5
NIST 4 4 12 12 32
ESA 2 3 4 4 13
MBDA 1 0 2 1 4
EDA 2 0 1 3 6
BIS 2 1 2 4 9
NOAA 21 27 41 64 153
Class Totals 57 70 128 156 411
In-Person (RSVP) 33 40 75 86 234
  57.9% 57.1% 58.6% 55.1% 56.9%
Totals (# Actuals) 49 60 120 98 327
In Person 23 28 58 34 143
WebEx 26 32 62 64 184
Ratios (Actual/RSVP) 85.96% 85.71% 93.75% 62.82% 79.56%
In Person 69.70% 70.00% 77.33% 39.53% 61.11%
WebEx 108.33% 106.67% 116.98% 91.43% 103.95%

As attendees registered for the course(s) of their interest before they were allocated a spot, we were able to get some insight on interested employees.

As expected, most participants were familiar with Microsoft Excel and few were familiar with more robust coding and data tools such as HTML, CSS3, Python, D3.js, R/R Studio, Github, JSON, to name a few.

Chart of Excel familiarity. Chart of Python familiarity.

Additionally, around 80% of the respondents are self-taught.

Lean Startup Methodology (Build-Measure- Learn)

Feedback from the pilot sessions were universally positive. A number of participants offered suggestions for improving future sessions, like making the sessions more interactive for those participating over the internet. We are very pleased with the feedback and hope to build on this pilot with even more useful training courses. 

As we grow and improve the Commerce Data Academy, we hope it will serve as a model for other agencies to train their employees and accelerate this drive to build a data-driven government.

By Dr. Tyrone Grandison, Deputy Chief Data Officer and Jeff Chen, Chief Data Scientist


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