DAMS teams, usually between three and six members strong, work with outside agencies to help them understand their data through analysis and visualizations. We’re a fast-learning, eager group ready to take on any data challenge. If you’d like to learn more about our data consulting services, please contact us here.
To learn more about some of our consulting projects, read below. The projects listed below all use publicly-available data.
We created a live interactive dashboard for people to use to visualize buses as they travel through the bus system in Alameda and Contra Costa counties. Buses are represented as dots, with lines representing common routes. The locations of buses are updated by AC Transit approximately every 30 seconds.
For Monterey county, we designed an interactive dashboard to help them visualize the frequency and severity of different types of car accidents on their roads.
This interactive dashboard, created for Contra Costa County, helps us understand traffic behavior along the I-680 corridor in the county, showing data like speed, flow, VHT, and VMT as well as collisions data.
This interactive dashboard was created for the City of Oakland to help them visualize demographic data about different neighborhoods of the city. It shows racial, income, and average rent data as well as other indices like Healthy Places and Economic Vulnerability.
There are 7,383 legislators in America – and they control crucial climate policy decision. They set clean energy and car standards, and decide natural disaster funding. But right now, there’s no way to understand how state legislators vote on climate. That’s why Climate Cabinet is creating the Climate Cabinet Score: a centralized place where ever legislator, nationwide, receives a “Climate Score” for their votes. We’re working with Climate Cabinet to understand publicly available data on legislator votes to give each legislator a climate score value.
Universities take metrics like US News World Report rankings seriously. There are lots of ways colleges are scored–faculty/student ratios, tuition, and graduation rate, to name a few. Unfortunately, because many of these rankings favor prestige, selectivity and wealth, they create incentives for institutions to enroll wealthier students over low-income students, furthering economic inequality on college campuses. Minority and low-income students don’t currently have a way to easily identify schools that will serve them with an accessible and equitable education. There are a variety of equity evaluations and metrics out there, but they are often hard to connect or interpret. We are working with the Common App to develop an “Equity Badge” system to score colleges based on how well they serve underprivileged students.
There are lots of great schools out there, and there are lots of students are qualified to attend. But the matching process between students and schools isn’t perfect because students often underestimate their ability to get into top-tier schools. This is an especially prevalent problem in underprivileged communities that don’t have access to quality advising. Being able to show students which schools they will be a good candidate for is something that could be incredibly powerful to reduce undermatching. However, there is a gap in admissions data that needs to be closed before this can be possible. A fast way to gather this is through student reported data at the end of the application cycle while a longer term solution includes some form of institutional reporting / data sharing. We are working with the Common App to collect data on college admissions outcomes and interpret that data using Deep Learning to recommend colleges to students.
The Common App is working on products to help transfer students. We’re working with them to parse & understand their unwieldly datasets through data cleaning and dashboarding.
The Common App is a great system for most colleges to efficiently collect student data. However, for many community colleges, the form doesn’t match their needs. We’re helping to create a community-college-friendly version of the Common App by making it responsive to student data while being easy to navigate.