Initial Use Cases
Upon using the initial license for several weeks, the team at PNH compiled feedback from other colleagues and departments and, with positive insights from various internal groups, ended up signing on as a customer. Outlined below are three of the initial use cases where Dataiku has helped PNH scale their data science efforts.
1. Meadow Birds Analysis
One PNH project deals with biodiversity and nature, specifically protecting the meadow bird population within the province. PNH spends significant resources annually collecting data on counts of the number and species identification of meadow birds and interpreting this raw data to determine trends in numbers, level of endangerment of specific species, and so on. Typically, PNH employs external services in order to compile and analyze this data.
Waiting for results used to take upwards of two years, whereas now, with Dataiku, the team can extract insights and calculate trends based on historical data in a matter of weeks and can understand the data on their own. Instead of needing to outsource, PNH has been able to leverage accessible data to make decisions on policy and save time to be used for other priority projects.
2. Traffic Light Optimization and Performance Measurement
PNH typically optimizes the traffic lights in the province once every three years. In order to measure performance prior to using Dataiku, the team would gather data from a typical day before the traffic light optimization as well as data from a typical day after the optimization to identify how many cars stop and for how long, thereby determining the success of the optimization. However, the team observed that this method only compares roughly one data point with another, but every day in the province is unique and there is lots of variation within a day, so having multiple data points to measure would generate stronger insights.
With Dataiku, the team gathered data from a week before the optimization and a week after, differentiated it by every 15 minutes, and incorporated the fact that different traffic lights have different settings to account for morning rush hour, evening rush hour, and the rest of the day. All of this data left the team with a significantly higher group of data points and more data to handle and evaluate the optimization.
Further, they can drill down to see where improvements have specifically been made (i.e. in the morning or evening rush hour) and observe at what times the optimization has the biggest impact. The team at PNH attributes a lot of this success to Dataiku’s ease of use and is excited to continue involving others for future data analysis projects.
3. Field Productivity and Compliance
A third use case also deals with biodiversity, specifically related to agricultural farms. The team at PNH performed an analysis of GIS data (for satellite imagery) in combination with their data science approach and techniques. PNH provides subsidies to agricultural farmers for mowing their fields later in the season in order to protect birds laying eggs in the fields earlier in the season.
The team uses the satellite data to check if the farmers comply with the agreement to mow their fields later in the season as well as identify the most productive areas or types of fields, which they then use to inform future decisions regarding water level, for example. Once they identify the fields that do not comply with the policies, representatives from PNH can visit these farmers to start a dialogue with them and encourage them to course correct their habits to preserve the biodiversity of the province.