Challenges
Choose your real world challenge to solve.
The 2019 Open Call opened on March 20th.
Pick one of our ‘ready-made’ challenges, where the challenge, data sets and data providers are all pre-defined by us, ready for you to solve!
Bring your own challenge, but solve it using one EDI data set and one external data set
You are free to propose your own challenge, and solve it working with your own data provider and external data sets
Meaningful cross-sectional benchmarking of buildings consumptions
Data Provider: VPS
To develop a benchmark tool that Energy Retailers will use to improve customer engagement and satisfaction.
read moreDemand Management
Data Provider: EMASESA
Establish a demand management system and analysis of the evolution of consumption in its different uses to speed up the detection of deviations and hasten and focus decision making.
read moreSupport System for Water Resources Management
Data Provider: EMASESA
To have a management system gathering all the environmental parameters and the specific conditions of EMASESA.
read moreAuditing Waste for Monitoring Litter Disposal in Tanzania
Data Provider: Nipe Fagio
To increase the speed and scale at which we detect illegal trash dumpsites to be cleaned up and to speed up imagery analysis to find dumpsites.
read moreCC Fraud Detection
Data Provider: Yapı Kredi Teknoloji
Forecasting fraud transactions of credit card users of YKT with machine learning technics instead of traditional rule-based systems.
read moreMake synthetic data for safe sharing with third parties
Data Provider: VRT NWS
To develop a system that creates synthetic data, based on real data, that can be shared safely with third parties.
read morePredictive Model of Churn Rate
Data Provider: EDP
Identify the cancellation of a given service and/or energy supply contract by customers before it happens
read moreAuto-tagging News Articles
Data Provider: VRT NWS
Assigning meaningful and detailed tags to VRT’s news stories, based on the content.
read moreTraffic Analysis
Data Provider: Technische Universität Berlin
Vehicle tracking in city of Berlin.
read moreOptimization of the Assistance Resources Location
Data Provider: RACC
Identify the optimal resources location allocation in the different services zones to minimize the response time of the assistants
read moreCustomer Acquisition Path
Data Provider: Sonae MC
Assessing the profile and categories of consumption at the different stages of the customer lifecycle.
read moreIoT in Retail
Data Provider: Migros Ticaret
Use the gathered IoT data in order to understand the customer behavior
read morePattern Recognition in Campaign Performance Indicators
Data Provider: JOT Internet Media
Identify behavior patterns in digital campaigns through the analysis of the main performance indicators
read moreCustomer Profitability – Segmentation and Prediction
Data Provider: Sonae MC
Clustering consumers into segments based on their profitability
read moreKeyword Categorization
Data Provider: JOT Internet Media
Massive classification of keyword lists
read moreGame Play Data Analytics
Data Provider: IGT
Insight into wager-based PC and mobile gaming sessions for different business users and derivation of player behaviour models.
read moreIndividual Digital Marketing Fan Automated Journeys and Content Personalization at Scale
Data Provider: IAAF
To turn large TV audience into a digital fan base for all year-round engagement and digital marketing activation.
read moreAthletics Statistics Collection and Mining for Prediction, Story Telling and Gamification
Data Provider: IAAF
To provide an exciting digital experience during Athletics sport events, the ability to capture performances and contextualize them is key for Fan engagement/participation.
read moreDetermining Load Profiles for Customers in the Indicated DSO Area based on Smart Meters
Data Provider: ENERGA-OPERATOR
Determining the load profile for energy metering points (MP)
read moreUrban bus fleet operational optimization
Data Provider: EMT Valencia
Improvement of the internal operations to deliver a better service to users
read moreRemote Measurements Control
Data Provider: Elektro Ljubljana
Detect errors on measurements using consumption data
read moreFree Choice Challenge: Bring your own data provider
Bring your own data provider, use external datasets, and propose your own challenge. You will need to apply to EDI hand in hand with your data provider.
read moreHalf and Half challenge: the potential of data combination
Propose your own challenge making use of at least two datasets: one dataset from the EDI Data Catalogue and one external dataset.
read more
