DareData Engineering
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About DareData Engineering
DareData Engineering is a top-tier boutique specializing in providing exceptional data science and engineering services. Our mission is to help businesses of all types - from startups to blue-chips - transition to a data-driven culture and provide support to tackle their most complex data challenges. Our custom data and AI consultancy solutions, training, and data engineering are designed to help our clients achieve their business goals.
As a global service provider, we successfully execute projects across a wide range of industries and with clients from over 8 countries, including the USA, UK, Brazil, and the EU.
At DareData Engineering, we are focused on providing innovative solutions that enable our clients to leverage data for sound decision-making or performance augmentation.
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Locations
Lisbon
AV FONTES PEREIRA MELO , 31 5 C LISBOAExpertise
- Cloud Solutions: 5%
- AI Company: 70%
- BI Company: 25%
BI & Big Data Solutions
- EMC: 25%
- Microsoft BI & Big Data: 25%
- Other: 50%
Artificial Intelligence
- Machine Learning: 25%
- Chatbots: 30%
- Image Processing: 20%
- Speech & Text Processing: 25%
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Portfolio
Key Clients
EDP OutSystems Roche CocaCola NOS Communications Accel Group Bain & Company Bial Heineken Central de Cervejas Altos Labs TekeverDownloads
Case Studies
Description
Our sales forecasting machine learning algorithms are currently being deployed in two markets of one of the major beverage companies in the world. We’ve done production-level forecasts, deployed using MLOps best practices, both for On-Trade (Restaurants, Cafes, etc.) and Off-Trade (Retail). We’ve achieved significant improvement in current MAPE (Mean Average Percentage Error), particularly in the On-Trade business.
Solution
We’ve tested both SARIMAX and Prophet models. The models are retrained to avoid overfitting and to capture significant changes in consumers demands. We’ve used sales, weather, soccer games, holidays and other factors to capture consumers demand.
Results
We have deployed models for more than 250 SKUs for both businesses. It’s impossible to tackle and manage these models without proper MLOps techniques and working CI/CD pipelines.
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Further case studies of the provider
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