Мы используем файлы cookie для быстрой и удобной работы сайта. Выберите, какие файлы cookie вы разрешаете нам использовать. Подробнее в Политике конфиденциальности.
We use cookies to ensure our website works quickly and easily. Choose which cookies you allow us to use. Learn more in our Privacy Policy.
Обсудить проект
Отправьте запрос, и наши специалисты свяжутся с вами в течение 1 часа
Нажимая кнопку «Отправить», Вы даете однозначное согласие на обработку своих персональных данных в объеме и с целями, определенными Политикой в отношении обработки персональных данных.
Discuss the project
Send a request and our specialists will contact you within 1 hour.
By clicking the "Send" button, you give your unambiguous consent to the processing of your personal data to the extent and for the purposes defined in the Personal Data Processing Policy.
Development of data warehouses and data lakes
Get advice from DUC Technologies experts on how to collect, structure, and analyze corporate data to make informed decisions and grow your business.
Integration of heterogeneous data sources and formation of data marts
Storage of structured, semi-structured and unstructured data
Ad-hoc data querying and hypothesis testing
Formation of a unified data model and a detailed data layer
scientific
approach
data-driven
guarantee
12 months
Our projects
15
5
the speed of management decision-making has increased
from 1-2 days to
times
reduced labor costs
for collecting reports
for collecting reports
We integrated the holding's disparate IT systems to improve reporting accuracy and speed up management decision-making
Development of an analytical platform for data collection and reporting
min
1.5
30%
the accuracy of criteria calculation has been increased
by
the speed of criteria processing and flight display window generation has been increased
How a flexible solution allows for recalculating flight validity for any arbitrary date without changing the code
Development of an analytical system for recording and verifying waste removal trips for compliance with criteria
times
Industrial Digital Ecosystems: Predictive Models and Architecture Development Issues
The concept of a digital ecosystem (DES) based on predictive models and the development of complex, stable, interactive, self-organizing and reliable control systems for various industries in an article by Alexander Suleikin, PhD and Big Data systems architect at DUC Technologies
Получите рекомендации
от экспертов «ДЮК Технологии»
от экспертов «ДЮК Технологии»
Data warehouse and data lake
development framework
development framework
Design
Development
Support
Design
01/03
1. Analysis of all data sources: source systems and entities, description of attributes, key and non-key fields
2. Creating Integration Contracts, defining integration keys and the type of data loading into the storage
3. Creation of data mart prototypes, creation of s2t documents for the marts
4. Designing the data model of the detail layer and the data mart layer
Development
02/03
1. Development of integrations
2. Development of a detailed layer
3. Development of data marts
4. Orchestration of data pipelines from the source to the formation of data marts, including data quality management processes and interaction with BI
Support
03/03
Troubleshooting system crashes and problems
improving the quality of management decisions based on data
increasing process efficiency
increasing business transparency and identifying bottlenecks
increasing sales by optimizing pricing policies and understanding competitors' prices
Business values
Technology stack
Data storage and processing
Integrations and ETL
Data Quality
and Catalog
and Catalog
Visualization
Semantic layer
Сообщение об успешной отправке!