15 results:
ScienceSoft designed and launched a scalable big data analytics system based on Apache Hadoop, Apache Hive, and Apache Spark. The new solution processes 1,000+ types of advertising data in real time and enables comprehensive analytics for different markets.
ScienceSoft delivered a centralized data analytics solution that allowed a multibusiness corporation to get a 360-degree customer view, optimize stock management, and assess the employees’ performance.
The app helps pet owners see where their pets are, get instant notifications if their pet leaves a secure territory, and even speak to them. The solution processes data from 1 million devices, and its architecture is designed to easily accommodate user growth.
ScienceSoft delivered an MVP of collaboration software the Customer used to provide consultations on large-scale construction projects.
ScienceSoft's .NET team developed 20 custom algorithms that auto-convert multi-source telematics big data to a unified proprietary format. The Customer's system has reached the capacity to process data on 100B+ vehicle events from hundreds of diverse devices.
ScienceSoft’s big data expert helped a large jewelry manufacturer and retailer speed up ETL migration to a new Incorta-based EDW. Acting as a consultant and developer, he helped the Customer’s in-house team improve their Python and Apache Spark skills and built 7 ETL pipelines to run enterprise-wide reports on inventory management, marketing campaigns, tendering, and more.
A scalable analytics system with Apache Kafka and Amazon Redshift at its core enables real-time customer analytics, data-driven forecasting, and automated reporting. ScienceSoft’s advice on the efficient analytics toolkit helped reduce system maintenance costs by 80%.
ScienceSoft assisted a US nationwide telecom leader with Hadoop configuration, helping remove a single point of failure and ensure uninterrupted access to critical telecom data for its 400+ clients.
With managed IT support for Apache NiFi that ScienceSoft delivered, the Customer benefited from the overall improvement of their big data ecosystem: big data processing became 10 times faster and the stability increased from 50% up to 99%.
ScienceSoft designed an image analysis application to remotely monitor oil store tanks in real time to help the customer optimize inventory management and detect oil leak.
In compliance with GDPR, your personal information will be collected and stored for ten years on servers located in the United States. After this term is expired, your information will be erased. We will share your information with our development center, which will handle your request. At our headquarters and our development center we apply the same level of care in respect of your information as prescribed with GDPR rules. For more information, please refer to our Privacy Policy.
Healthcare
Insurance
Investment
