We streamline data management with robust architectures and scalable solutions, offer instant insights through real-time streaming, and leverage predictive analytics and machine learning to boost decision-making and efficiency.
Who we are
Our team excels in designing robust data architectures that ensure seamless integration from various sources, coupled with scalable data engineering solutions for efficient storage, retrieval, and processing, ensuring your data is always ready and reliable.
We specialize in creating real-time data-streaming frameworks to deliver instant insights and developing state-of-the-art data warehousing and flexible data lakehouses that support both batch and real-time processing for comprehensive data analysis.
Through the application of advanced statistical methods, predictive modeling, and cutting-edge machine learning algorithms, we unlock meaningful insights, forecast future trends, and tailor models to meet specific business objectives, integrating them for enhanced decision-making and operational efficiency.
How can we assist you on your analytics path?
Key foundations of our expertise:
Selection of appropriate technology stack and cutting-edge architecture crafting
Creation of a solid data foundation using data-engineering methods
Transformation of your data into a powerful asset with advanced analytical practices
Operationalization of data and machine learning processes to achieve maximum efficiency
Areas where we can support you
Big Data
Our big data services are anchored on a design of robust data and integration platforms, incorporating a sophisticated data fabric to ensure seamless data flow and connectivity. We specialize in proof-of-concept design and execution, cloud engineering, and comprehensive data architecture and engineering, enabling advanced data streaming and real-time analytics for immediate insights and decision-making.
Data Engineering
Our data engineering services offer comprehensive solutions that include data design and modeling, and robust data architecture and engineering to support scalable and efficient data management. We excel in ELT and ETL pipelines design and implementation, employing metadata-driven development to streamline processes and enhanced data quality and accessibility.
Data Science
Our data science services offer cutting-edge solutions, including time-series analysis for forecasting trends, predictive modeling for future insights, and anomaly detection to identify outliers. Additionally, we excel in cluster analysis for grouping complex datasets and leveraging neural networks to analyze and interpret vast amounts of data, enabling smarter business decisions.
Machine Learning Ops
Our services include Machine Learning Ops, enabling seamless integration of machine learning models into your operational workflows, ensuring efficiency and scalability. We provide professional management of the machine learning lifecycle, from development to deployment, optimizing processes for peak performance.
Service Management
In the service management area we focus on integrating DevOps and DataOps methodologies, ensuring seamless collaboration and automation across development, operations, and data management teams. By incorporating these practices, we enhance agility, streamline workflows, and promote a culture of continuous improvement in service delivery.
We use a broad spectrum of technologies
Our portfolio encompasses an extensive array of technologies essential for any project development, ensuring that we meet every demand. Our specialists engage with secure, well-documented tech stacks while continuously exploring the newest and most sophisticated tools and libraries.
We are certificated professionals
The technical professionals we have on board are distinguished by their extensive certifications, covering a wide array of platforms provided by leading service providers. This diverse certification portfolio underscores not only our comprehensive knowledge and expertise in utilizing various technologies but also our ability to design, implement, and manage scalable and resilient solutions.
Case studies
Trading data hub
- Our team engineered a state-of-the-art trading data platform on the AWS cloud, leveraging the data mesh concept and constructed with Snowflake and Kafka. This platform facilitated the consolidation and seamless integration of diverse data sources, including on-premise databases, APIs, and data streams, into a unified AWS environment. Not only did the solution enhance data accessibility and reliability for real-time trading decisions, but it also set a new standard for agility and scalability in data management.
- Used technologies: AWS, S3 Bucket, DynamoDB, Apache Kafka, Snowflake, Aiven, Lambda, Event-driven architecture, REST
Machine learning data hub
- We played a crucial role in the journey of developing an MVP for an innovative data platform designed to handle vast volumes of data and facilitate the creation of complex analytical models. Utilizing Databricks and Kafka, we designed and implemented processing layers and loaders that are both efficient and scalable. Furthermore, we established a Cloud Governance framework tailored for the Azure cloud, laying down comprehensive guidelines for data projects and also the groundwork for a seamless multi-cloud environment.
- Used technologies: Databricks, Kafka, Azure Synapse, Airflow, Azure Data Factory, Event-driven architecture, REST
Big data monitoring & targeting platform
- Our team developed a monitoring and targeting platform leveraging the Cloudera big data technology stack , designed to enhance energy management efficiency. We implemented sophisticated data processing pipelines capable of validating information from diverse sources and constructing a complex, common data model. This model effectively filtered out irrelevant data through anomaly detection and employed advanced analytical techniques to assess the impact of implemented changes on energy consumption. The results demonstrated a significant positive effect on energy efficiency, showcasing the power of integrating big data solutions in practical energy management strategies.
- Used technologies: Hadoop, Hive, Python, Jupyter, Hadoop, Spark, Hive, Kudu, Impala, Airflow
Integrated data platform
- We developed a comprehensive target concept for an on-premise integrated data platform within the distribution segment of an energy company, focusing on the critical infrastructure's needs. The solution encompassed technology, application, and data design, all fortified with a disaster recovery plan in a Cloudera environment. Key components such as Spark, Kafka, Impala, Kudu, and S3 Object Store were utilized to ensure robust performance, scalability, and reliability.
- Used technologies: Kafka, Spark, Livy, Impala, Kudu, HDFS, Zookeeper, Ozone, Ranger, Knox, Atlas, HBase, Hue, Event-driven architecture, REST
