We provide support for your data projects, as the exponential growth of data collection has led to the emergence of new ways to store, process, and derive insights in the past decade.
The prohibitive cost of boosting individual supercomputers' performance has led to a paradigm shift towards horizontal scaling, where multiple computers work in parallel, and leveraging cloud-based services for computing power, storage, and monitoring. In the context of data, this means using a cloud-based data warehouse in combination with a data lake, advanced analytics, and AI and ML components to deliver Data as a Service.
With the pay-as-you-go pricing option, you can optimise costs and dynamically scale your application capacity using on-demand resources, allowing you to scale up as your client base grows.
We can create and integrate unique solutions, tailored to your specific use case, environment, and company culture.
We are always up to date with the latest technologies, platforms, and methodologies, ensuring that you are always ahead in your data domain, collecting, curating, and aggregating data from various sources.
We assess and plan the migration of your systems and applications to the cloud, defining and implementing the architecture needed to securely collect and transmit data from your on-premise data centre to the cloud.
A modern cloud data warehouse (DWH) serves as a central building block for your data-driven company, forming the foundation for all aspects related to reporting and analytics. By leveraging a cloud data warehouse, you can unleash the power of the cloud across your entire data and analytics value chain. Take full advantage of the cloud by starting with a cloud data warehouse.
A cloud data warehouse enables modern Business Intelligence solutions by providing BI, AI, and ML tools with valuable, up-to-date data; it meets the ever-evolving demands for data storage, while offering flexibility, automation, and cost-effectiveness when compared to the static data silos often found in on-premise data warehouses. Cloud data warehouses seamlessly integrate into your cloud environment and are often integrated into a holistic analytics platform, which combines data lake, advanced analytics, AI, and ML components with a cloud data warehouse, thus offering a unified view of data and advanced analytics capabilities.
Pay only for the resources you actually use, not for those you reserved in advance.
A cloud data warehouse allows you to build a consolidated data source with a single-point-of-truth approach for all analyses, ensuring data timeliness according to your needs. You can also use targeted permissions to ensure that your team has access to the data they need, when they need it, regardless of location; it also enables new ways of working, like remote work and collaboration across different company locations.
A cloud data warehouse offers scalability, automatically scaling processing power and storage capabilities to meet your needs just in time. It also allows you to take advantage of Continuous Integration/Continuous Deployment (CI/CD) and DevOps practices to generate faster results through highly automated processes. And with a cloud data warehouse, you can leave the maintenance and administration of hardware to the cloud provider's experts, allowing you to fully focus on your data.
The journey to the cloud can be tricky, as old concepts need to be rethought and long-held beliefs challenged. With our many years of experience, we support you on your journey to your cloud DWH becoming an integral part of your analytics platform.
Thanks to our many years of experience, we are experts in the modernisation of existing DWHs and cloud implementations. From cloud governance to the successful implementation and operation of your solution, we accompany you step by step on the way to your cloud DWH.
We ensure a vendor-agnostic architecture definition and vendor selection process with predefined evaluation criteria, along with thorough proof of concept testing. As a trusted partner of leading service providers like AWS, Google Cloud Platform, Microsoft Azure, and Snowflake, we enable you to leverage the optimal capabilities of your solution.
Our team of experts specify the required hardware as code, enabling rapid deployment of the required cloud infrastructure with quick, secure access to all necessary configurations, and also facilitating a seamless migration to an alternative cloud provider, if necessary.
Our employees are always up to date with the latest cloud trends and the latest features offered by cloud providers, enabling us to offer implementations according to best practices. You too can benefit from this knowledge by letting us show you the latest developments and what they can do for your organisation.
Security is an indispensable part of everything we do. In all our projects, we take the utmost care to safeguard your data from unauthorised access, starting with cloud governance, architecture and configuration to access control and automated monitoring.
Data science at scale: innovative companies strive for an AI factory to minimise the cycle time and cost of analytical models from ideation to production deployment. At the heart of these AI production lines lies an analytical data platform that provides essential processes, environments, and tools. Achieving competitive advantages through advanced analytics requires mature processes for the automated identification, development, deployment, monitoring, and maintenance of advanced analytics models, and this can only be achieved through standardisation via use case blueprints, data and model governance (including data privacy), and efficient processes. The next crucial building block is the standardised implementation of sophisticated data integration processes through data pipelines. Remember that requirements for model development and deployment are distinct, so to effectively address all these requirements you need an analytical platform with extensive functionality, necessitating end-to-end integration into the system landscape of the respective customer.
Data analysis opens the door to optimising existing business processes, saving costs or improving the customer journey. Data and data management are available centrally in one place, meaning significantly shorter deployment time for new projects, easier access permission management, firewall permissions already in place, etc.
We ensure data privacy through the rigorous separation of machine learning development and machine learning operations; we also implement log management and notifications to track and log all data accesses, making them available for auditing purposes.
Deploy an automated data science workspace to accelerate model development: data ingestion is metadata-driven and there’s integration with a data catalogue to provide data pipelining as a service. Simplify machine learning operations using orchestration, AI modelling, and feedback loop services; integrate CI/CD pipelines for reliable, fast, and reproducible deployment of machine learning models, including integration into operational systems.
At synvert we have a wide range of experience in designing, setting up and operating data analytics platforms, both on-premise and cloud, regardless of the various components you might want. We have the relevant experts, best practices and the necessary experience to deliver.
As a vendor-independent company we are in the perfect position to advise you comprehensively and independently of software manufacturer interests; we are solely focused on your goals and the concrete needs of your company. Thanks to our strategic partnerships with leading cloud platforms and tool vendors, we are able to offer you a wide range of possibilities.
Cloud-based solutions scale very well, but costs need to be kept under control. Here at synvert we have the necessary experience to select a technology and service stack (complemented with open-source components) to balance performance requirements with budget considerations.
synvert takes care of the automation and reusability of all system components during the planning and implementation of your analytical platform – you’ve got nothing to worry about.
synvert and our consultants take data privacy very seriously, from the very start of the project, through all its phases and in every decision, ensuring that access to data is rigorously controlled.
Data engineering combines traditional data transformation processes with software engineering techniques to enable data for analytics using cutting-edge cloud technologies.
Data preparation often accounts for up to 80% of the time spent on analysis. Take your analytical skills to new heights by efficiently transforming valuable data into actionable insights!
Integrate data from diverse sources into a centralised analytics cloud platform, empowering your data scientists with easy access to the data they need.
Streamline your data connections with modern technologies like Apache Spark, dbt, Fivetran, Databricks, and cloud-based solutions, and enhance performance when processing large data volumes through in-memory technologies and scalable cloud services.
As a leading consulting company with over 30 years of experience in classic ETL and modern ELT processes, synvert is the ideal partner for your data engineering and integration projects. With technology partnerships with leading vendors and best practices from our ample project experience, we guide you through the process of selecting the right technology, implementing data pipelines, and operationalising data for advanced analytics. synvert utilises modern technologies to conceptualise and implement efficient data pipelines regardless of the source and target system, providing bespoke, high-performance solutions to fully leverage your data.
We offer vendor-neutral architecture definition and tool selection with predefined evaluation criteria and proof of concept testing.
We take care of the installation and configuration of the tools in your chosen environment and infrastructure.
We design and implement data transformation processes and generic ETL / ELT frameworks for use on premise or in the cloud.
Our project accelerators for various tools ensure a shorter time to market, eliminating the need for costly implementations of standard functionalities like the logging and monitoring of data paths, metadata management, or data migration.
With many years of project experience under our belt, using the relevant tools and migrating classic ETL routes to modern data engineering frameworks for loading and transformation of large amounts of data, we can bring invaluable expertise to your own project.
A lean path to the future? A greenfield approach is not necessarily the best, and our solutions can be future-proofed according to your needs through migration and replatforming. Leverage our expertise to move your solutions to a new platform via a lift-and-shift approach or migrate them to a state-of-the-art solution, enabling improvement without starting from scratch.
Cost optimisation through new cost models.
Flexibility to avoid vendor lock-in.
Building future-proof skills through the introduction of modern technologies.
Future-oriented architecture and platform as a starting point.
Performance optimisation through scalability.
The journey to becoming a data-driven enterprise often involves crucial decisions about building from scratch, migrating, or replatforming. Drawing from our extensive experience in migration and optimisation projects, we can provide valuable guidance to help you make the right decisions.
We are your strategic partner, helping you to choose between replatforming and migration, while maintaining a forward-looking approach.
Here at synvert we prioritise efficiency during implementation, ensuring that improvements are implemented at a sensible pace, without compromising the cost-effectiveness of the project.
In addition to decision-making and implementation, our developers must be cost-aware too, in order to ensure that supposed advantages with pay-as-you-go models do not turn into disadvantages and cost traps, particularly in cloud migrations.
We provide seamless change management for migration projects, addressing the the challenges often posed by the adoption of new technologies or the transition from an on-premise environment to the cloud.
The data warehouse (DWH) is the central building block for any data-driven company, whether hosted on premise or in the cloud. While new decentralised concepts like Data Mesh are gaining traction, the data warehouse is still needed by most companies to maintain a unified view of their data. However, migrating to the cloud may not always be feasible, so here at synvert we offer support for on-premise data warehousing during your DWH journey.
Single Point of Truth – a consolidated data source for all reports.
Self-Service BI – empower your employees to visualise their data themselves.
Standards – meet regulatory requirements like BCBS 239, MaRisk, or Solvency II, and support accounting according to IFRS standards.
Modern platform for BI and analytics.
Batch and streaming – data timeliness according to your needs.
ETL and ELT – data transformations with modern techniques and tools.
Automation – optimise your development with CI/CD and DevOps and generate fast results through highly automated processes.
Thanks to over 30 years of experience, we have been able to develop well-defined procedures, templates, checklists, and sample solutions that have been thoroughly tested in numerous projects across various industries. Our vendor neutrality allows us to draw on a wide range of technologies, from major manufacturers to open source, to find the perfect solution for your needs. Let us be your guide as you embark on your journey to becoming a data-driven company!
Thanks to our extensive experience, we are experts in modernising existing data warehouse solutions; we work with you to identify and address any weaknesses in previous implementations, ensuring optimal performance and efficiency.
We guarantee a vendor-neutral architecture definition and tool selection process, based on predefined evaluation criteria and proof of concept testing, thus ensuring that our recommendations are unbiased and tailored to your specific requirements.
We always emphasise cloud-readiness in the architecture and system model of your DWH solution, making it future-proof. This allows for a seamless migration to the cloud with minimal effort, or integration with cloud components in a hybrid model, providing flexibility and scalability.