Simplify your data ecosystem
Single service, multiple workloads
Data management is often said to be about removing silos, but many legacy data management tools ultimately create more silos than they remove. Different tools for specific data types. Separate tools for data governance, data integration, data quality and data mastering. Multiple separate databases to cope with ever-higher data volumes.
Utilising the Datasynthesis Platform’s cloud-native scalability and concurrency, it offers a more integrated approach to enterprise data quality. Instead of more and more instances of different data tools being installed, one service is simply applied to each data workload, and the platform automatically allocates the resources necessary to get the job done.
Near-infinite scale to address all your needs
The data architecture at many organizations is a complex network of legacy tools and operational databases that is becoming ever-more difficult and costly to manage and maintain. The inherent lack of scale in legacy systems and tools drives a defensive approach to allowing a business to make the most of its data. Rather than the driven-by-data goal of digital transformation projects, you are left with a constrained-by-data business.
The Datasynthesis Platform has been designed as a cloud-native solution, one that can offer near-infinite processing capacity, storage capacity and concurrency of user access. With the constraints of scale removed, it now becomes possible to move towards a modern data architecture that is simpler, free of systems maintenance and that offers the scale to meet both current and any future data processing needs.
Your path to a modern data architecture
Incremental improvement and scale
Migration to more efficient ways of managing data quality is a difficult problem in the context of legacy systems in existing data architectures. A big-bang approach to modernising data architecture would be almost impossible to implement and more importantly, almost certain to fail.
The Datasynthesis Platform takes a much more flexible, non-invasive approach where it can be incrementally take on certain workloads whilst sitting alongside your existing set of tools. As more data management workloads are migrated across, no new software needs to be installed and the services managed by the platform automatically scale to meet the new processing, storage and concurrency needs. Gradually the complexity and costs of your existing data architecture can be drastically reduced, whilst at the same time data quality and enterprise consistency are improved.
Turn your upfront CapEx into controllable OpEx
On-premise solutions can involve a very high degree of upfront costs involving software licensing, hardware and implementation before any value is delivered. Add to this the risk of sizing the system before all the consequences and possibilities of its introduction can be properly assessed.
The Datasynthesis Platform’s cloud-native design offers a pay-as-you-go approach. It offers low upfront costs, combined with rapid implementation and no sizing risks. Time to value is improved and ROI increased.
Provision with security and trust
Secure, governed access to your data
Data security is a key concern for all organisations. Regulations such as GDPR have driven many security initiatives, but in addition the sheer reputational damage of a data breach is something that is unquantifiable for many. In a data architecture of comprised of many legacy tools with complex cross-dependencies, it is unsurprising that weaknesses exist and are difficult to mitigate.
The Datasynthesis Platform provides a single set of secure services for accessing enterprise data. These services take care of authorizing users, authenticating credentials and granting access to only the data they have been permissioned to see, based on their role in the organization. Given the scalability of the platform, point-to-point and departmental tools can gradually be rationalised as you move towards a modern, simpler and more secure data architecture.
Near-zero systems maintenance
Use less resources on the mundane, focus on the strategic
Putting aside the direct licensing and support fees incurred in many legacy data architectures, so much resource is deployed simply to maintain systems, optimize databases and in the general administration of IT. Organizations need to free IT resources to deliver on strategic business initiatives rather than on the tedium of maintaining the status quo.
The cloud-native design of the Datasynthesis Platform means that scale and capacity issues around processing, storage and user concurrency are no longer constraints. The platform’s modern, serverless design means that it automatically scales to meet the agreed performance service levels. Combined with a no-code approach to enterprise data rule management, the mundane maintenance workload for IT is drastically reduced, enabling greater focus on projects that can deliver new value to the business.
Decouple IT and data to the benefit all
Less time on data requests, more on strategic delivery
For many IT experts, it is frustrating to receive seemingly ad-hoc requests from data professionals to correct some data issue, particularly when these requests compete for time with the project deliverables you have been tasked with. And for many data experts, it is frustrating that many organizations use data quality tools that need programming skills to monitor and improve data quality.
Adopting a self-service approach, the Datasynthesis platform offers no-code data governance and data quality management. This increases the productivity of the IT expert as data issue are left to the people who know the data best and frees the data expert from dependency on IT time and resource. Combining this approach with the scalability of the platform enables data experts to ask questions such as “Tell me about any data issues right now” and receive enterprise-scope responses in real-time, delivering a new level of transparency for enterprise data quality.
Faster development of data applications
Accelerate your development deliveries with repeatable service catalogs
For many IT departments, their task in delivering new applications based on data is made more complex if attempting to consolidate different sources of data from a diverse, complex legacy data architecture. Understanding the data that business users need is made even more difficult when there isn’t a common way of finding data definitions and each type of data requires a different access method.
The Data-as-a-Service approach of the Datasynthesis Platform means that developers use standard service catalogs for finding and retrieving enterprise data, accelerating project delivery through a repeatable approach to accessing high quality data. Based on a Common Data Model, data, its transformation and flow for the new application are transparently available to all, leveraging and building on what has gone before.
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Please contact us if you would like to discuss how you could migrate away from the costs and complexity of legacy data tools and incrementally deploy a modern data architecture.