Twenty years ago data was only useful for reporting purposes, while now it has become the ultimate means to make business processes smarter. Data must be available increasingly faster, in larger quantities, and in more places for more complex analyses, and that places high demands on the underlying data architecture.
Many companies notice that their data warehouse solution has reached its limits and are looking for a way to migrate to an integrated data platform that can flexibly grow with the corporate ambitions and the technological developments.
Kadenza helps you to design and build such a modern data architecture, in line with the chosen cloud strategy with maximum scalability and manageable costs.
A modern data platform sets itself apart from the traditional data warehouse on two important points. Firstly, such a platform is ‘designed for the cloud’ and makes optimal use of all functional and technical possibilities of the relevant cloud platform. In addition, data virtualisation is used to minimise data replication and to ensure maximum uncoupling of data and logic.
The combination of a cloud platform and data virtualisation makes it possible to connect new data sources and establish new data services much faster, also for real-time data. Via data virtualisation, one can offer all kinds of formats, without the need to constantly replicate the data. The underlying cloud platform also ensures the required performance level, even when large data volumes are involved. you can up- or downscale resources at any moment.
Perhaps your organisation already has a cloud strategy, and the next logical step is to migrate your existing data warehouse to the cloud too. That’s the ideal opportunity to let go of your old ways of thinking and to implement a radical architectural change. Cloud platforms bring possibilities about that we could previously only dream about. A good example is Snowflake, an analytical database developed for the cloud, with implementations on Microsoft Azure and AWS. Snowflake gives you access to a highly scalable MPP database that supports ANSI SQL and hardly requires management. An extremely powerful combination with the functionality, for example, of Microsoft Azure. Also scalable from minor implementations to company-wide, distributed data architectures.
Uncoupling with data virtualisation
When migrating to the cloud, however, you must take care to avoid the old pitfalls. One should not create various architectural layers in the new data platforms, between which to replicate data. That only makes the development process complex and inflexible. Also, it’s important to properly separate the data and logic, in view of flexibility and data governance requirement. This is where data virtualisation comes into play. By steering clear of physical data integration, the process of developing and testing data services, in any format you desire, becomes much simpler. From data sets for data science and self-service BI, to complete API libraries. Moreover, a data virtualisation platform offers excellent possibilities for data lineage, authorisation and on-the-fly data anonymisation.
When designing new data architectures Kadenza uses a reference architecture for Microsoft Azure in combination with Snowflake and the Denodo data virtualisation platform. This reference architecture is made so that it can evolve with the rapid technological developments. For each functional architecture component, the best technological fit is being made, preferably as a ‘service’ that one merely has to configure. When new functionalities become available, you determine how the technology might improve or enrich the data platform.
The reference architecture provides endless possibilities and functions that you can activate and try out with the push of a button. What’s more, up- and down-scaling new applications is easy. Thus, you can discover whether a technology is really usable, at an early stage.
Let’s get to work!
Designing a new data architecture does not necessarily have to take weeks or months. Thanks to the reference architecture, we, along with your team, can work out a data platform that suits your organisation, ambition and application landscape. With the flexibility of the reference architecture, the cloud platform and data virtualisation, we can then help you, in quick, short cyclical steps, to work out the use cases and to start building your data platform in the cloud.
Proof of concept
We can easily try out the different architectural components with you (and also new possibilities in the future), in a representative proof of concept. The cloud platform gives us all the leeway, at a low cost, to determine whether new functionality is of value to your architecture.
Of course, we give careful prior thought to what y9u want to achieve with the addition of a component, because new functionality is released almost daily, and it’s not sensible to give everything a try. By properly monitoring the architecture in terms of context, we prevent initiatives from getting bogged down in various detached experiments without any common thread or clear goal.
Snowflake in practice
“Able to handle any scale of data, workloads & users”
- Zero-management data warehouse-as-a-service in the cloud
- The unique Snowflake architecture divides the power of calculating from storage, so that organisations can up- and downgrade quickly,
- Snowflake supports all kinds of data, from traditional databases to big data sources
Clients appreciate us for our sincere interest, professionalism and the results that we achieve.
- Business applications, organisation or technology: our employees know what is involved.
- We build bridges in the data-driven organisation. Bridges between business and IT and between technology and user.
- The experience that we have acquired is incorporated into tools, methods and reusable knowledge.