Data plays a crucial role in enabling businesses to deliver on their digital transformation strategies. In fact, as evidenced in the recent Cambridge Analytica scandal, it can make or break a business. By capitalising on enterprise information, businesses can unlock value to reveal hidden customer behaviour patterns.
However, this insight can only be derived from a modern data and analytics platform. This platform should be integrated with data virtualisation components that support every aspect of data from acquisition and transformation to storage, analysis and delivery.
The Need for a Modern Data Architecture
A modern data architecture or a hybrid version at the least will help businesses respond to dynamic industry changes and address customer needs. It will prove useful in the following instances.
- Modern data sources to find answers to critical business questions. From chatbots to social media, these applications are available in various formats, speed and volume.
- Addressing complex business issues with advance tools, techniques and self-serve capabilities for analysing data in a sandbox like environment.
- Augmenting investments in enterprise data warehouses (EDW) with a modern data architecture.
- Innovative ways of presenting data through data visualisation using graphs, infographics, animated charts and more to bring multiple perspectives together.
- Achieving agility in data adoption and implementation using Data-as-a-Service.
Bridging the Gap with Data Virtualisation
As part of the transformation process, businesses can modernise their data architectures with data virtualisation. I’ve listed below architecture principles that data virtualisation components should align with for digital transformation success.
Data as shared asset
Using data virtualisation techniques organisation can view data at single location as a “Logical View” instead of departmental data silos to persist, these enterprises ensure that all stakeholders have a complete view of the company.
Single source of truth
Applications should access data from a single source. This can be created using the “logical view” offered by data virtualisation and can be accessed as data-as-a-service using REST APIs.
Eliminating data copy and movement
As data virtualisation techniques do not move data from underlying source system, this eliminates data movement and copy of the same data across various layers. This also saves on an escalation of storage cost.
Creating common business vocabulary
As enterprises build a data bus using data virtualisation techniques, then can create a shared data asset for multiple consumers across the business. The shared bus must be based on a common vocabulary and product catalogues. Additionally, fiscal calendar dimensions, account dimensions, provider hierarchies and business KPI definitions all need to be common regardless of how users consume or analyse the data.
The figure below demonstrates where a data virtualisation component sits within a modern data architecture.
Data virtualisation serves as a building block on the path to digital transformation success. While it helps organisations build an uniform data access view, it also serves as a neutral layer between databases and applications from different technology providers and vendors.
Don’t let data hinder organisational productivity! Find out how Mastek’s Data Virtualisation solution can help you gain insight up to 5 times faster.