Welcome to FINBOURNE Five, our new series that succinctly covers core data management methods or concepts in five minutes or less. In this first piece we’ll look at data virtualization and some of its practical applications in global financial services.
Data virtualization is a method of data delivery which enables users to retrieve, join and manipulate data from across your organisation’s disparate systems in real-time. Technical details about the underlying data including its format and physical location are not needed. The secure virtualization creates a single representation of data without having to move or replicate data.
How does data virtualization compare with traditional approaches to data management?
Unlike traditional ‘extract, transform, load’ (ETL) processes, data virtualization does not impose a single data model on the data and queries data in real-time from the source systems. This removes the need for data replication, thereby ensuring that the latest and most accurate data is used, improving efficiency and reducing costs. The flexibility of the tool enables time-consuming business challenges, such as joining data sets and migrating off legacy systems, to be rapidly resolved without an expensive IT solution.
How can financial services firm use data virtualization?
Remove data duplication: Rapidly connect and translate disparate data sources without the need to replicate data, giving the user the ability to share and reuse analytic datasets across multiple tools.
- When onboarding a new data source, in a traditional ETL process, you would typically need to build a new connection to extract and replicate the data to a staging area before loading the data into the target data table, which is both costly and highly time-consuming. With data virtualization, a new data source can be connected directly to the data virtualization tool, removing the need to create a new process, saving time, money and resources.
Remove data domicile issues: Source data does not need to be moved or copied, preventing data duplication. You can query and combine data sets without requiring source data to be replicated in a single data lake or warehouse.
- If you have data in a specific country which cannot be moved outside of the domain, for example China, data virtualization can be utilized to derive insights from this data without moving the data, avoiding governance and regulatory breaches.
Enable business intelligence systems to access timely information: Eliminate batch processing large data sets to feed systems.
Migrate legacy systems: Utilise data virtualization to seamlessly migrate legacy systems.
- Obfuscate complex queries behind business user-friendly views, enabling easy and controlled access to underlying data. Migrate sources/systems by editing the obfuscated query while having no impact to the user’s experience.
Introducing Luminesce:
Luminesce (FINBOURNE’s data virtualization product) simplifies the connection to any source or shape of data in your organisation and enables you to join it together in a single, virtual view in real-time. The platform removes the need for data replication, reducing costs and delivering efficiency; it also enables you to instantly respond to cross-business challenges as they appear, without requiring a complex IT solution. Simply combine multiple sources of data into a single, queryable data source. Luminesce provides comprehensive role-based entitlements to the source data and new data sources can be brought online and accessed within minutes.
For further details on Luminesce and to arrange a demonstration, please get in touch below:
Book a Luminesce demo (finbourne.com)
