While technologies such as data lakes, data catalogs, and data integration platforms have promised to end data silos, the truth is, data silos are inevitable! They exist for excellent reasons. They allow for local control and governance when important to a particular part of your business. Some data must be stored apart from other data to comply with legal regulations or simply for legacy business reasons. Or data is just too essential to business operations to bear the risk of consolidating, eliminating, or modernizing it.
Data silos are the result of enterprise data that is:
- Diverse, and only becoming more diverse as unstructured data growth rates skyrocket.
- Distributed across multiple systems in different places, particularly as hybrid and multi-cloud computing become necessary.
- Controlled by division business leaders who may have competing interests.
- Enabled by vendors who want to lock you into their solution.
Whereas previous data management solutions have focused on eliminating silos through mastering, migration, consolidation, or governance, data fabrics offer a practical alternative to fighting data silos. Rather than working against data silos, a data fabric leverages these data silos without requiring further copies of data.
Leverage existing data management systems for your data fabric
Instead of replacing legacy technologies, a data fabric works alongside existing investments and improves their utility. This is because a data fabric is not a single solution; it is an architecture design that operates at the compute layer and focuses on connecting data wherever it resides. Thus, a data fabric improves upon existing data storage assets like data lakes and warehouses, data catalog software, and other data integration platforms like MDM.
The key to getting started: an Enterprise Knowledge Graph
The mechanism for weaving the fabric is an Enterprise Knowledge Graph (EKG). The EKG sits at the compute layer, as seen in the diagram above, and connects disparate data of any structure using semantic graph.
Semantic graph creates meaning by mapping entities, their metadata, and their relationships in an evolving information network. Semantic graph, also called RDF graph, is the only way to represent data natively stored in other structures while maintaining all relevant metadata and context.
With Stardog, different data dialects and structures embedded in legacy systems can be represented in the standard language of RDF. This allows for queries across relational databases, NoSQL databases, documents, and even geospatial data.
Designing your data fabric with Stardog
A successful data fabric requires leveraging and connecting existing source systems. Stardog’s Virtual Graphs capability connects to existing data catalogs, data lakes, databases, and other data management platforms, offering comprehensive support of the most important enterprise data sources.
The power of data virtualization in Stardog means not having to wait for long, costly data preparation and migration processes to start deriving value from unified data. With Virtual Graphs, you’re now guaranteed to always get the most up-to-date data every time you ask a question.
However, we recognize that not all data can be virtualized, whether due to regulation or internal policy, so Stardog offers both world-class graph virtualization and world-class graph storage. Use both in combination to support the needs of different data owners while still feeding your Enterprise Knowledge Graph.
Given the scale and velocity of today’s enterprise data landscape, including hybrid cloud and multi-cloud environments, no one solution is best for every data problem. The future of data management is hybrid. Accordingly, you can store some data in Stardog and leave other data in its native data silo, and Stardog can query all of the data based on what it means, not where it lives.
Begin your data fabric journey
Want to learn more about how Stardog works alongside your existing investments to contribute to your overall data fabric design? Check out our Comparison pages which go deeper into how Stardog works alongside the following data management technologies.