The Logical Data Warehouse

Ontology 4 is a key enabler of the Logical Data Warehouse, the next step in accessing enterprise data in a Big Data world.

Traditional data warehousing used to represent the state of the art way to derive insight from organisations' data estates. However, technical challenges such as the long delivery times required to access new information types, as well as performance management issues relating to dealing with ever bigger data warehouses have led users to question the suitability of traditional, monolithic data warehouses to deliver against modern data access requirements.

Ontology 4 addresses the three key trends that will shape next generation approaches to data warehousing:

Everything faster

Extending the data warehouse to accommodate new types of data must become a quick, low-risk, routine activity instead of the heavy-lift, big budget project it is today. Ontology's graph-based data representation requires no schema which enables iterative implementation and avoids the sort of lengthy, big-bang, upfront analysis cycles of traditional schema-based approaches. Ontology's ability to access and link virtually any data source with no upfront risk and no traditional data integration means that adding data and new data types, can become an ongoing, low cost, routine activity.

Big Data

Gaining actionable insight into Big Data sets, requires that the Big Data estate is linked to, and seen in the context of, the rest of the organisation's data estate. The high velocity, volume and variety of these Big Data sets can cause traditional storage and query solutions to no longer function. Ontology 4 is specifically designed to link data from different sources and provides a mix of access methods including "on demand" data fetches and mixed-source searches. This means that big data sets, can be fully exploited in the context of their relationships with other enterprise data.

Search and unstructured data

Some enterprise data has historically only been available to access in aggregate form through enterprise search and document management systems. In order for these search-only sources of aggregated enterprise structured and unstructured data to be included in the goals of a data warehouse, it must first be understood in the context of the wider data estate. Ontology 4 provides integrated search of both structured and unstructured data sources, and unlike traditional data warehousing solutions that struggle to import or even access these search-only data sources, Ontology sees them as just another data source.

The logical data warehouse is emerging as the architectural approach that will accommodate these trends and address the Big Data issues that are stretching traditional data warehousing approaches. The Logical Data Warehouse requires a radically different, lower risk and more flexible approach to data access and data linking. Ontology 4 provides the foundation for this new way of seeing enterprise data.

Read more about Ontology as an enabler for the logical data warehouse in the Ontology Big Data and the Logical Data Warehouse Whitepaper here.