YarcData's Urika Shows Big Data is More than Hadoop and Data Warehouses (Carl Claunch, Sept 11, 2012)
- Why data discovery is hard
- Analyst validation
- Discover unknown linkages
- Purpose built
- The power of graph analytics
- What fits into 512 TBs?
- Easy to deploy
The power of graph analyticsGraph analytics is the way to true data discovery. It’s big data without the schema. It’s bringing relationships between data front and center, ready to be queried. It’s ingesting new data sources to combine with the old. It’s exposing patterns between unlike data structures.
In short, graph analytics adapts big data to big discovery. So you can get to “Eureka!” faster. Here’s how.
- Discovery at its essence is about seeing patterns. When it comes to data, this means seeing their relationships. Graphs provide a flexible model of data relationships that can easily grow to bring new relationships to the surface – even when data entities are continually ingested from new and different data sources.
- Discovery can’t predict what questions to ask the data. That’s ok because graphs are not constrained with a schema. Instead, they can ingest and expose a growing set of data relationships – all from disparate sources and all ready to be queried.
- Discovery with the best chance of getting to “Eureka!” demands real time response. The data model for graphs lends itself for adaption to purpose-built appliances that deliver real time performance in support of data discovery.
Graphs make big data discovery a viable endeavor. But it’s the purpose-built appliance delivering real time graph analytics performance that makes it feasible…