Effective, Integrated Master Data Management with AgensGraph
Master Data Management with AgensGraph: Bring Down the Walls
Research institutes generally lack the database technology to properly unify its data in order to readily access and analyze it with an intuitive view, accuracy and efficiency. When they fall short in this area it quickly leads to organization-wide inefficiencies, risk and added cost, operational performance and research team frustration.
Bitnine solved this problem for a research institute by delivering a platform that standardized and unified isolated information and now allows for the visualization of analytical data in ways never possible before.
With AgensGraph, now every member of our client research team has ubiquitous access to critical data once hidden before.
They now have a clearer understanding and access to real-time data, more efficient and effective at their jobs, and most importantly they reduced the risk of producing faulty research results.
Most database systems are simply not designed for the kind of information collaboration required by researchers.
These systems come with enormous ‘opportunity cost’, for example, data may not have been joined for the consideration in a critical study because the database was not available.
Then, research produces what they consider to be a conclusive, exhaustive summary of evidence, only to find there was additional and vital information available that would have changed the outcome of the research.
It’s easy to see the problems and inefficiencies that occur when non-standardized data is scattered across multiple databases in different formats.
In this case, they had phased research findings pouring in from different departments including both unstructured and structured master data.
To further complicate matters, there was no data model that allowed for quick modifications and provided an intuitive, analytic view of the intertwined data.
As swift and timely responses to major issues were almost impossible, they were unproductive and found themselves needlessly wasting valuable time locating and organizing the data they needed.
Master Data Management with Multi-Model Graph Database: Bring Down the Silos
To unify different data formats, enable associations between unstructured and structured data, and empower institutions of research with the means to visualize their disparate, scattered multi-formatted data from whatever perspective they chose, AgensGraph was the only path for a walkthrough.
By implementing AgensGraph we standardized and consolidated data it into a single repository, reorganized data structures to unify access to all formats, and removed redundant and inaccurate data.
Our client’s data was managed on PostgreSQL environment, which means implementing graph database into their existing system could be quite an ugly and challenging task.
But, through the implementation of AgensGraph, the world’s only relational-graph multi-model graph database system that integrated PostgreSQL, it was possible to leverage the powerful attributes of graph model with minimizing the migration cost of graph database.
If you want to know more about this story, please visit Bitnine website to get the details of this case.
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