
Graph
Analytics
Integrated Graph Advanced Analytics:
How is it superior to
Relational Database Analytics?

Graph Analytics is 1,000x faster than a Relational Database
Graph Analytics
easily models & stores complex relationship data
& large data sets

Simplify complex queries without the hassle of multiple JOINS.
After 3-4 JOINs, Relational Database performance degrades

Easily scale to
TB or PB of data
for performance with lower cost of ownership

Effortless modeling of new relationships

Here's how Graph Analytics works.
A graph stores the relationships between data entities & can
be used to uncover relationships between data entities.







Let's look at a couple Analytics case studies.
Advanced Analytics:
Provider Case Study
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Leverage 50 million unique patients' EHRs
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Identify related EHR for better understanding of patients’ history
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Ensure better patient outcomes in less time
Provider Objectives
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Leveraged petabytes of data to load & compute the patient profile
-
Reduce call time from 24 to 18 minutes
-
Built a demonstrable track record of better patient outcomes
Results that Move the Needle
GOAL: Aggregate health records to improve patient outcomes after telehealth visit
Advanced Analytics:
Pharma Case Study
-
Leverage TB of data efficiently
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Identify referral relationships amongst
prescribers through correlation of medical & pharmacy claims data over time
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Detect communities of prescribers based on claims analysis & identify influential hubs
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Prioritize the key prescriber communities to roll out a new drug
Pharma Company Objectives
-
Leveraged TB of data
-
Load & compute was speedy & efficient
-
Graph Analytics enabled Pharma company to identify the most influential providers, to drive prescriptions for cardiac care, and to educate key prescribers on products with the best fit & efficacy for their patients
Results that Move the Needle
GOAL: Understanding relationships amongst patients & prescribers to increase sales of a new drug