Unlock insights "trapped" in rows and columns
Graph Data Science is an evolving data analytics and machine learning field that helps you understand the connections in big data to answer critical questions and improve predictions.
How graph data science can help you create business value?
Drastically improve Data Privacy, Risk and Compliance
Visualise private data and control its use while internal staff members provide fast answers to privacy inquiries. Enable privacy managers to trace data flows, investigate potential breaches, and prove compliance to regulators. Without graph technology, it’s almost impossible to understand the full lifecycle of personal data. The visualisation, data lineage, connected data analysis and pattern detection make perfect use cases for graph technology.
Power more accurate recommendations in real time
Increase revenue with real-time recommendation engines, a key to the success of any online business. To make relevant recommendations in real time requires the ability to correlate product, customer, inventory, supplier, logistics and even social sentiment data. Moreover, a real-time recommendation engine requires the ability to instantly capture any new interests shown in the customer’s current visit.
Enrich your data for complex decision-making with knowledge graphs
Create your knowledge graph, an insight layer of interconnected data enriched with semantics, so you can reason with the underlying data and use it confidently. A knowledge graph gets richer as new data is added. Through a combination of data, graph, and semantics (meaning), you get a knowledge graph with deep, dynamic context.
CASE STUDY: PROFILE BUILDER
An IoT anomaly detection platform
Squaredev worked with Exus to create a platform that, when installed in an IoT network, can detect any network anomaly targeting the connected devices. It acts as a security layer on the IoT network, protecting it from attacks with smart alerting. The solution is based on graph data science algorithms and models developed by Squaredev.
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