Graphs for Real- Time Analytics at Scale

Until recently, real-time analytics has been challenging to deliver at the speed and scale required of applications. Here’s why:

• Finding new insights from data is an iterative, continuous, expensive, laborious process of connecting various data sets, on-premises or in the cloud.
• Legacy technologies complicate the analysis process, requiring developers and data scientists to write complex code that is time-consuming
• Rapid advancements in data modeling (driven by artificial intelligence (AI), machine learning (ML), and real-time analytics) require greater nimbleness and data flexibility.

• The relentless growth of enterprise data needs a reliable and increasingly scalable data infrastructure.