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 – [Forrester Wave™].
Rapid advancements in data modeling (driven by artificial intelligence (AI), machine learning (ML) and real-time analytics) require greater nimbleness and data flexibility.
Relentless growth of enterprise data needs a reliable and increasingly scalable data infrastructure.
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