What is Real Time Analytics? Explain in Brief
The analytics is a science that uses logic and mathematics to analyse data in order to generate insights that help people make better decisions faster. For certain use cases, real-time merely implies that the analytics are finished within seconds or minutes of fresh data arriving. On-demand Real time analytics/analysis waits for a query request from users or systems before delivering the analytic findings. Continuous real-time analytics is more proactive, triggering warnings or replies as events occur.
To begin, Live analytics/analysis is a layer of technology that sits right on top of your cloud data platform, allowing everyone in your business to connect with live data in an unlimited number of ways. Second, each dataset, graph, and insight may be interacted with. You may use Live Analytics to look for answers, ask follow-up questions, and dig down to the row level to figure out not just what's going on in your organisation, but why. Because each query is conducted in real-time on your cloud data, you can be sure that your insights represent what's going on in your organisation right now, rather than a snapshot of two days or two months ago.
Why is post analysis important?
A Post analysis is looking at data after research has been completed in order to uncover patterns that were not the study's original goals. In other words, post analyses are any analyses that were not planned ahead of time and were carried out as 'extra' analyses after the experiment was completed.
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