Real-time analytics presents a view into the immediate state of business processes. Ordinal Science joins high throughput streaming data and analyzes information for instant, informed decision making. Real-time analytics challenges the traditional paradigm of slow data collection and delivers data in time to affect a positive change on operational situations.
“It’s about combining and analyzing data so you can take the right action, at the right time, and at the right place.”
– Mike Barlow, Author of Real-Time Big Data Analytics: Emerging Architecture
Companies today generate a constant steam of data, yet the reporting tools take hours of days to collate with limited analytical insight. If the real-time data is key to business decisions then yesterday’s reports are too late. The lack of real-time visibility forces companies into inflexible process to manage situations that can benefit from minor ongoing adjustments with intelligence from the field.
We use streaming platforms such as Kafka, Storm or Kinesis to ingest high throughput data generated in real-time. We analyze the real-time stream in Spark to aggregate data, find anomalies, calculate statistics, then present results immediately to users and subscribers. Our apps present a simple, powerful picture of the situation at the speed of data.
Ordinal Science overcomes the challenge or merging unstructured real-time data with resampling, validation and windowing. The platform presents analytical insights into easy to interpret landing pages that are updated continuously. Your team has up to the minute information to make decisions based on factors that would previously take weeks to assemble.