transitioning into big data analytics
summary
Claim: a Hadoop-native end-to-end stack lets business analysts access entire data lake in a day without IT, connecting a visual Tableau-like interface to a visual data catalog/wrangling layer that auto-drives Hadoop jobs and populates a scale-out in-memory layer for subsecond interaction. Built on Cloudera/Hortonworks/MapR, integrates Spark for ML and graph, accepts Spark artifacts, and reports 210% year-over-year growth in 2014 and a trebling of Global 2000 customers. Example: pivot from a 5 million‑person segment to social sentiment in minutes.
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chapters (15)
- 0:00Introduction
- 0:20BI to big data transition
- 1:02Classic BI limitations
- 1:22Platform4 Hadoop stack
- 2:05Data lake growth
- 2:48Oracle big data initiative
- 3:52Big data two-horse race
- 4:14End-to-end platform meaning
- 5:37Pre-distilled data model problems
- 6:18Platform4 three-layer integration
- 7:22Real-time big data demo
- 8:03Platform4 Spark support
- 8:47Spark future in big data
- 9:49Balanced Spark integration
- 10:09Closing remarks
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