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We were frustrated by the limitations of our previous businessintelligence (BI) solution, which was holding us back from our vision to accelerate data sharing, team collaboration, and security within Amazon. This framework can be described as follows: Findable – Metadata and data should be easy to find for both humans and computers.
Business metrics – Providing KPIs, scorecards, and business-relevant benchmarks. In parallel, the Pinot controller tracks the metadata of the cluster and performs actions required to keep the cluster in an ideal state. Anomaly detection – Identifying outliers or unusual behavior patterns.
Metadata management has played a role in data governance and analytics for many years. It wasnt until the emergence of the data catalog as a product category just over a decade ago that enterprises had a platform for metadata-driven data management that could span multiple departments and use cases across an entire enterprise.
What we consistently overlooked were the direct and indirect consequences of disruption to business continuity, the challenges of acquisitions and divestitures, the demands of integration and interoperability for large enterprises and, most of all, the unimpressive track record for most enterprise transformation efforts.
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