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About the role
Ingest and validate 18+ months of Teradata DBQL logs including SQL text, object usage, timestamps, user/application IDs, row counts, and steps. Integrate metadata from Autosys (scheduling), DataStage (orchestration), and MagicWand (observability) to supplement DBQL analysis. Build end-to-end, log-driven analysis pipelines in Databricks to identify unused datasets, read-only (non-updating) datasets, and unused partitions within active datasets. Capture and analyze CPU/IO resource usage and workload statistics (ResUsage) to quantify cost-reduction opportunities. Classify data into cold, warm, and hot tiers; generate heatmaps of date/partition access patterns. Develop a prioritized recommendation backlog with expected savings, risk levels, and required changes. Apply AI/ML models or LLM-assisted analysis to detect access pattern anomalies, predict cold data candidates, and automate classification. Produce and present deliverables: Observation Report, Workshop Notes & Action Log, and Final Readout for customer stakeholders. Ingest and validate 18+ months of Teradata DBQL logs including SQL text, object usage, timestamps, user/application IDs, row counts, and steps. Integrate metadata from Autosys (scheduling), DataStage (orchestration), and MagicWand (observability) to supplement DBQL analysis. Build end-to-end, log-driven analysis pipelines in Databricks to identify unused datasets, read-only (non-updating) datasets, and unused partitions within active datasets. Capture and analyze CPU/IO resource usage and workload statistics (ResUsage) to quantify cost-reduction opportunities. Classify data into cold, warm, and hot tiers; generate heatmaps of date/partition access patterns. Develop a prioritized recommendation backlog with expected savings, risk levels, and required changes. Apply AI/ML models or LLM-assisted analysis to detect access pattern anomalies, predict cold data candidates, and automate classification. Produce and present deliverables: Observation Report, Workshop Notes & Action Log, and Final Readout for customer stakeholders.
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