Analyzing data distribution

Maintain schema health and ensure data is distributed efficiently across the cluster by auditing database structures and diagnosing storage bottlenecks. Use the Data Analysis panel on the left sidebar to monitor table growth, identify bloat, and resolve data skew.

Optimizing storage and schema health

Monitor the scale of your relational data and verify that your storage settings are optimized for analytical workloads with the Tables tab.

• To validate compression efficiency, observe the Compression and Level columns. If the compression ratio is low for a large table, consider adjusting the algorithm (for example, switching to zstandard) to reclaim disk space.
• Check metadata freshness by monitoring the Last Analyze timestamp. If a table hasn't been analyzed recently, the query planner might use stale statistics, leading to inefficient execution plans.
• Manage external data services with the External Tables tab, which provides an overview of external tables and their sources.
• Inspect views with the Views tab. For materialized views, use the Materialized Views tab, which also exposes Size, Storage Type, Compress Type, and Compress Level for each view.
• Review installed extensions with the Extensions tab.

Improving performance and storage efficiency

Ensure your data structures support rapid query execution and simplified data lifecycles using the Indexes, Partitions, Missing Stats, Bloat, and Data Skew tabs.

• Identify tables with stale statistics using the Missing Stats tab. Select Run ANALYZE in the Actions column to update statistics for a table directly from the interface.

• Reclaim wasted disk space using the Bloat tab. The Dead (MB) and Bloat % columns help you prioritize which tables to address. Use the Actions column to run either VACUUM (quick, non-blocking cleanup) or VACUUM FULL (full space reclamation, blocks all table access until complete). VACUUM FULL requires confirmation before running.
• Resolve data distribution imbalance by looking at the Data Skew tab to find tables where data is unevenly spread across segments. A high skew percentage indicates that a single segment is doing more work than others, slowing down the entire cluster. If a large table shows significant skew, investigate the distribution key and consider using ALTER TABLE ... SET DISTRIBUTED BY to choose a column with higher cardinality or fewer nulls.

Planning long-term storage and capacity

Analyze the physical composition of your database and identify long-term storage trends with the Charts tab.

• Prioritize archival candidates by reviewing the Top 50 Tables by Size (GB) bar chart to see which objects are candidates for partitioning or data archiving.
• Audit storage formats by looking at the Storage Format Distribution pie chart. If a majority of your data is in Heap format, plan a migration to append-only storage to optimize for high-volume analytical reads.