# DATA MANAGEMENT - [Data Management Overview](https://docs.apica.io/data-management/overview.md) - [Data Explorer Overview](https://docs.apica.io/data-management/overview-1.md) - [Visualizations](https://docs.apica.io/data-management/overview-1/visualizations.md): Apica offers a variety of visualizations to support different use cases. This section of the documentation highlights the built-in visualizations, their options and typical usage. - [Line](https://docs.apica.io/data-management/overview-1/visualizations/line.md): A line chart shows trends over time by connecting data points. Use it for time series metrics and comparisons across multiple series. - [Bar](https://docs.apica.io/data-management/overview-1/visualizations/bar.md) - [Area](https://docs.apica.io/data-management/overview-1/visualizations/area.md): An area chart shows trends over time with the area under the line filled in. Use it to highlight magnitude and compare multiple series. - [Scatter](https://docs.apica.io/data-management/overview-1/visualizations/scatter.md): A scatter plot shows relationships between two numeric fields. Use it to spot correlations, clusters, and outliers. - [Barrace](https://docs.apica.io/data-management/overview-1/visualizations/barrace.md): A bar race chart animates ranked bars across time. Use it to show how top categories change between time frames. - [Bubble](https://docs.apica.io/data-management/overview-1/visualizations/bubble.md): A bubble chart plots X and Y values and uses bubble size for a third metric. Use it to compare three dimensions at once. - [Boxplot](https://docs.apica.io/data-management/overview-1/visualizations/boxplot.md): A box plot shows the distribution of a metric across time buckets or groups. Use it to spot variability and outliers. - [Heatmap](https://docs.apica.io/data-management/overview-1/visualizations/heatmap.md): A heat map shows how a numeric metric varies across two dimensions using color intensity. Use it to spot hotspots and patterns. - [Sunburst](https://docs.apica.io/data-management/overview-1/visualizations/sunburst.md): A sunburst chart visualizes hierarchical data using concentric rings. Use it to understand proportional breakdowns across levels. - [Funnel](https://docs.apica.io/data-management/overview-1/visualizations/funnel.md): A funnel chart shows how a metric changes across ordered steps. Use it to measure drop-off, progression, or stability between stages. - [Sankey](https://docs.apica.io/data-management/overview-1/visualizations/sankey.md): A Sankey chart visualizes how a numeric metric flows across ordered stages. Use it to understand movement between categories and spot imbalances. - [Status](https://docs.apica.io/data-management/overview-1/visualizations/status.md): A Status chart displays a single metric as a health state using text and color. Use it to show UP/DOWN/OK style states based on thresholds. - [Counter](https://docs.apica.io/data-management/overview-1/visualizations/counter.md): A Counter displays a single numeric value as a large, prominent number. Use it for KPI tiles like totals, capacity, or current usage. - [Stat](https://docs.apica.io/data-management/overview-1/visualizations/stat.md): A Stat chart shows a single key metric with its recent trend. Use it to see the latest value plus context over time. - [Size](https://docs.apica.io/data-management/overview-1/visualizations/size.md): A Size chart displays a single numeric value formatted into human-readable units. Use it for data volume, storage, and large numbers. - [Gauge](https://docs.apica.io/data-management/overview-1/visualizations/gauge.md): A Gauge chart displays a single metric as a percentage of capacity using a dial. Use it to see how close you are to a limit. - [Disk](https://docs.apica.io/data-management/overview-1/visualizations/disk.md): A Disk chart is a capacity indicator. It shows used vs total as a percent-full ring. - [Datetime](https://docs.apica.io/data-management/overview-1/visualizations/datetime.md): A DateTime chart displays a time-based value as a human-readable duration. Use it for uptime, age, and time-since metrics. - [Densestatus](https://docs.apica.io/data-management/overview-1/visualizations/densestatus.md) - [Honeycomb](https://docs.apica.io/data-management/overview-1/visualizations/honeycomb.md): A Honeycomb chart shows the status of many entities as color-coded hexagons. Use it for at-a-glance fleet or cluster health. - [Pie](https://docs.apica.io/data-management/overview-1/visualizations/pie.md): A Pie chart shows how a total is divided across categories. Use it for quick part-to-whole breakdowns. - [Table](https://docs.apica.io/data-management/overview-1/visualizations/table.md): A Table chart shows query results as rows and columns. Use it when you need exact values instead of a visual summary. - [List](https://docs.apica.io/data-management/overview-1/visualizations/list.md): The List visualization shows tabular data as rows and columns. Use it to inspect exact values and detailed records. - [Pivottable](https://docs.apica.io/data-management/overview-1/visualizations/pivottable.md): A Pivot Table summarizes large datasets into a grid using grouping and aggregation. Use it to compare totals across multiple dimensions. - [Searchable-table](https://docs.apica.io/data-management/overview-1/visualizations/searchable-table.md): A Searchable Table lets you explore large datasets with search, filters, and pagination. Use it for investigation and validation. - [Details](https://docs.apica.io/data-management/overview-1/visualizations/details.md): A Details Table shows one record at a time as key–value fields. Use it for deep inspection of metrics, events, or log entries. - [Page](https://docs.apica.io/data-management/overview-1/page.md) - [Query Builder](https://docs.apica.io/data-management/overview-1/query-builder.md) - [Widget](https://docs.apica.io/data-management/overview-1/widget.md) - [Alerts](https://docs.apica.io/data-management/overview-1/alerts.md) - [JSON Import](https://docs.apica.io/data-management/overview-1/json-import.md) - [Creating Json Schema](https://docs.apica.io/data-management/overview-1/creating-json-schema.md) - [Visualization](https://docs.apica.io/data-management/overview-1/creating-json-schema/visualization.md) - [Line chart](https://docs.apica.io/data-management/overview-1/creating-json-schema/visualization/line-chart.md) - [Bar chart](https://docs.apica.io/data-management/overview-1/creating-json-schema/visualization/bar-chart.md) - [Area chart](https://docs.apica.io/data-management/overview-1/creating-json-schema/visualization/area-chart.md) - [Scatter chart](https://docs.apica.io/data-management/overview-1/creating-json-schema/visualization/scatter-chart.md) - [Status chart](https://docs.apica.io/data-management/overview-1/creating-json-schema/visualization/status-chart.md) - [Counter chart](https://docs.apica.io/data-management/overview-1/creating-json-schema/visualization/counter-chart.md) - [Stat chart](https://docs.apica.io/data-management/overview-1/creating-json-schema/visualization/stat-chart.md) - [Size chart](https://docs.apica.io/data-management/overview-1/creating-json-schema/visualization/size-chart.md) - [Dense Status chart](https://docs.apica.io/data-management/overview-1/creating-json-schema/visualization/dense-status-chart.md) - [Honeycomb chart](https://docs.apica.io/data-management/overview-1/creating-json-schema/visualization/honeycomb-chart.md) - [Gauge chart](https://docs.apica.io/data-management/overview-1/creating-json-schema/visualization/gauge-chart.md) - [Pie chart](https://docs.apica.io/data-management/overview-1/creating-json-schema/visualization/pie-chart.md) - [Disk chart](https://docs.apica.io/data-management/overview-1/creating-json-schema/visualization/disk-chart.md) - [Table chart](https://docs.apica.io/data-management/overview-1/creating-json-schema/visualization/table-chart.md) - [Date time chart](https://docs.apica.io/data-management/overview-1/creating-json-schema/visualization/date-time-chart.md) - [Time-Series AI/ML](https://docs.apica.io/data-management/overview-1/time-series-ai-ml.md) - [Anomaly Detection](https://docs.apica.io/data-management/overview-1/time-series-ai-ml/anomaly-detection.md) - [Averaging](https://docs.apica.io/data-management/overview-1/time-series-ai-ml/averaging.md) - [Standard Deviation(STD)](https://docs.apica.io/data-management/overview-1/time-series-ai-ml/standard-deviation-std.md) - [Data Explorer Dashboard](https://docs.apica.io/data-management/overview-1/data-explorer-dashboard.md) - [Create a Dashboard](https://docs.apica.io/data-management/overview-1/data-explorer-dashboard/create-a-dashboard.md) - [Editing Dashboard](https://docs.apica.io/data-management/overview-1/data-explorer-dashboard/editing-dashboard.md) - [Dashboard level filters](https://docs.apica.io/data-management/overview-1/data-explorer-dashboard/editing-dashboard/dashboard-level-filters.md) - [Timestamp handling](https://docs.apica.io/data-management/timestamp-handling.md): This document describes the heuristic used by Apica Ascent for managing timestamps in incoming log data - [Timestamp bookmark](https://docs.apica.io/data-management/timestamp-handling/timestamp-bookmark.md) - [Large log/events/metrics/traces](https://docs.apica.io/data-management/large-log-events-metrics-traces.md): Large log/events are single events/logs that exceed 16KB in size. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.apica.io/data-management.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.