Advanced Analytics overview

Cloudera Data Visualization provides an extensive array of tools to support advanced analysis.

Complex data types

Cloudera Data Visualization supports native complex data type configurations, bypassing ETL workflows and avoiding unnecessary flattening at query time. Explore complex data types to leverage the powerful native SQL already optimized for complex types.

Dimension hierarchies

Cloudera Data Visualization provides full support for dimensional hierarchy modelling at dataset level, enabling smooth natural transition between granularity levels of data. For more information, see Dimension hierarchies.

Segments

Segments can be very powerful in data visualization, and form the foundation of cohort analysis and row-level access restrictions. For more information, see Segments.

Events

Identifying and managing events within your time-stamped data enables you to measure outcomes of complex workflow scenarios. For more information, see Events.

Visuals for analytics

For advanced analysis, you can create advanced visual types, such as funnels, flows, correlation flows, and histograms. For more information, see Visuals for Analytics.

Advanced visualization techniques

Advanced visualization techniques, such as trellises, dual-axis line visuals, and dimension hierarchies free you to explore the visualized data from diverse perspectives. For more information, see Advanced Visualization Techniques.

Analytic functions

On select connection types, Cloudera Data Visualization supports several analytic functions that examine overlapping groupings of data. For more information, see Supported connections.

Derived data

You can derive data from an existing query, build computed columns for re-use, and reference results in new queries. Derived data enables you to stack sub-query analytical results.