Snowflake Chart

In Big Data Chart, calculations in the backend are performed in the datasource where the eventlog data is stored, whereas the regular chart uses the in-memory processing. In Big Data Chart, depending on the [[QPR_ProcessAnalyzer_Project_Workspace#Models|model type], processing is done in Snowflake (for models using Snowflake datatables) or in SQL Server (for models using Local datatables).

Big Data Chart can be added to dashboard by selecting the second item from the tool palette (labelled Big Data Chart).

Differences to in-memory chart

Visualization settings are the same between the Big Data Chart and in-memory chart. On the other hand, data selection settings, and measures and dimensions work differently. Differences are as follows:

• There are different set of analyzed objects, measures and dimensions available.
• In Big Data Chart, filtering cases and events can be done also for each measure and dimension separately. This allows to versatilely build KPI's without going to the custom expressions.
• In Big Data Chart, available measures and dimensions are equal. They are separated only by the additional aggregation selection that measures have. Due to the similarity in Big Data Chart, measures can be moved to dimensions and vice versa by clicking the Move to dimensions and Move to measures icon buttons.
• Custom expressions are written as SQL expressions which differs from the eventlog objects available in the in-memory charts. Note also that the measure expression in the Big Data Chart doesn't include the aggregation logic, and thus the custom measure and dimension expressions are equal.
• Big data chart cannot be used for model using ODBC or expression datasources.
• The Any datatype is not supported by the Big Data Chart for case and event attributes. Thus, when importing data, the specific datatypes need to be set for each column, for case and event attributes get correct datatypes.

Following functionalities supported by the in-memory are not available in the Big Data Chart: Presets, Group rows exceeding maximum, Analyzed objects sample size, Find root causes, and Business calendar. In addition, the following measure/dimension settings are not available: Round to decimals, Calculate measure for, Variable name, Custom aggregation expression, and Adjustment expression.

When to use Big Data Chart

Snowflake powered calculation will enable practically unlimited scaling when the amount of data and users increase. The Big Data Chart needs to be used in dashboards when using Snowflake models.

In addition, Big Data Chart can be used for models using local datatables. In that case, processing is performed in SQL Server which is not optimal for analytics queries from performance viewpoint. There are still use cases when the Big Data Chart is a suitable option for model using local datatables:

• Eventlogs are filtered heavily so that the number of remaining cases and events are low (usually maximum of some thousands). Then processing may be done in the SQL Server without using the in-memory processing (which will require less memory)
• If the model is not currently loaded in the memory, the fastest method is to use the Big data chart comparing to the in-memory chart, when also calculating the required time to load the model in-memory.

Filtering

The Big Data Chart supports filtering similar to the in-memory chart, i.e., visualizations can be clicked to create filters for the shown data. Big Data Chart does not support expression based filter rules and thus there are more dimensions where filtering is not possible.

The filter rules are same for the Big Data and in-memory charts, and thus the same dashboard can contain both types of chart components, and filtering between them works. Note that when an expression based filter rule is created from the in-memory chart, the Big Data Chart cannot be shown as the filter rule cannot be calculated there.