QPR ProcessAnalyzer Chart - Revision history

Ollvihe: /* Layout Settings */

2026-03-19T09:37:43Z

Layout Settings

← Older revision		Revision as of 09:37, 19 March 2026
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	* '''Border width''': Border width of the chart in pixels. When the width is zero, border is not visible.		* '''Border width''': Border width of the chart in pixels. When the width is zero, border is not visible.
	* '''Border corner roundness''': Border corner roundness in pixels. Zero means sharp corners.		* '''Border corner roundness''': Border corner roundness in pixels. Zero means sharp corners.
	* '''Color palette''': Colors for chart series come from the color palette. When in the static series mode, colors for each y-axis can be overridden in the measure settings. Like the background, the palette colors can also contain transparency. The colors in the color palette can be reordered by using the mouse to drag and drop them into your preferred sequence. ~~The~~ color palette can be [[PA_Configuration_database_table#:~:text=DefaultColorPalette\|configured globally in the environment]].		* '''Color palette''': Colors for chart series come from the color palette. When in the static series mode, colors for each y-axis can be overridden in the measure settings. Like the background, the palette colors can also contain transparency. The colors in the color palette can be reordered by using the mouse to drag and drop them into your preferred sequence. Note that the default color palette can be [[PA_Configuration_database_table#:~:text=DefaultColorPalette\|configured globally for the environment]].

	== Filtering Settings ==		== Filtering Settings ==

Ollvihe: /* Layout Settings */

2026-03-19T09:37:00Z

Layout Settings

← Older revision		Revision as of 09:37, 19 March 2026
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	* '''Border width''': Border width of the chart in pixels. When the width is zero, border is not visible.		* '''Border width''': Border width of the chart in pixels. When the width is zero, border is not visible.
	* '''Border corner roundness''': Border corner roundness in pixels. Zero means sharp corners.		* '''Border corner roundness''': Border corner roundness in pixels. Zero means sharp corners.
	* '''Color palette''': Colors for chart series come from the color palette. When in the static series mode, colors for each y-axis can be overridden in the measure settings. Like the background, the palette colors can also contain transparency. The colors in the color palette can be reordered by using the mouse to drag and drop them into your preferred sequence. The color palette can be [[PA_Configuration_database_table#:~:text=~~DefaultColorPaletteconfigured~~ globally in the environment\|]].		* '''Color palette''': Colors for chart series come from the color palette. When in the static series mode, colors for each y-axis can be overridden in the measure settings. Like the background, the palette colors can also contain transparency. The colors in the color palette can be reordered by using the mouse to drag and drop them into your preferred sequence. The color palette can be [[PA_Configuration_database_table#:~:text=DefaultColorPalette\|configured globally in the environment]].

	== Filtering Settings ==		== Filtering Settings ==

Ollvihe: /* Layout Settings */

2026-03-19T09:36:48Z

Layout Settings

← Older revision		Revision as of 09:36, 19 March 2026
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	* '''Border width''': Border width of the chart in pixels. When the width is zero, border is not visible.		* '''Border width''': Border width of the chart in pixels. When the width is zero, border is not visible.
	* '''Border corner roundness''': Border corner roundness in pixels. Zero means sharp corners.		* '''Border corner roundness''': Border corner roundness in pixels. Zero means sharp corners.
	* '''Color palette''': Colors for chart series come from the color palette. When in the static series mode, colors for each y-axis can be overridden in the ~~chart~~ settings. Like the background, the palette colors can also contain transparency. The colors in the color palette can be reordered by using the mouse to drag and drop them into your preferred sequence.		* '''Color palette''': Colors for chart series come from the color palette. When in the static series mode, colors for each y-axis can be overridden in the measure settings. Like the background, the palette colors can also contain transparency. The colors in the color palette can be reordered by using the mouse to drag and drop them into your preferred sequence. The color palette can be [[PA_Configuration_database_table#:~:text=DefaultColorPaletteconfigured globally in the environment\|]].

	== Filtering Settings ==		== Filtering Settings ==

Ollvihe: /* Available Visualizations */

2026-01-22T18:09:21Z

Available Visualizations

← Older revision		Revision as of 18:09, 22 January 2026
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	=== Available Visualizations ===		=== Available Visualizations ===
	Chart provides variety of visualizations:		Chart provides variety of visualizations:
	* '''[[~~QPR ProcessAnalyzer Graphs~~\|Graph]]''': For example, bar chart, column chart, area chart, donut chart belongs to these kind of visualizations.		* '''[[QPR_ProcessAnalyzer_Graph_Charts\|Graph]]''': For example, bar chart, column chart, area chart, donut chart belongs to these kind of visualizations.
	* '''[[QPR ProcessAnalyzer Table\|Table]]''': The table shows the data in a similar form that it is returned from the server, and thus the table is useful when defining dimensions and measures. In the table, dimensions are first starting from the left and then there are measures. Filters can be created from the table by clicking dimensions/columns (it's not possible to create filter by clicking measures). Also when creating a column filter to the table (which only filters the data in the table), a process mining filter is automatically suggested which can be accepted or ignored. Columns widths can also be changed, and tables are able to remember the adjusted widths.		* '''[[QPR ProcessAnalyzer Table\|Table]]''': The table shows the data in a similar form that it is returned from the server, and thus the table is useful when defining dimensions and measures. In the table, dimensions are first starting from the left and then there are measures. Filters can be created from the table by clicking dimensions/columns (it's not possible to create filter by clicking measures). Also when creating a column filter to the table (which only filters the data in the table), a process mining filter is automatically suggested which can be accepted or ignored. Columns widths can also be changed, and tables are able to remember the adjusted widths.
	* '''[[QPR ProcessAnalyzer Pivot Table\|Pivot Table]]''': In the pivot table, the first dimension is visualized as rows and the second dimensions is visualized as columns. Measures are as cell values of the pivot table. In addition to the usual table, the pivot table provides changing number of columns depending how many unique values there are in the second dimension.		* '''[[QPR ProcessAnalyzer Pivot Table\|Pivot Table]]''': In the pivot table, the first dimension is visualized as rows and the second dimensions is visualized as columns. Measures are as cell values of the pivot table. In addition to the usual table, the pivot table provides changing number of columns depending how many unique values there are in the second dimension.

Ollvihe: /* Visual Settings */

2026-01-22T18:09:10Z

Visual Settings

← Older revision		Revision as of 18:09, 22 January 2026
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	* '''Description''': You can add a description to a chart, which users can access by clicking the info button in the chart's top right corner. The info button appears only when a description has been defined for the chart. This description can be used to provide additional insights into the chart and the KPIs it visualizes. The description field supports multiple lines and allows for Markdown syntax (https://www.markdownguide.org/basic-syntax) and basic HTML formatting (including tags like b, i, u, h1, and h2). For example bolding, italic, underline, headings, lists and links can be added. See examples how to use the Markdown syntax from Snowflake presets. The dialog containing the description can be moved and resized, and users can continue to interact with the dashboard even while the dialog is open.		* '''Description''': You can add a description to a chart, which users can access by clicking the info button in the chart's top right corner. The info button appears only when a description has been defined for the chart. This description can be used to provide additional insights into the chart and the KPIs it visualizes. The description field supports multiple lines and allows for Markdown syntax (https://www.markdownguide.org/basic-syntax) and basic HTML formatting (including tags like b, i, u, h1, and h2). For example bolding, italic, underline, headings, lists and links can be added. See examples how to use the Markdown syntax from Snowflake presets. The dialog containing the description can be moved and resized, and users can continue to interact with the dashboard even while the dialog is open.
	* '''[[Chart_On-screen_Settings\|On-screen Settings]]'''		* '''[[Chart_On-screen_Settings\|On-screen Settings]]'''
	* '''Custom Layout''': Using the Custom Layout, advanced visual settings for the chart and table can be defined using JSON format. Settings defined here override the default chart and table settings. Overriding is done for individual properties, so only the customized settings need to be specified. See examples for [[~~QPR ProcessAnalyzer Graphs~~#~~Customization%20Examples~~\|customizing charts]]. Note that when changing the visualization, the custom layout settings are reset, because the settings are specific to a visualization type.		* '''Custom Layout''': Using the Custom Layout, advanced visual settings for the chart and table can be defined using JSON format. Settings defined here override the default chart and table settings. Overriding is done for individual properties, so only the customized settings need to be specified. See examples for [[QPR_ProcessAnalyzer_Graph_Charts#Customization_Examples\|customizing charts]]. Note that when changing the visualization, the custom layout settings are reset, because the settings are specific to a visualization type.
	* '''Export''': Tables, pivot tables and charts can be exported into several formats available in the dropdown list.		* '''Export''': Tables, pivot tables and charts can be exported into several formats available in the dropdown list.

TeeHiet: TK-57056

2026-01-14T11:17:43Z

TK-57056

← Older revision		Revision as of 11:17, 14 January 2026
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	* '''Analyzed objects sample size''' (in-memory): Sampling randomly removes some of the items leaving only the sample size of items left to the analyzed objects. If sample size is not defined, sampling is not used. The purpose of sampling is to improve performance, as there will be less items in the dimension and measure calculation. The intention is that the calculation from the sampled dataset would provide close enough results in statistically high enough probability. Sampling cannot be used in some calculations, because it affects the calculation results.		* '''Analyzed objects sample size''' (in-memory): Sampling randomly removes some of the items leaving only the sample size of items left to the analyzed objects. If sample size is not defined, sampling is not used. The purpose of sampling is to improve performance, as there will be less items in the dimension and measure calculation. The intention is that the calculation from the sampled dataset would provide close enough results in statistically high enough probability. Sampling cannot be used in some calculations, because it affects the calculation results.
	* '''Model''': Select a process mining model that is shown by this chart. When selecting ''<used by dashboard>'', the model that is currently selected for the dashboard in the header, is used by the chart. This setting allows to create dashboards, where the dashboard at the same time fetches and visualizes data from different models.		* '''Model''': Select a process mining model that is shown by this chart. When selecting ''<used by dashboard>'', the model that is currently selected for the dashboard in the header, is used by the chart. This setting allows to create dashboards, where the dashboard at the same time fetches and visualizes data from different models.
	* '''Base object-type ~~(object-centric perspective)~~''': When the object-centric model is converted into a case-centric eventlog, object of this type will be cases. All events in the object-centric eventlog are projected into these cases. This setting is only shown when an object-centric model is selected for the chart		* '''Base object-type''': When the object-centric model is converted into a case-centric eventlog, object of this type will be cases. All events in the object-centric eventlog are projected into these cases. This setting is only shown when an object-centric model is selected for the chart
	* '''Object relation steps ~~(object-centric perspective)~~''': Specifies how many object-object relations will be traversed in order to find events connected to the base objects. Value zero means that only those events are returned that are directly connected to the base objects. This setting is only shown when an object-centric model is selected for the chart.		* '''Object relation steps''': Specifies how many object-object relations will be traversed in order to find events connected to the base objects. Value zero means that only those events are returned that are directly connected to the base objects. This setting is only shown when an object-centric model is selected for the chart.
	* '''Show event types ~~(object-centric perspective)~~''': List of event type names which are included into the object-centric perspective eventlog. If no events are selected, all events will be included, but their event attributes are not included to the eventlog. This setting is only shown when an object-centric model is selected for the chart.		* '''Show event types''': List of event type names which are included into the object-centric perspective eventlog. If no events are selected, all events will be included, but their event attributes are not included to the eventlog. This setting is only shown when an object-centric model is selected for the chart.
	* '''Event type mapping''': Select the event attribute used as the event type for this chart. The event type selection affects the process flow and for example variations and flows. When the chart specific event type mapping is defined, the chart works similarly as if the same event type mapping had been selected in the model level. When ''<model default>'' is selected, the event type mapping defined for the model is used. Note that filters don't contain the event type mapping information, so they use the mapping that has been defined for the chart, and thus charts with different event type mapping don't work together with filtering (usually all cases appear to be filtered out due to the mismatch). This setting is available only in the Snowflake chart and Snowflake flowchart.		* '''Event type mapping''': Select the event attribute used as the event type for this chart. The event type selection affects the process flow and for example variations and flows. When the chart specific event type mapping is defined, the chart works similarly as if the same event type mapping had been selected in the model level. When ''<model default>'' is selected, the event type mapping defined for the model is used. Note that filters don't contain the event type mapping information, so they use the mapping that has been defined for the chart, and thus charts with different event type mapping don't work together with filtering (usually all cases appear to be filtered out due to the mismatch). This setting is available only in the Snowflake chart and Snowflake flowchart.

TeeHiet: TK-61134

2025-09-22T09:18:20Z

TK-61134

← Older revision		Revision as of 09:18, 22 September 2025
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	: When there are event level filters in use, the order of filter rules may affect the result because filter rules are applied to the resulting event log of the previous filter rule calculation. In certain use cases, it's desired to apply the chart filters before the dashboard filters.		: When there are event level filters in use, the order of filter rules may affect the result because filter rules are applied to the resulting event log of the previous filter rule calculation. In certain use cases, it's desired to apply the chart filters before the dashboard filters.
	* '''Allow Creating Filters''': When checked, filters can be created based on selected items in the chart. When unchecked, no filters are created when clicking the chart. For Snowflake models, chart's event filter rules are embedded to the created filter rule~~, whereas for~~ the in-memory models, the chart's event filter rules are ignored from the created filter rules. In addition, for Snowflake models, all measure/dimension/column filter rules are embedded to the created filter rule.		* '''Allow Creating Filters''': When checked, filters can be created based on selected items in the chart. When unchecked, no filters are created when clicking the chart. For Snowflake models, the chart's event filter rules are embedded to the created filter rule. For the in-memory models, the chart's event filter rules are ignored from the created filter rules. In addition, for Snowflake models, all measure/dimension/column filter rules are embedded to the created filter rule.
	** '''Default filtering''': '''Filter cases''' / '''Filter events''': Choose whether cases or events filtering is selected by default when making selections in the chart. Regardless of this setting, user can change the filtering type between cases and events before confirming the filter. Note that for some selections, the events filtering is not possible, so cases filter is created regardless of this setting.		** '''Default filtering''': '''Filter cases''' / '''Filter events''': Choose whether cases or events filtering is selected by default when making selections in the chart. Regardless of this setting, user can change the filtering type between cases and events before confirming the filter. Note that for some selections, the events filtering is not possible, so cases filter is created regardless of this setting.
	** '''Apply with Chart Case Filters''': When checked, when selecting datapoints in the chart, the chart's case filter rules are included to the created filter as separate filter rules (located before the filter rule corresponding to the selected datapoints).		** '''Apply with Chart Case Filters''': When checked, when selecting datapoints in the chart, the chart's case filter rules are included to the created filter as separate filter rules (located before the filter rule corresponding to the selected datapoints).

TeeHiet: TK-61134

2025-09-22T09:08:34Z

TK-61134

← Older revision		Revision as of 09:08, 22 September 2025
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	: When there are event level filters in use, the order of filter rules may affect the result because filter rules are applied to the resulting event log of the previous filter rule calculation. In certain use cases, it's desired to apply the chart filters before the dashboard filters.		: When there are event level filters in use, the order of filter rules may affect the result because filter rules are applied to the resulting event log of the previous filter rule calculation. In certain use cases, it's desired to apply the chart filters before the dashboard filters.
	* '''Allow Creating Filters''': When checked, filters can be created based on selected items in the chart. When unchecked, no filters are created when clicking the chart.		* '''Allow Creating Filters''': When checked, filters can be created based on selected items in the chart. When unchecked, no filters are created when clicking the chart. For Snowflake models, chart's event filter rules are embedded to the created filter rule, whereas for the in-memory models, the chart's event filter rules are ignored from the created filter rules. In addition, for Snowflake models, all measure/dimension/column filter rules are embedded to the created filter rule.
	* '''Default filtering''': '''Filter cases''' / '''Filter events''': Choose whether cases or events filtering is selected by default when making selections in the chart. Regardless of this setting, user can change the filtering type between cases and events before confirming the filter. Note that for some selections, the events filtering is not possible, so cases filter is created regardless of this setting.		** '''Default filtering''': '''Filter cases''' / '''Filter events''': Choose whether cases or events filtering is selected by default when making selections in the chart. Regardless of this setting, user can change the filtering type between cases and events before confirming the filter. Note that for some selections, the events filtering is not possible, so cases filter is created regardless of this setting.
	* '''Apply with Chart Filters''': When checked, chart's case filter rules are included to the ~~dashboard level~~ filter ~~selection (and eventually to the filter), when selecting items in the chart. Note that event~~ filter rules (~~e.g., events by type and events by attribute) are never included. When this selection is unchecked, any chart~~ filter ~~rules are not added~~ to the ~~dashboard level filter when selecting items~~.		** '''Apply with Chart Case Filters''': When checked, when selecting datapoints in the chart, the chart's case filter rules are included to the created filter as separate filter rules (located before the filter rule corresponding to the selected datapoints).
	* '''Update Filter During Selection''': When checked, other charts are filtered during selecting items in this chart, enabling to preview filtering results in other charts before confirming the selection. When unchecked, a filter is created only when the selection is confirmed, improving smoothness of usage in large models.		** '''Update Filter During Selection''': When checked, other charts are filtered during selecting items in this chart, enabling to preview filtering results in other charts before confirming the selection. When unchecked, a filter is created only when the selection is confirmed, improving smoothness of usage in large models.
	* '''On-screen Settings Follow Flow Selection''': When checked, selecting flows (e.g. in the flowchart) changes accordingly the start and end event types that are as on-screen settings. Note that the start and end event types need to be as on-screen settings, for the automatic fill in to work. When unchecked, the automatic fill in is disabled.		* '''On-screen Settings Follow Flow Selection''': When checked, selecting flows (e.g. in the flowchart) changes accordingly the start and end event types that are as on-screen settings. Note that the start and end event types need to be as on-screen settings, for the automatic fill in to work. When unchecked, the automatic fill in is disabled.
	* '''Chart Filter''': Button to add filter rules that affect this chart only. Filter rules can be edited by clicking them and removed from the recycle bin icon. The chart or dashboard component only shows cases and events that match with the defined filter rules. If there are several filter rules defined, all of the individual rules must match.		* '''Chart Filter''': Button to add filter rules that affect this chart only. Filter rules can be edited by clicking them and removed from the recycle bin icon. The chart or dashboard component only shows cases and events that match with the defined filter rules. If there are several filter rules defined, all of the individual rules must match.

Ollvihe: /* Analyzed Data */

2025-08-29T09:21:35Z

Analyzed Data

Ollvihe: /* Analyzed Data */

2025-08-29T09:20:45Z

Analyzed Data

← Older revision		Revision as of 09:20, 29 August 2025
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	* '''Cases sample size''' (Snowflake): Defines how many cases are randomly selected for the analysis. Purpose of sampling is to improve performance because instead of entire dataset only a subset is used in the calculation. Depends on the analysis whether sampling can be used, for example portions (e.g., percentage of cases) are similar in a representative sample, but volumes in a sample are incorrect (e.g., number of cases). Sampling is applied after filtering has been performed (i.e., sampling is applied for the filtered eventlog). For Snowflake, the sampling setting only samples cases and is only available when performing calculations to models (in-memory samples any analyzed objects).		* '''Cases sample size''' (Snowflake): Defines how many cases are randomly selected for the analysis. Purpose of sampling is to improve performance because instead of entire dataset only a subset is used in the calculation. Depends on the analysis whether sampling can be used, for example portions (e.g., percentage of cases) are similar in a representative sample, but volumes in a sample are incorrect (e.g., number of cases). Sampling is applied after filtering has been performed (i.e., sampling is applied for the filtered eventlog). For Snowflake, the sampling setting only samples cases and is only available when performing calculations to models (in-memory samples any analyzed objects).
	* '''Result filtering expression''' (Snowflake): Defines an expression that filters the query result rows, i.e. removes certain rows based on the criteria in the expression. Column names that can be used in the result filtering expression are defined using [[Measure,_Dimension_and_Column_Settings#Advanced_settings\|measure and column variables]]. The result filtering expression is evaluated before the Maximum rows setting is evaluated, so that the maximum rows limitation is respected.		* '''Result filtering expression''' (Snowflake): Defines an expression that filters the query result rows, i.e. removes certain rows based on the criteria in the expression. Column names that can be used in the result filtering expression are defined using [[Measure,_Dimension_and_Column_Settings#Advanced_settings\|measure and column variables]]. The result filtering expression is evaluated before the Maximum rows setting is evaluated, so that the maximum rows limitation is respected.
	:Example: Show ~~only~~ rows where column with variable "count" value is greater than 100:		:Example: Show rows where column with variable "count" value is greater than 100:
	:<pre>Column("count") > 100</pre>		:<pre>Column("count") > 100</pre>
	:Example: Show ~~only~~ rows where column with variable "Cost 1" value is less than "Cost 2":		:Example: Show rows where column with variable "Cost 1" value is less than "Cost 2":
	:<pre>Column("~~Cost~~ 1") < Column("~~Cost~~ 2")</pre>		:<pre>Column("cost 1") < Column("cost 2")</pre>
	:Example: Show ~~only~~ rows where both of the previous conditions apply:		:Example: Show rows where both of the previous conditions apply:
	:<pre>Column("count") > 100 && Column("~~Cost~~ 1") < Column("~~Cost~~ 2")</pre>		:<pre>Column("count") > 100 && Column("cost 1") < Column("cost 2")</pre>
			:Example: Show rows where column with variable "Region" has the listed values:
			:<pre>In(Column("Region"), "Dallas", "New York", "Los Angeles")</pre>
			:Example: Show only rows where column with variable "Region" has the listed values:
			:<pre>In(Column("Region"), "Dallas", "New York", "Los Angeles")</pre>
			:Example: Show rows where column with variable "start" has a date value in year 2025:
			:<pre>Year(Column("start")) == 2025</pre>
	* '''Analyzed objects sample size''' (in-memory): Sampling randomly removes some of the items leaving only the sample size of items left to the analyzed objects. If sample size is not defined, sampling is not used. The purpose of sampling is to improve performance, as there will be less items in the dimension and measure calculation. The intention is that the calculation from the sampled dataset would provide close enough results in statistically high enough probability. Sampling cannot be used in some calculations, because it affects the calculation results.		* '''Analyzed objects sample size''' (in-memory): Sampling randomly removes some of the items leaving only the sample size of items left to the analyzed objects. If sample size is not defined, sampling is not used. The purpose of sampling is to improve performance, as there will be less items in the dimension and measure calculation. The intention is that the calculation from the sampled dataset would provide close enough results in statistically high enough probability. Sampling cannot be used in some calculations, because it affects the calculation results.
	* '''Model''': Select a process mining model that is shown by this chart. When selecting ''<used by dashboard>'', the model that is currently selected for the dashboard in the header, is used by the chart. This setting allows to create dashboards, where the dashboard at the same time fetches and visualizes data from different models.		* '''Model''': Select a process mining model that is shown by this chart. When selecting ''<used by dashboard>'', the model that is currently selected for the dashboard in the header, is used by the chart. This setting allows to create dashboards, where the dashboard at the same time fetches and visualizes data from different models.

← Older revision		Revision as of 09:21, 29 August 2025
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	* '''Cases sample size''' (Snowflake): Defines how many cases are randomly selected for the analysis. Purpose of sampling is to improve performance because instead of entire dataset only a subset is used in the calculation. Depends on the analysis whether sampling can be used, for example portions (e.g., percentage of cases) are similar in a representative sample, but volumes in a sample are incorrect (e.g., number of cases). Sampling is applied after filtering has been performed (i.e., sampling is applied for the filtered eventlog). For Snowflake, the sampling setting only samples cases and is only available when performing calculations to models (in-memory samples any analyzed objects).		* '''Cases sample size''' (Snowflake): Defines how many cases are randomly selected for the analysis. Purpose of sampling is to improve performance because instead of entire dataset only a subset is used in the calculation. Depends on the analysis whether sampling can be used, for example portions (e.g., percentage of cases) are similar in a representative sample, but volumes in a sample are incorrect (e.g., number of cases). Sampling is applied after filtering has been performed (i.e., sampling is applied for the filtered eventlog). For Snowflake, the sampling setting only samples cases and is only available when performing calculations to models (in-memory samples any analyzed objects).
	* '''Result filtering expression''' (Snowflake): Defines an expression that filters the query result rows, i.e. removes certain rows based on the criteria in the expression. Column names that can be used in the result filtering expression are defined using [[Measure,_Dimension_and_Column_Settings#Advanced_settings\|measure and column variables]]. The result filtering expression is evaluated before the Maximum rows setting is evaluated, so that the maximum rows limitation is respected.		* '''Result filtering expression''' (Snowflake): Defines an expression that filters the query result rows, i.e. removes certain rows based on the criteria in the expression. Column names that can be used in the result filtering expression are defined using [[Measure,_Dimension_and_Column_Settings#Advanced_settings\|measure and column variables]]. The result filtering expression is evaluated before the Maximum rows setting is evaluated, so that the maximum rows limitation is respected.
	:Example: Show rows where column with variable "count" ~~value~~ is greater than 100:		:Example: Show rows where column with variable "count" is greater than 100:
	:<pre>Column("count") > 100</pre>		:<pre>Column("count") > 100</pre>
	:Example: Show rows where column with variable "Cost 1" ~~value~~ is less than "Cost 2":		:Example: Show rows where column with variable "Cost 1" is less than "Cost 2":
	:<pre>Column("cost 1") < Column("cost 2")</pre>		:<pre>Column("cost 1") < Column("cost 2")</pre>
	:Example: Show rows where both of the previous conditions apply:		:Example: Show rows where both of the previous conditions apply:
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	:Example: Show rows where column with variable "Region" has the listed values:		:Example: Show rows where column with variable "Region" has the listed values:
	:<pre>In(Column("Region"), "Dallas", "New York", "Los Angeles")</pre>		:<pre>In(Column("Region"), "Dallas", "New York", "Los Angeles")</pre>
	~~:Example: Show only rows where column with variable "Region" has the listed values:~~		:Example: Show rows where column with variable "start" has a date in year 2025:
	~~:<pre>In(Column("Region"), "Dallas", "New York", "Los Angeles")</pre>~~
	:Example: Show rows where column with variable "start" has a date ~~value~~ in year 2025:
	:<pre>Year(Column("start")) == 2025</pre>		:<pre>Year(Column("start")) == 2025</pre>
	* '''Analyzed objects sample size''' (in-memory): Sampling randomly removes some of the items leaving only the sample size of items left to the analyzed objects. If sample size is not defined, sampling is not used. The purpose of sampling is to improve performance, as there will be less items in the dimension and measure calculation. The intention is that the calculation from the sampled dataset would provide close enough results in statistically high enough probability. Sampling cannot be used in some calculations, because it affects the calculation results.		* '''Analyzed objects sample size''' (in-memory): Sampling randomly removes some of the items leaving only the sample size of items left to the analyzed objects. If sample size is not defined, sampling is not used. The purpose of sampling is to improve performance, as there will be less items in the dimension and measure calculation. The intention is that the calculation from the sampled dataset would provide close enough results in statistically high enough probability. Sampling cannot be used in some calculations, because it affects the calculation results.