Data Filters for Data Analytics

Imagine the different views you’d like to see of your data within a Dataset for business intelligence. Maybe you want to see sales orders for the United States, or Canadian Provinces, or maybe all of Europe.

Informer Data Filters simplify your data analytics workload by enabling you to create these different views when designing your Dataset and Visuals.

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How do Data Filters Support Data Analysis?

Data Filters enable you to filter the data within your Informer 5 Dataset into subsets of information to support your business intelligence requirements. Using Data Filters to narrow down your data views can provide different views of the same data without the need to create multiple Datasets. For example, given a Dataset of Enrolled Students from the past 10 years, apply a Data Filter to narrow the list to only those students from the previous fall semester who have declared English as their major, or a Data Filter to see the students who enrolled in classes within the last 30 days.

Creating Data Filters

To narrow the scope of your data, just start typing a field name property in the Dataset’s auto complete Filter Bar, (for example: Product Name, Employee Last Name, Country, etc.). After selecting the desired field from the drop-down list, the associated Data Filters will intelligently populate in the Navigation Panel. Then select the values you are interested in for data analytics from the Data Filter check boxes. You’ll see the data in the Dataset update dynamically as you create a filter without having to refresh the browser. It’s that easy!

Filter Chips consolidate your Filter criteria and are visible on your Filter Bar. See Figure 1. You can further filter your data by merging and saving combinations of Filter Chips into a Saved Filter. The narrowed scope will consist of the data that matches all your Filter Chips.

Figure 1: Multiple Filter Chips
Using multiple datasource filters for data analytics

 

Filtering is a powerful tool:

  • Complex filters can be created based on the properties in your Dataset mapping
  • Filter criteria can be applied to each property
  • And, logic can be applied to how each property is processed.

You can create complex filters for your data analysis that include a mixture of “ALL”, “ANY” and “NONE” logic. You can also Filter Datasets using: AND, OR, NOT with multiple Filter Chips.

 

Match All: These filter chips are displayed in green to reflect the “ALL” condition. In the example below, the rows that meet the filter criteria must contain “janet” and “NM” and “gnocchi”.

Matching all filter criteria for data analysis

 

Match Any: These filter chips are displayed in orange to reflect the “ANY” condition. In the example below, the rows that meet the filter criteria must contain either “janet” or “NM” or “gnocchi”.

Matching any filter criteria for data analytics

 

Match None: These filter chips are displayed in dark orange to reflect the “NONE” condition. In the example below, the rows that meet the filter criteria cannot contain either “janet” nor “NM” nor “gnocchi”.

Matching none filter criteria for business intelligence

 

Once you create a Saved Filter, you can apply it across different Discover visuals and Reports to pivot on data within the Dataset as shown in Figure 2.

Figure 2: List of Saved Data Filters
Applying saved datasource filters for business intelligence

Using Data Filters for Better Data Visualization

Saved Data Filters can also be applied to your data visualization Visuals and Dashboards that reference the Dataset. This alleviates the need to make multiple Visuals with slight variations. Figure 3 depicts a Visual with a Saved Filter applied.

Figure 3: Example of applying a Saved Filter on the same data visualization that would otherwise show data from the entire Dataset.

Data filters for better data visualization

Configuring Data Filters for Business Intelligence

You can quickly and easily narrow the scope of your Dataset based on any field data type or a combination of them in Informer 5 (for example: Text, Integer Number, Date/Timestamp). Properties are grouped by data type:

  • Date Filters enable you to select values from any of the date components (month, day, year, week, and quarter), or filter on dates relative to the current date (past, next n days, weeks, months, years).
  • Numeric values filter by selecting a range of set values.
  • Text values present a distinct list of values from which to choose. You can optionally include or exclude checked values.
  • Location fields (those based on latitude-longitude pairs) filter based on proximity to your current location.

You can select from displayed criteria options when you hover over the property name. In this example, the mouse is hovering over the Text property “Product Name”.

Narrow datasource with select criteria for data analytics

Filtering Datasets with a Timestamp (Date/Time) Criteria

The options for date and/or time filter criteria include:

  • Distinct Values: must match any of the selected values
  • Date Range: must be within a min/max range
  • Date Relative to Now: within a past or future time range
  • Date Keyword: on/before/after ranges for keywords such as TODAY or YEAR_END
  • Is Empty: the property is empty or NULL
  • Is Not Empty: the property contains a value

 

Filtering data using date and time criteria for data analysis

Date Range – The Date Range option creates a filter that will restrict data based on a range of dates. Figure 4 A and B show an example of configuring a date range Data Filter.

Figure 4A
Filtering by date range for data analytics

 

Figure 4B
Restrict data using date range for business intelligence

 

Date Relative to Now – The Date Relative to Now option creates a filter that defines dates in a past or future range. You can select between Next and Past, and between days, weeks, months or years.
Filter dates relative to now for data analysis

 

Date Keyword – The Date Keyword option creates a filter that creates relative dates based on keyword. The help icon, “?” provides detailed information on the available options.
Create dates based on a keyword for data analysis

Options for date keywords for data analytics

 

Filtering Datasets with Numeric Value Criteria

Number filtering is subdivided into Decimal and Integer numbers. See below:

  • Distinct Values: must match any of the selected values
  • Number ranges: must be within the selected distinct value ranges
  • Number range slider: must be within the selected value range (min and max)
  • Number value slider: must be within the selected value range
  • Enter Value: Any of one or more values
  • Is Empty: the property is empty or NULL
  • Is Not Empty: the property contains a value

 

Filtering datasets with numeric value criteria for data analytics

 

The Number Ranges option facilitates creating a filter by selecting discrete ranges of numbers. For example:

Discrete number range filter for data analysis

 

You can restrict the range of data for your data analysis by typing a numeric value into either the Min or Max fields. Use the up or down arrows to increase or decrease the value, or click and hold on the slider to drag to the desired value.

Restrict filter range using min and max for data analysis

 

Filtering Datasets with Text Criteria

The options for Text Filtering include:

  • Distinct Values: must match any of the selected values
  • Like: Use for partial matches
  • Enter Value: Any of one or more values
  • Is Empty: the property is empty or NULL
  • Is Not Empty: the property contains a value

 

Text criteria for filtering datasets for business intelligence

 

The Like option provides a partial match of the property by leveraging wildcard characters. Wildcard characters are:
• ‘*’ for any string of characters (or no characters)
• ‘?’ for a single character

Some examples:
• ‘*eve*’ will match ‘Steven’
• ‘*R*’ will match ‘Rio’
• ‘?/ *’ will match ‘C/ Romero’
• ‘*,*’ will match every property with a comma

 

Filtering Datasets with Location Criteria

The options for location filter criteria for data visualization include:

  • Location range: within a specified distance
  • Is Empty: the property is empty or NULL
  • Is Not Empty: the property contains a value

 

Data visualization using location criteria

 

The Location Range option creates a filter that includes data within a specified distance of the location coordinate.

Filtering a datasource on Location for data analysis

 

Filtering Datasets with Distinct Values Criteria

The Distinct Values option provides a menu of check box options listing the data values in the property. This filter can be applied to text, integer or decimal number or timestamp (date/time) data types. The number of occurrences in the dataset are also displayed.

Text Example of Distinct Values

Filtering data using distinct values for business intelligence

 

Integer Number Example of Distinct Values

Filtering using integer values for data analysis

 

Timestamp Example of Distinct Values

Filtering datasource using date values for business intelligence

 

Filtering Datasets by using ‘Is Empty’ or ‘Is Not Empty’ Criteria

The ‘Is Empty’ or ‘Is Not Empty’ filter options are toggles to filter for properties that do or do not have a value. Once either is selected, a filter chip is created showing the property name and the state.

Filtering datasources for data analytics

 

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