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Preparation Details in Data Designer (BETA)

Overview

This article will walk you through the functionalities in the Preparation tab, and also focuses on how to make use of them while preparing a Dataset for Analysis.
 

In the preparation step, you can merge two different objects and create a Dataset. This document explains the functionalities in the Preparation tab, assuming that you have already created a minimum of two Datasets on two different objects. For information on how to create a Dataset, refer Create Datasets in Data Designer (BETA).


You can make use of the following functionalities, while preparing a dataset:

  1. Edit Dataset
  2. Transform 
  3. Merge
  4. Preview Dataset
  5. Delete
  6. Preview Output Dataset

To access Preparation tab in Data Designer (BETA), navigate to Administration > Analytics > Data Designer, and open an existing design you wish to edit (or) click New Design to create a new one, enter the Details and navigate to the Preparation tab. 

Edit Dataset

To edit a Dataset:

Click the pencil icon (or) click Options, and then click Edit to edit a dataset. You will be landed on the following page, where you can see Fields, Filters and Summary tabs.

Fields

You can see the following options in the Fields tab:

  1. Enter Dataset Name: In the Enter Dataset Name textbox, type In the Dataset Name, if you want to edit the Dataset Name. 
  2. Search Fields: In the Search Fields textbox, type in the Field Name you want to search for. Search operation happens on the fields available in the Dataset.
  3. Add Fields: Click Add Fields to select the required fields you want to add to the dataset, and then click Select. You can also remove fields from the dataset by deselecting them.
  4. Group By: You can select the required fields to Group By, to slice and dice the data in the dataset. Once you select a Field to Group By, all the other fields in the dataset will become aggregated.
  5. Aggregation: You can select the required aggregation type from the Aggregation dropdown list.
  6. Display Name: By default, Field Name name appears in the Display Name textbox, if required you can modify it. Display Names are shown in the Datasets/reports. 
  7. Settings: For the numeric data type fields, you can set the decimal places. Click the Settings icon to enter the decimal places you want to set.
  8. Delete: Click the Delete icon to delete a field from the dataset.
  9. Save: Click Save to save the changes made in the dataset.

Preparation.gif

Filters

To apply Filters:

  1. Navigate to the Filters tab.
  2. Click Add Filter.
  3. Select the field you want to filter on.
  4. Choose the operator and then input the data in the Value text box.
    Notes:
    • You can also Add more filters by clicking the + icon next to Value text box.
    • You can Delete a filter by clicking the x icon.
    • You can add advance filters such as (A OR B) AND C, type in your desired expression in the Advanced Logic text box.
  5. Click Save.

Filter.gif

Summary

In the Summary tab, you can view a list of all Fields (including Group By, if any) and Filters in the Dataset.

Summary.gif

Transform

Transform allows you to apply Formula Fields and Case Expressions on the fields added to the dataset.

To apply Transformation on a dataset:

Click Options on the dataset you want to apply transformation, and then click Transform. A new window with the dataset name ‘Transform’ appears, where you can see Fields, Filters and Summary tabs.

Fields

Once you apply Transformation on a dataset, you can now create Formula Fields and Case Fields upon the fields added to the transformed dataset.

Formula Fields and Case Fields in the Preparation Details of Data Designer (BETA) work as the Formula Fields and Case Fields in Bionic Rules. For information on how to create Formula Fields and Case Fields, refer to Formula Fields and Case Fields article.

All the other options in the Transform > Fields tab work as the options in the Fields > Edit Dataset and Fields > Merge.

Add Formula Field

To create a Formula Field:

  1. Click Add Formula Field.
  2. Enter the Formula Field name in the Label textbox.
  3. Select the required Data Type (String or Date or Number).
    Notes:
  • Select the data type, based on the output field you want. For example, if you want to see the output as number of days/weeks/months, then select the output data type as number.
  • Functions and Fields may differ based on the selection of the data type.
  • For Number data type, you can select the Expression Type as Function or Expression from the Expression Type dropdown list, based on your business requirements.
  1. Select the required Function of your choice, and then select/enter the Values and/or Fields as per your requirement.
  2. Click Save to save the formula field.
  3. Click Save to save the Transform dataset.

Add Formula.gif

You can preview the records of the newly created formula fields, by clicking Preview on the Transform dataset.

Preview Formula FIelds.gif

Add Case Field

You can use the Case Expression formula field to categorize data, based on specific set of requirements. You can use this Formula function to create an output Field. This output field has values for the records that match your specific set of requirements. 

Case Fields in the Preparation Details of Data Designer (BETA) work as the Case Fields in Bionic Rules. For information on how to create Case Fields, refer to the Case Fields article.

To create a Case Field: 

  1. Click Add Formula Field.
  2. Label: Enter the Formula Field name in the Label textbox.
  3. Select the required Data Type (Number/String/Boolean). The options present in the Case Output depends on the Output data type.
    Note: If you select Number in the Data Type, select the number of decimal places upto which the output must be displayed, for floating point numbers.
  4. Case: Case consists of the Criteria(s). You can add multiple criteria by clicking +
  5. Criteria. The various fields present in a Criteria are:   
    1. Field: Select the field on which the Criteria must be applied. All the fields included in the Dataset are displayed here.
    2. Operator: Select an Operator to be applied on the field. The operators are displayed based on the field selected.
    3. Matching Criteria: Select the matching criteria which must be satisfied, for this criteria to be successful. You can either select:
      1. Value: Enter a value which must match the field value.
      2. Field: Select a field whose value must match the value of the field, selected in the first field.

Case Exp1.gif

  1. Advanced Logic: When you have multiple criteria, select the logical operator to be applied between those criteria(s). By Default, the AND logic is applied.
  2. Then: If all the criteria(s) are matched, the action specified in this field is executed. The options available in this field depend on the value selected in the Output Data Type field.
  3. Default: This field represents the default case. There is no criteria for this case. It only has action. If all the cases fail, this case is executed.
  4. Click Save to save the case expression.
  5. Click Save to Transform dataset.

Case Exp2.gif

Execution of the Case Expression in detail:

  1. Execution of the Case Expression begins with the evaluation of the first case on a record. If all the criteria in this case are satisfied by the record, the action associated with this case is executed. The execution of Case expression halts here for this record and none of the other cases are evaluated.
  2. However, if the first case is not satisfied, the system evaluates the second case on the same record, and so on. If none of the available cases are satisfied by the record, the default case is executed.

Filters

Filters in Transform work as Filters in Edit Dataset. For more details, refer to the Filters section.

Summary

Summary details in Transform are same as Summary details in Edit Dataset. For more details, refer to the Summary section.

Merge

You can merge datasets in two possible ways:

  1. Click Options on the dataset you want to merge, and then click Merge and select the required dataset. (OR)
  2. Drag and drop the first dataset on to the second dataset.

Once you merge the datasets, A new window with the dataset name ‘Merge’ appears, where you can see Join, Fields, Filters and Summary tabs.

Merge.gif

Join

Basic JOIN clauses are used to combine rows from two or more tables, based on a common field between them. There are four types of Joins supported in Gainsight: Inner Join, Left Join, Right Join, and Outer Join. Each join type, when used with a Merge task in Data Designer (BETA), produces a slightly different data set. For more information, refer to the Join Types document.

Inner Join: this join retains common records from both datasets. 

Left Join: this join retains all the records from the left dataset.

Right Join: this join retains all the records from the right dataset.

Outer Join: this join Retain all records from both datasets.

To Join two datasets:

  1. Navigate to the Join tab.
  2. Select the required Join type, based on your business requirement.
  3. Select a field from each dataset to set the criteria. For instance, the Company Name in first dataset is Name, and Company Name in second dataset is Company Name.
  4. Click + to add multiple field mappings, if required. This helps filter the records based on your business requirements. 
  5. Click Save.

Join.gif

Fields 

You can see the following options in the Fields tab:

  1. Search Fields: In the Search Fields textbox, type in the Field Name you want to search for. Search operation happens on the fields available in the Dataset.
  2. Select All: Select/Deselect the checkbox to Add/Remove the fields from the merged dataset (or) You can also select/deselect the individual field checkboxes.  
  3. Display Name: By default, Field Name name appears in the Display Name textbox, if required you can modify it. Display Names are shown in the Datasets/reports. 
  4. Save: Click Save to save the changes made in the merged dataset.

Merge fields.gif

Filters

Filters in Merge work as Filters in Edit Dataset. For more details, refer to the Filters section.

Summary

Summary details in Merge are same as Summary details in Edit Dataset. For more details, refer to the Summary section.

Preview Dataset

To Preview Dataset:

Click the eye icon (or) click options, and then click Preview Dataset. In Preview, you can only view the sample data and might not contain the entire data.

Maximize: You can also view the sample data in a full screen view by clicking the Maximize  icon on the Preview tab. 

Refresh : Click the Refresh icon on the Preview tab to refresh the sample data, if you have edited the dataset.

Enlarge and Refresh.gif

Delete

To delete a Dataset:

If you wish to delete a dataset permanently from a Data Design, click Options, and then click Delete icon.

Preview (Output Dataset)

To Preview Output Dataset:

Click Preview on the upper right corner of the Design page (or) Navigate to the output/last dataset in the design, Click the eye icon (or) click Options, and then click Preview.

Preview Output Dataset.gif

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