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Import/Export CSV

The CSV import/export functionality extends this capability by allowing you to manage FEEL expressions in familiar spreadsheet environments while maintaining full compatibility with Nected's powerful

Nected gives you an option to import or export Decision Tables in FEEL-compatible CSV format. This feature allows you to manage Decision Table logic using spreadsheet tools like Excel or Google Sheets.

What is FEEL?

Friendly Enough Expression Language (FEEL) is a standardized expression language designed to bridge the gap between business logic and technical implementation. FEEL enables business analysts, domain experts, and developers to collaborate effectively by providing a syntax that is both human-readable and machine-executable. Originally defined as part of the Decision Model and Notation (DMN) specification by the Object Management Group (OMG), FEEL has become the standard for expressing business rules and decision logic.

In Nected, FEEL serves as the foundation for creating sophisticated decision logic within Decision Tables, Rules, and Workflows. By supporting FEEL-compatible expressions, Nected ensures that your business rules remain portable, standardized, and accessible to both technical and non-technical team members. Whether you're defining simple conditions or complex multi-criteria decisions, FEEL's intuitive syntax makes it easy to express your business logic clearly and precisely.

DMN (Decision Model and Notation) support is also on our roadmap. Soon, you'll be able to import and manage complete DMN models directly within Nected, making it easier to align with industry-standard decision modeling practices.

Before importing or exporting the CSV file, here are the prerequisites that you need to understand and configure accordingly:

What should the FEEL-compatible CSV File Format be?

Whenever you're preparing a CSV file for rule testing or bulk evaluations, the structure must strictly follow a FEEL-compatible format. Each column should represent a valid FEEL expression bound to a data type (e.g., numeric, string, date, datetime). Each row represents a different test case or input set.

status

numeric({{.customInput.Num1}})

numeric({{.customInput.Num1}})

date({{.customInput.Date1}})

dateTime({{.customInput.DateTime1}})

string(result)

dateTime(keyName)

TRUE

1

2

date("2025-11-10")

datetime("2025-06-27T16:27:00+05:30")

"Atul1"

datetime("2025-06-27T17:28:43+05:30")

TRUE

fx(var a=10;a)

< fx(var a=10;a)

fx(var a = "2025-11-10";a)

> datetime("2025-06-27T17:06:02+05:30")

"Atul1"

datetime("2025-06-27T17:28:43+05:30")

TRUE

< 10

not([12...231])

!= fx(var a = "2025-11-10";a)

< datetime("2025-06-27T17:06:09+05:30")

"Atul1"

datetime("2025-06-27T17:28:43+05:30")

TRUE

>= 1

>= 1

[fx(var a = "2025-11-10";a)...date("{{.globalVar.fs}}")]

!= datetime("2025-06-27T17:06:24+05:30")

"Atul1"

datetime("2025-06-27T17:28:43+05:30")

Download the sample CSV file to get an idea how to write the CSV file:

7KB
FEEL_CSV.csv

2. FEEL Compatible Operators for CSV

When creating FEEL expressions in your CSV files, use these operators that are compatible with Nected's platform. This table shows the FEEL syntax, corresponding Nected operators, their purpose, and usage examples.

FEEL Operator
Nected Operator
Purpose
Examples (Static / Token / Function)

Existence

exists()

EXISTS

Confirms that the current field is present and not null

exists()

not(exists())

NOT EXISTS

Confirms that the current field is missing or undefined

not(exists())

null

NULL

Checks for an explicit null value

null

not(null)

NOT NULL

Checks that the value is anything except null

not(null)

Comparison

==

EQUAL

Tests equality

== 10 / ==ABC or, simply writing the value 10 / == {{.customInput.Name}} / == fx(var a=10;a)

!=

NOT EQUAL

Tests inequality

!= "Blocked" / != {{.globalVar.status}} / != fx(var s="X";s)

>

GREATER THAN

Greater‑than comparison

> 21 / > {{.customInput.age}}

<

LESS THAN

Less‑than comparison

< 1000 / < {{.globalVar.maxAmount}}

>=

GREATER THAN EQUALS

Greater‑than‑or‑equal comparison

>= 75 / >= {{.globalVar.minScore}}

<=

LESS THAN EQUALS

Less‑than‑or‑equal comparison

<= 5000 / <= {{.customInput.limit}}

Range

[x...y]

BETWEEN

Inclusive range check

in [1...3] / in [1...{{.globalVar.base_price}}]

not([x...y])

NOT BETWEEN

Outside inclusive range

not(in [0...50]) / not(in [0...{{.globalVar.minPass}}])

(x..y)

BETWEEN EXCLUSIVE

Exclusive range check

in (100..1000) / in ({{.globalVar.minAmount}}..{{.globalVar.maxAmount}})

String

contains()

CONTAINS

Checks for substring

contains("John") / contains("{{.globalVar.searchTerm}}")

not(contains())

NOT CONTAINS

Confirms substring absence

not(contains("spam")) / not(contains("{{.globalVar.blocked}}"))

startsWith()

START WITH

Checks prefix

startsWith("ABC") / startsWith("{{.globalVar.prefix}}")

not(startsWith())

NOT START WITH

Confirms prefix absence

not(startsWith("TEMP")) / not(startsWith("{{.globalVar.tempPrefix}}"))

endsWith()

END WITH

Checks suffix

endsWith(".com") / endsWith("{{.globalVar.allowedDomain}}")

not(endsWith())

NOT END WITH

Confirms suffix absence

not(endsWith(".tmp")) / not(endsWith("{{.globalVar.tempExt}}"))

List

in

IN

Membership test

in ["Active","Pending"] / in {{.globalVar.statusList}}

not(in)

NOT IN

Non‑membership test

not(in ["Blocked","Banned"]) / not(in {{.customInput.List1}})

empty()

EMPTY

Checks for empty list

empty()

not(empty())

NOT EMPTY

Checks for non‑empty list

not(empty())

containsIn()

CONTAINS IN

Validates that every item exists in a reference list

containsIn ["Admin","User"] / containsIn {{.customInput.roles}}

not(containsIn())

NOT CONTAINS IN

Detects missing items with respect to reference list

not(containsIn ["Special"])

matchAll()

MATCH ALL

Confirms that all specified items are present

matchAll ["GPS","WiFi"] / matchAll {{.customInput.features}}

not(matchAll())

NOT MATCH ALL

Confirms that at least one item is missing

not(matchAll ["ID","Proof"])

Boolean

true

TRUE

Boolean literal true

true

false

FALSE

Boolean literal false

false

even()

EVEN

Checks if current number is even

even()

not(even())

ODD

Checks if current number is odd

not(even())

Date/Time

date()

DATE

Creates a date value

date("2025-01-15") / date("{{.customInput.dateString}}")

datetime()

DATETIME

Creates a datetime value

datetime("2025-01-15T10:30:00") / datetime("{{.customInput.dateTimeString}}")

Advanced

fx()

ExcelFormula

Evaluates an Excel‑style formula

fx(var a=10;a*2) / fx(var a={{.customInput.value}};a*{{.globalVar.mult}})

js()

JsFormula

Evaluates a JavaScript expression

js: Math.round(10.4) / js: Math.round({{.customInput.value}}*{{.globalVar.rate}})

Refer to the Pre-Configured Operators documentation for the complete list of available operators and their syntax. This ensures that your CSV expressions will work correctly when imported into Nected Decision Tables. Example expressions:

  1. age >= 18 (numeric comparison)

  2. status = "Active" (string equality)

  3. category in ["Premium", "Gold"] (list membership)

  4. applicationDate between "2024-01-01" and "2024-12-31" (date range)

  5. age >= 18 (numeric comparison)

  6. status = "Active" (string equality)

  7. category in ["Premium", "Gold"] (list membership)

  8. applicationDate between "2024-01-01" and "2024-12-31" (date range)

Available Token Types:

  • customInput: {{.customInput.fieldName}} - User-defined inputs

  • globalVar: {{.globalVar.variableName}} - Global variables

  • dataSet: {{.dataSet.fieldName}} - Dataset references

  • outputData: {{.outputData.fieldName}} - Previous rule outputs

  • systemVar: {{.systemVar.NULL}}, {{.systemVar.ExecutionId}}, {{.systemVar.Environment}}

Importing Decision Tables from FEEL-compatible CSV

You can import Decision Table data from CSV files that follow the FEEL-compatible format. This allows you to manage your decision logic using external spreadsheet tools and bulk import rules into Nected.

Only the Table data will be imported, not the dependencies i.e., input attributes are not included in CSV import. To import the complete decision table, import it using by default way.

Follow these steps to import a FEEL-compatible CSV to the decision table:

  1. Access Import Function

    • Open the Decision Table editor where you want to import the CSV from the dashboard or create a new one.

    • Click the Import button in the bottom of the decision table. It will open a popup like below:

      image.png

  2. Upload and Preview

    • Click Upload file and select your prepared CSV file

    • After it successfully got imported, click on “Continue with Import” button.

      image.png

If everything with your csv file is correct, then the rows will be simply imported and appended into the decision table; else you’ll see the errors in your csv file from this popup:

image.png

Exporting Decision Tables to FEEL-compatible CSV

Export your existing Decision Tables to CSV format for external editing, backup, or sharing with stakeholders who prefer working with spreadsheet applications.

Steps to Export the decision table as FEEL compatible format is very simple:

  1. Open the Decision Table to ensure it contains the data you want to export.

  2. Click the Export button in the Decision Table

To Export the Decision Table to FEEL compatible csv format, their should be at least one property added in the DT.

Not Supported Features

When using CSV import/export for Decision Tables, certain advanced features are not supported. If your Decision Table contains any of these elements, CSV export will not be possible:

1. Group Conditions If you've created grouped conditions in your Decision Table using the "Group" functionality, CSV export will not work. Group conditions that combine multiple criteria with complex logical relationships cannot be represented in the flat CSV structure.

2. Relative Dates Decision Tables that use relative date conditions (such as "last 30 days", "next week", or "3 months ago") are not supported in CSV export. These dynamic date references cannot be accurately converted to the static CSV format.

Conclusion

The CSV import/export functionality for Decision Tables provides a powerful way to manage your business rules using familiar spreadsheet tools while maintaining full compatibility with Nected's FEEL expression language. This feature enables seamless collaboration between technical and business teams, allows for bulk rule management, and simplifies the process of maintaining complex decision logic.

By leveraging FEEL-compatible operators and Nected's comprehensive token system, you can create sophisticated decision rules in CSV format that seamlessly integrate with your existing workflows. Whether you're migrating existing rules, collaborating with stakeholders, or managing large-scale decision tables, the CSV format offers the flexibility and ease-of-use needed for effective decision management.

Remember to follow the format specifications and operator guidelines outlined in this documentation to ensure successful import and export operations. For any advanced features not supported in CSV format, continue using the native Nected Decision Table interface to maintain full functionality.

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