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Dynamics NAV + JetExpress create report Understand table structure

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Posted on by D365 Warrior

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Hi,

I am a newbie in Dynamics NAV. Recently I am working on Dynamics NAV 2015 and JetExpress reports.

During report implementation, I have faced an issue that how can manage table relation among related tables.

Say, I would like to create a report Item and Customer sales report. In JetExpress table builder I

In JetExpress table builder I select Item table first then under it Customer and Value Entry table. It shows the completely wrong result.

But when following the JetExress example, Add Value Entry table first then item and customer. It shows exact results.

My understanding is that there should be rules, how can I relate tables with each other in the report.

Can anyone help me to understand the table structure while designing a report?

Thanks

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mmv 11,471 on at

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The structure and relation of each table differs. Please elaborate which all the tables you want to relate.

If you look at the Item or Customer table, there are some flow fields to display some calculated figures (e.g Balance, Payments, "Invoice Amounts" fields etc in the Customer table). You may get some idea from that too.

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D365 Warrior 130 on at

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Following tables are rquired

Value Entry

Item

Customer

Item Ledger Entry

The main purpose of the report is Item sales report for customer based on EU country

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mmv 11,471 on at

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You may relate the "Value Entry" with Customer as below:-

Source No. is Customer -> No.

Source Type is Customer.

Item Ledger Entries can be related with Item : "Item Ledger Entry" -> Item No. = Item -> No.

Value Entry can be related with Item Ledger Entry : "Value Entry" -> "Item Ledger Entry No." = "Item Ledger Entry"."Entry No."

Hope this gives you some highlight on how to relate few tables.

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D365 Warrior 130 on at

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Thanks Mahesh for your great support. Yes, I got your point. But the main problem occurred while using the multi table in jetReport. Please see the below images

In the above image: Root table Item-> than other tables use the relation as you mention above but result totally different.

On the other hand

use the same relation as you mention above result shows as expected.

Do you have any idea, why it behaves totally differents?

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