Sage 100 Template

Use the following links to jump to a section:

• Sage 100 Template
• Introduction
• Nectari Data Sync
• Importing the Extractions
• Add SQL Query with ODBC connector without Subqueries
• Validating and Building the Extractions
• Running the Extractions
• Data Source Configuration
• Importing Templates
• Updating template
• Building and Loading the OLAP Cubes

Introduction

The Templates installation provides you with a ready-to-use set of Views, Dashboards and Reports.

The installation (assuming the Central Point is freshly installed and empty), will consist of two steps:

• Configuring the Data Sources for the ERP and Data Warehouse (optional) databases.
• Importing the Templates into the Central Point.

There may be other steps including building and loading the OLAP Cubes.

Nectari Data Sync

Data Sync is required for Sage 100 Premium only if you want to consolidate the data into one database so that Reports from different Companies can be viewed into the same one.

Prerequisites

• A version of Sage 100 supported by Sage
• A destination database (preferably, in the same collation as your Sage 100 Database)
• A valid version of Data Sync (refer to Installing Data Sync for more information)

Set the Connections

Settings for Sage 100 Premium

If you are using Sage 100 Premium, do as follows. If not, refer to Settings for Sage 100 Standard.

• Follow the procedure described in Add a Source and Destination Connection to create a Source and a Destination connection.

Settings for Sage 100 Standard

1. In Data Sync, click on the Connections tile.
2. In the upper left corner, click on New to create a new Source connection.
   
3. In the list, select the ODBC.

Connection Properties Panel

1. In the Description field, enter a name for this connection.
2. Leave the Null Expression fields on their default values.
3. Enter a single quote in the String Constant fields.
4. In the section below, tick all the checkboxes except the Supports Schemas and Supports Subqueriesand checkboxes.

5. When ticking the Supports Quotes checkbox, tick only the Alias and Columns checkboxes.
6. Enter a single quote in the Left Delimiter and Right Delimiter fields.
7. Leave the other Fields on their default values.
8. In the Meta Loading drop-down list, select From SELECT Statement.
   

Additional Connection Properties Panel

• Click on Add property to add the properties described in the table below:

Advanced Settings Panel

1. In the Tracking Type drop-down list, select Date.
2. Set the time zone to the Sage 100 Application Server Time.

You should have a result similar to this:

3. Click on Save to finish.

Importing the Extractions

This feature allows you to import a pre-defined template or to restore a backup that you may have done yourself with the Export feature (refer to Export an Extraction for more details).

Some pre-defined templates are already available; if you don't have access to them, please contact your partner. An example of a pre-defined template you could use is the one which defines the list of tables and fields to be synchronized to send Sage 300, X3, Acumatica, Salesforce data to the Cloud.

1. Click on one of the extractions in the list then on the Import icon located on the upper right-hand corner.
   
2. In the Import Extraction window, click on the Choose a zip file hyperlink to browse to the location you saved the export .zip file or drag it directly into that window and click on Next.

3. On the left pane, select the type of extraction you want to perform and click on Next.
   

4. Refer to Setup the Extraction Panel to define the extraction and click on Import to finish the process.
   

5. You should have a result similar to this:

The diagram below illustrates how Data Sync processes data.

Add SQL Query with ODBC connector without Subqueries

When Subqueries on your Source connection for ODBC are disabled, Nectari Data Sync no longer parses your code with the settings and only executes raw code entered in the SQL Query window. Note that ERPs such as Sage 100 Standard use an older ODBC Driver, which does not support Subqueries, and can limit capability.

When adding an SQL Query (refer to Setup the Field Section), there are multiple guidelines to be mindful of:

1. If Delimiters are absolutely necessary with your ODBC Driver, you will have to set them.
2. To do a Join , your Tables must be placed inside {oj […]}.

SELECT Customer.*
FROM {oj Customer INNER JOIN SalesReps ON Customer.SALESREP = SalesReps.SALESREP}

3. You cannot use the * (asterisk) without an Alias in your SELECT statement if your SELECT statement joins more than one Table. While this might not give you an error, there is a risk of introducing errors when you have multiple Columns with the same name across the different Tables .

Here is an example of a statement that would cause errors:

SELECT *
FROM {oj Customer INNER JOIN SalesReps ON Customer.SALESREP = SalesReps.SALESREP}

4. You cannot use multiple * (asterisk) with an Alias in your SELECT statement. This issue also applies to multiple Columns with the same name, although this will simply break when performing the Process Deleted Records task, as it will not be able to find which Table the Field comes from.

Here is an example of a statement that would cause errors:

SELECT Customer.*, SalesReps.*
FROM {oj Customer INNER JOIN SalesReps ON Customer.SALESREP = SalesReps.SALESREP}

5. Avoid creating Calculated Fields in the SELECT statement. Use the menu options in the Field section instead (refer to Setup the Field Section). In most cases, this will not cause a problem. However, when setting that Field as a Primary Key or Tracking Key, there is a risk of introducing an error during the Incremental Load or Process Deleted Records tasks.

Adding a Table not included in the Extraction zip file

• Refer to Setup the Field Section to use the following Calculated Field as Tracking Key for Incremental Load task if you wish to add a Table:

{fn TIMESTAMPADD(SQL_TSI_SECOND,
{fn CONVERT( {fn FLOOR(  {fn CONVERT(TimeUpdated,SQL_FLOAT)} * 3600 ) } - {fn CONVERT( {fn FLOOR(  {fn CONVERT(TimeUpdated,SQL_FLOAT)} ) }, SQL_INTEGER) } *3600, SQL_INTEGER) },
{fn TIMESTAMPADD(SQL_TSI_HOUR, {fn CONVERT( {fn FLOOR(  {fn CONVERT(TimeUpdated,SQL_FLOAT)} ) }, SQL_INTEGER) } ,{fn CONVERT(DateUpdated,SQL_TIMESTAMP)} )}  )}

Validating and Building the Extractions

Once your extraction (source, destination connection and their related tables) is set up, the next step is to validate the setting of an extraction, before being able to run it.

The feature will:

• Ensure that all the tables/fields exist in the source connections,
• Validate all SQL queries or calculated fields,
• Ensure that the data integrity in the destination connection is not affected (ex: change the table structure).

To do so:

1. Select the extraction you want to validate and build in the list and click on the Validate and Build icon.
   
2. In the new window, choose the action which best fits your needs and click on Build (Validate for Migration and Export extraction types).
   

3. Wait for the process to be done.

Running the Extractions

Once your data have been validated (refer to Validate and Build an Extraction for more details), you can manually run the extraction if you want an immediate result instead of scheduling it.

1. Select the extraction you want to run in the list and click on the Run Extraction Now icon.
   
2. In the upper-right hand corner, choose the action you want to execute and the table(s) then click on Run.

3. Wait for the process to be done.

Data Source Configuration

Environments and Data Sources

The following information is needed to configure the Data Sources:

• Database server credentials: Server name, Instance, Authentication strategy.
• Main ERP database information: Database and schema name.

ERP Data Source

1. In the upper-right hand corner, click on the to access the Administration section.
   
2. On the left pane, select Env. & Data Sources.
3. By default, there is already an environment called Production, which you can rename by double-clicking in the name box. Once changed, press the Enter key.
   
4. In the Data Sources section, click on Add to create the first Data Source.
   
5. Complete the ERP Data Source configuration. See instructions for MS SQL Server below.

Datasource description:

If you use Data Sync:

Sage 100 DATASYNC

If you don't use Data Sync:

Sage 100 VIEWS

For UDM Template:

Sage 100 TABLES

Type:

SQLSERVER

Server:

Database server of Sage 100

Database name:

Name of the Sage 100 database (beware of the case sensitivity)

Database schema name:

Create the two following entries by clicking on the icon (replace DatabaseName by the appropriate value):

If you use Data Sync:

DatabaseName.DestinationSchemaInDataSync

DatabaseName.NEC_CUSTOM_SCHEMA

If you don't use Data Sync:

DatabaseName.NEC_CUSTOM_SCHEMA

DatabaseName.dbo

For UDM Template:

DatabaseName.dbo

DatabaseName.NEC_CUSTOM_SCHEMA

Note

This second line contains the NectariCustom Schema.

You can use a different one, but we highly recommend following this naming convention:

• Start with NEC
• Use all capitals
• Separate words by an underscore

Important

Choose a unique Custom Schema name for each Environment.

Nectari schema:

Enter the chosen Nectari custom schema for the current environment

Authentication stategy:

UseSpecific

User Name:

SQL User accessing the Sage 100 database. For example, sa.

Password:

The user's password.

6. Click on Validate then on Save to complete the configuration of the Data Source.

Cube Data Source

In the same Environment as the ERP Data Source, create a new Data Source for the OLAP Cube.

Complete the Data Source Definition with all the appropriate information.

The screenshot below provides an example of this.

Server:

Database server where the Nectari OLAP For SQL Server package is installed.

Database name:

NectariCube.

Database schema name:

NectariCube.NEC_FOLDER (replace FOLDER by the folder name).

Where NEC_FOLDER (replace FOLDER by the folder name) is the schema used in the ERP Database of the same environment.

Nectari schema:

Enter the chosen custom schema for the current environment

• Click on Validate then on Save.
• Click on Set as Data Warehouse to define the Data Source as a Data Warehouse then enter the following information:

Database warehouse schema:

Enter the chosen Nectari custom schema again.

Use MARS during the cube loading:

Unchecked

• Click on Validate then on Save.

Importing Templates

For each environment, the following previously configured information will be required:

• ERP Database Name
• Nectari Custom Schema
• ERP Schema

Download the Template file: TPL_9.X.XXX_Sage100Conso.zip.

The X represents the build number of the template (use the highest available).

Running the Import Template

1. In the upper-right hand corner, click on the to access the Administration section.
   
2. In the Administration section, click on the Templates drop-down menu in the left pane.
3. Select Import Template.
4. Choose the specific location where the new templates will be installed and click on Next.
   
   Note

   Usually, the Root folder is used.

5. In the Import Template window, click on Select files....
   
6. Find the folder where you saved the Template.zip file in order to select it then click on Open.
7. In the Data Sources Mapping screen, associate the Data Sources (ERP) listed in the Received Data Sources Description column (those from the template) with the Data Sources you previously defined in the Central Point (listed in the Current Data Sources Description column)
• In the Received Data Sources Description column, ensure that only the Data Sources checkboxes you want to use from the template are ticked off.
• In the Current Data Sources Description column, click on Bind a Data Source to access the drop-down list containing the existing Data Sources and click on Next.
  

In the next screen all of the Templates content is displayed, against what the Central Point already has.

By default, on the first install, everything will be set to Add (leave everything by default) .

• In the case of a first installation, the first four columns will display None and Never Installed, the next three will detail the Template content, and the last three gives you the choice to Add, Update or Skip during the installation.
  Note

  In the case of an update, you can refer to Updating template for more details.

1. Click on Next (this can take time).
   

2. Once this has been completed, a window will be prompted to input the necessary parameters to create the custom objects.
3. If more than one Environment have been created, you will see a column per Environment. You can untick an Environment checkbox, in which case the Global Scripts will not run in it.

4. Complete the parameters, see examples below, and click on Next.
   

5. After importing, an Execution Report will be produced, as shown below.
   Note

   The first section is for the ERP Data Source and the one below it is for the Cube Data Source.

   You can click on the button to see the details of each script individually. If no failures are reported, close the window.

6. If any of the scripts failed to run, a fail icon will be displayed. Click on the fail symbol to view the Report Preview window, which shows the respective SQL script.
   

• Copy this script, debug, and run it separately if needed. Users who are proficient with SQL can debug it straight in the Report Preview window and run it by clicking on the Try to rerun button.
  

Updating template

When performing an upgrade of the Nectari software, it will only update the software and not the template. In other words, the existing Nectari Data Models and Views won't be affected.

To update a template:

1. After having mapped the Data sources, tick the checkboxes of the objects you want to upgrade and click on Next.
   
   Note

   By default, no checkbox in the Update column will be ticked. If there is a new Data Model / View the Add checkbox will be ticked. Select Skip if you want to ignore it.

   Important

   If you tick the Update checkbox, it will overwrite the existing Nectari objects associated with that Data Model or connected to the others (dependencies). Please note that if any customizations have been done, they will be lost.

2. Select the environment in which the scripts will be executed and click on Next.
3. Complete the parameters and click on Next.
4. In the Execution report window, If any of the scripts failed to run, a fail icon will be displayed. Click on the fail symbol to view the Report Preview window, which shows the respective SQL script.
5. Copy this script, debug, and run it separately if needed. Users who are proficient with SQL can debug it straight in the Report Preview window and run it by clicking on the Try to rerun button.
   

Building and Loading the OLAP Cubes

To create the Cubes database structure in the NectariCube database previously installed, you need to Build the Cube.

1. In the upper right-hand corner, click on the to access the Administration section.
   
2. In the left pane, click on OLAP Manager.
3. In the right pane, click on Manage.
   
4. In the left section, select all the Cubes to build by ticking the checkbox next to the Description column.
5. In the Manage window, select Build in the Action drop-down list then the environment(s) and click Confirm.
   
6. In the Confirmation window, tick the checkbox and click on Yes.
   
7. If errors occur refer to Logs to activate the logging feature.

Now that the Cubes are built, you can now populate them.

1. In the right pane, click on Manage.
2. In the left section, select all the Cubes to load by ticking the checkbox next to the Description column.
3. In the Manage window, select Load All in the Action drop-down list then the environment(s) and click Confirm.
   
4. In the Confirmation window, tick the checkbox and click on Yes.
   

The template installation is now complete.

Regular data refresh jobs for the Cubes can now be scheduled. For more details on how to do this, refer to Scheduler.

Populate Zip Codes

During the import, a table is created in the Nectari Custom Schema for ZIP codes.

Although the ZIP table is not required for the Sage 100 Template to function, downloading and populating the ZIP table with a recent data dump of ZIP codes including the (latitude, longitude) details is recommended.