Creating Data Tables

This guide covers how to create and configure all types of data tables in AI SCADA.

When to Use This Page

Use this page when:

• your basic tag-view-run path already works
• you need records with columns and rows, not only live values
• you know what event or schedule should create each record

Before You Start

Make sure:

• the project is already open and can run
• the source tags are named and tested
• you know whether the first table should archive by time, by event, or by manual input

Expected Result

After this page, you should be able to:

• create one practical data table
• add fields from tags or formulas
• enable the related data service
• show the resulting records on a view

Day-1 Quick Path

For the first useful table, do only this at first:

1. create one Tag Archiving table named Monitoring_Snapshots
2. add Temperature, Pressure, and MotorRunning as fields
3. configure one simple trigger
4. start the data service
5. confirm that rows begin to appear

Once that works, you can stop. The aggregation and base-data sections later on this page are advanced extensions.

Recommended First Table for a New Project

For a first table, start with one simple Tag Archiving table such as Monitoring_Snapshots:

Field	Source	Example use
Record Time	System default	Timestamp for every row
Temperature	Tag link	Save the current process value
Pressure	Tag link	Save a second analog value
MotorRunning	Tag link	Save the basic equipment state
OperatorNote	Optional text or formula	Add context later if needed

This is usually enough to validate the full table workflow before you design larger production tables.

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Create a Tag Archiving Table

Tag Archiving tables collect data from tags based on trigger conditions.

Note: For a first project, start with Tag Archiving. Add Data Aggregation and Base Data only after one simple table already records correctly.

Step 1: Create the Table

1. Navigate to Data Management
2. Click Add → Tag Archiving
3. Enter a table name (e.g., Monitoring_Snapshots)
4. Click Confirm

📷 [UG-DATA-TBL-01] Create Tag Archiving Table dialog

Step 2: Configure Fields

Fields define what data is recorded in each row.

Add a Field:

1. In the Configuration Panel, click Add Field
2. Enter a field name (e.g., Temperature, Cycle_Time, Operator_ID)
3. Select a field type:
   • Numeric: For numbers (temperature, pressure, count)
   • Text: For strings (status, operator name, product code)
   • Date: For timestamps (start time, end time)
4. Configure the field source:
   • Link to Tag: Select a tag to record its current value
   • Calculation Formula: Enter a formula to process data
5. Click Confirm

📷 [UG-DATA-TBL-02] Add Field dialog showing tag selection and formula editor

Default Fields:

• Every table includes a Record Time field (timestamp when the record was created)
• You cannot create another field named "Record Time"

Field Configuration Examples:

Field Name	Type	Source	Description
Temperature	Numeric	Link to Tag: Temperature	Current process temperature
Pressure	Numeric	Link to Tag: Pressure	Current process pressure
MotorRunning	Text	Link to Tag: MotorRunning	Current equipment state
Shift	Text	Link to Tag: System_Shift	Current shift name

Step 3: Configure Storage Settings

1. Click Storage Settings
2. Enable Auto Cleanup
3. Set the Retention Period (e.g., 6 months, 1 year)
4. (Optional) Enable Auto Backup Before Cleanup
5. Set the Backup Path (local or network share)
6. Click Confirm

📷 [UG-DATA-TBL-03] Storage Settings dialog Reuse note: Can likely share one base dialog with UG-TAGS-HIS-03.

Retention Guidelines:

Archiving Frequency	Recommended Retention
Every second	3-6 months
Every minute	1-2 years
Hourly	3-5 years
Daily	5-10 years

Step 4: Enable the Data Service

1. Click Run Settings in the toolbar
2. Click Start Data Service
3. The table begins archiving data based on trigger conditions

⚠️ Caution: The Data Service is disabled by default during configuration. Remember to enable it before deployment.

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Stop Here for the First Success Path

If Monitoring_Snapshots is already recording rows, your first table is complete.

You only need the sections below when you are moving beyond the first project into dashboard summarization, master-data management, or larger business workflows.

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Advanced Extensions

Create a Data Aggregation Table

Data Aggregation tables summarize data from another table (the "source table").

Step 1: Create the Table

1. Navigate to Data Management
2. Click Add → Data Aggregation
3. Enter a table name (e.g., Hourly_Production, Daily_Energy)
4. Select the Source Table (must be an existing table)
5. Click Confirm

📷 [UG-DATA-TBL-04] Create Data Aggregation Table dialog with source table selection

⚠️ Caution: The source table cannot be changed after creation. Plan your aggregation structure carefully.

Step 2: Configure Fields

Aggregation fields define how data is grouped and summarized.

Add a Field:

1. Click Add Field
2. Enter a field name
3. Select a field type (Numeric, Text, or Date)
4. Configure the field source:
   • Link to Field: Select a field from the source table
   • Calculation Formula: Enter a formula to process data
5. If linking to a field, set the Processing Rule:
   • Grouping: Group records by this field
   • Aggregation: Summarize records using this field
6. Click Confirm

📷 [UG-DATA-TBL-05] Add Aggregation Field dialog

Grouping Rules

Numeric/Text Fields:

• Same Value: Group records with identical values

Date Fields:

• By Year/Quarter/Month/Week/Day/Hour/Minute: Group by time dimension
• Same Value: Group by exact timestamp

Aggregation Rules

Numeric Fields:

• Sum: Total of all values
• Average: Mean of all values
• Maximum: Highest value
• Minimum: Lowest value
• Distinct Count: Number of unique values
• Count: Number of records

Text Fields:

• Distinct Count: Number of unique values
• Count: Number of records

Date Fields:

• Earliest: First timestamp
• Latest: Last timestamp

💡 Tip: Every aggregation table must have at least one grouping field and one aggregation field.

Example Configuration

Scenario: Calculate hourly average temperature and pressure from Monitoring_Snapshots.

Field Name	Source Field	Processing Rule
Hour	Record Time	Group by Hour
Avg_Temperature	Temperature	Average
Max_Temperature	Temperature	Maximum
Avg_Pressure	Pressure	Average

Result: One record per hour showing average and peak values for the monitoring tags.

Step 3: Configure Aggregation Trigger

1. Click Trigger Configuration
2. Choose a trigger type:
   • Real-time Update: Aggregate whenever the source table updates
   • Scheduled Trigger: Aggregate at specific times (e.g., daily at midnight)
3. Click Confirm

⚠️ Caution: Real-time updates consume more system resources. Use scheduled triggers for large tables.

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Create a Base Data Table

Base Data tables store custom business data not directly linked to tags.

Step 1: Create the Table

1. Navigate to Data Management
2. Click Add → Base Data
3. Enter a table name (e.g., Work_Orders, Personnel_Skills)
4. Click Confirm

Step 2: Configure Fields

1. Click Add Field
2. Enter a field name
3. Select a field type (Numeric, Text, or Date)
4. Configure field properties:
   • Unique: Values must be unique (e.g., Employee ID)
   • Not Null: Field must have a value
   • Default Value: Value to use if not specified
5. Click Confirm

Example: Work Order Table

Field Name	Type	Unique	Not Null	Default Value
Order_ID	Text	✓	✓	-
Product_Code	Text	-	✓	-
Quantity	Numeric	-	✓	0
Start_Date	Date	-	✓	TODAY()
Status	Text	-	✓	"Pending"

Step 3: Manage Data

Add a Record:

1. Select the table
2. Click Add Record in the Data Preview area
3. Enter field values
4. Click Save

Import Data:

1. Click Import in the toolbar
2. Select an Excel file
3. Map columns to fields
4. Click Import

Export Data:

1. Click Export in the toolbar
2. Select a save location

💡 Tip: Use Scripts (Event-Action system) to automatically manage Base Data records.

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Display Data on Views

Create a Data Table Component

1. Open a view in the View Editor
2. Drag a Table component to the canvas
3. Configure data source:
   • Data Source: Data Management
   • Data Table: Select your data table
4. Configure columns to display
5. Add filters and export buttons

📷 [UG-DATA-TBL-06] Table component showing archived data

Create a Chart Component

1. Drag a Chart component (Bar, Line, Pie) to the canvas
2. Configure data source:
   • Data Source: Data Management
   • Data Table: Select your data table
3. Configure:
   • Dimension: Field to group by (e.g., Hour, Product_Code)
   • Metric: Field to aggregate (e.g., Total_Parts - Sum)
4. Style the chart

📷 [UG-DATA-TBL-07] Bar chart showing hourly production

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Best Practices

Table Design

• Use descriptive names: Monitoring_Snapshots or Temperature_Hourly instead of Table1
• Include time dimension: Energy_Daily, Alarms_By_Shift
• Keep tables focused on a single purpose
• Avoid overly wide tables (> 50 fields)

Archiving Frequency

Frequency	Use Case	Storage Impact
Every second	Critical parameters	High
Every 5-10 seconds	Standard monitoring	Medium
Every minute	Slow processes	Low
On event	Part completion	Very Low

Aggregation Strategy

• Use Real-time Update for critical dashboards (< 1000 records/hour)
• Use Scheduled Trigger for large tables
• Schedule aggregations during low system activity

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Next Steps

• Configuring Triggers and Formulas - Define the exact event or schedule that should create records
• Creating Analytics Dashboards - Visualize the new table after records start appearing
• Data Management Reference - Return here for field types, functions, and troubleshooting
• Data Management Examples - Use these later for broader production scenarios