Creating Data Tables

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

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Create a Tag Archiving Table

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

Step 1: Create the Table

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

📷 [Screenshot: 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

📷 [Screenshot: 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
Oven_Temperature	Numeric	Link to Tag: Oven_Temp	Current oven temperature
Product_Code	Text	Link to Tag: Product_ID	Current product being manufactured
Cycle_Time	Numeric	Formula: [End_Time] - [Start_Time]	Calculated cycle duration
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

📷 [Screenshot: Storage Settings dialog]

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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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

📷 [Screenshot: 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

📷 [Screenshot: 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 production by product code.

Field Name	Source Field	Processing Rule
Hour	Record Time	Group by Hour
Product_Code	Product_Code	Group by Same Value
Total_Parts	Part_Count	Sum
Avg_Cycle_Time	Cycle_Time	Average

Result: One record per hour per product showing total parts and average cycle time.

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

📷 [Screenshot: 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

📷 [Screenshot: Bar chart showing hourly production]

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Best Practices

Table Design

• Use descriptive names: Production_Hourly not 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 - Set up data collection rules
• Data Management Reference - Field types, functions, troubleshooting
• Data Management Examples - Real-world scenarios