Day3-Data Models & Dimensions

• Analytics

Data models

●  Aggregate data:
    ○ Routinely collected
    ○ Mostly numbers

● Events:(Indoor Hospital)
  ○ Occurs at any time 
  ○ Describes an event that took place

● Tracking data: (EPI Cold Chain, Kala-Azar, MCH Tracker, HIV-AIDS, Cervical Breast Cancer Tracking)
  ○ Data linked to an identifiable entity
  ○ Data can be linked to stages in program

• Data dimensions

A data value in DHIS2 is described by at least three dimensions: 1) data element, 2) organisation unit, and 3) period. These dimensions form the core building blocks of the data model.

Fixed Data Dimension:

Example:

Dynamic Data Dimension:

Example:

Dynamic Data Dimension: Organization Unit group sets

Dynamic Data Dimension: Organization Unit group sets example

Dynamic Data Dimension: Category options group sets

Dynamic Data Dimension: Category options group sets example

Data Dimensions - Events:

● Fixed dimensions
   ○ Program
   ○ Periods
   ○ Organisation units

Example:

 

● Dynamic dimensions
   ○ Data elements
   ○ Attributes

• Analytics engine overview

 ● Source for aggregate data - used by all DHIS 2 analysis apps
 ● Useful for integration with third-party tools
   ○ Analysis tools like R, Stata, SPSS
   ○ Integration with external systems/tools like SSI
 ● Exposed as REST Web API and Java API
 ● Analytics tables must be generated (ad-hoc or scheduled)
 ● Pivot table & event reports can be used as API browser

• Dimensions and Item

 ● Dimensions are uniform
  ○ No need to know the underlying object type

 ● Get all dimensions from API
  ○ /api/dimensions
Example: 
http://103.247.238.86:8081/dhis28/api/dimensions

Result: 
{
    "pager": {
        "page": 1,
        "pageCount": 1,
        "total": 1,
        "pageSize": 50
    },
    "dimensions": [
        {
            "id": "mc2ceK4TjB6",
            "displayName": "Sex"
        }
    ]
}

 ● URL syntax
  ○ /api/analytics?dimension=dim-id:item-id;item-id;

• Aggregate Analytics API

● Returns data values aggregated across dimensions
  ○ /api/analytics

● dimension query parameter
  ○ Defines which dimensions to include in response

● filter query parameter
  ○ Defines which dimensions to apply as filter for response

• Dimensions and Items

• The dx dimension

• Date and Period Format

• Aggregate Indicators

●	Expression with data elements
●	Indicator type
●	Numerator and denominator

• Program Indicators

	●	Expression and Filter
	●	Aggregation types
	●	Functions
	●	Variables

• Aggregation Operators

• Aggregation Levels and Measure Criteria

	●	Apply filters to data in the response Operators: EQ, GT, GE, LT, LE
	●	Format: measureCriteria=criteria:value;criteria:value
	●	Example: api/analytics?measureCriteria=GE:6500;LT:33000

• Table Layout

• Options

• Response Formats

• Date Value set Format

• Integration with DVS format

• Raw Data Format

• Aggregate analytics API

• Event analytics API (aggregate/event query)

• Unified Analytics Across Data Models

• Analytics

Data models

●  Aggregate data:
    ○ Routinely collected
    ○ Mostly numbers

● Events:(Indoor Hospital)
  ○ Occurs at any time 
  ○ Describes an event that took place

● Tracking data: (EPI Cold Chain, Kala-Azar, MCH Tracker, HIV-AIDS, Cervical Breast Cancer Tracking)
  ○ Data linked to an identifiable entity
  ○ Data can be linked to stages in program

• Data dimensions

A data value in DHIS2 is described by at least three dimensions: 1) data element, 2) organisation unit, and 3) period. These dimensions form the core building blocks of the data model.

Fixed Data Dimension:

Example:

Dynamic Data Dimension:

Example:

Dynamic Data Dimension: Organization Unit group sets

Dynamic Data Dimension: Organization Unit group sets example

Dynamic Data Dimension: Category options group sets

Dynamic Data Dimension: Category options group sets example

Data Dimensions - Events:

● Fixed dimensions
   ○ Program
   ○ Periods
   ○ Organisation units

Example:

 

● Dynamic dimensions
   ○ Data elements
   ○ Attributes

• Analytics engine overview

 ● Source for aggregate data - used by all DHIS 2 analysis apps
 ● Useful for integration with third-party tools
   ○ Analysis tools like R, Stata, SPSS
   ○ Integration with external systems/tools like SSI
 ● Exposed as REST Web API and Java API
 ● Analytics tables must be generated (ad-hoc or scheduled)
 ● Pivot table & event reports can be used as API browser

• Dimensions and Item

 ● Dimensions are uniform
  ○ No need to know the underlying object type

 ● Get all dimensions from API
  ○ /api/dimensions
Example: 
http://103.247.238.86:8081/dhis28/api/dimensions

Result: 
{
    "pager": {
        "page": 1,
        "pageCount": 1,
        "total": 1,
        "pageSize": 50
    },
    "dimensions": [
        {
            "id": "mc2ceK4TjB6",
            "displayName": "Sex"
        }
    ]
}

 ● URL syntax
  ○ /api/analytics?dimension=dim-id:item-id;item-id;

• Aggregate Analytics API

● Returns data values aggregated across dimensions
  ○ /api/analytics

● dimension query parameter
  ○ Defines which dimensions to include in response

● filter query parameter
  ○ Defines which dimensions to apply as filter for response

• Dimensions and Items

• The dx dimension

• Date and Period Format

• Aggregate Indicators

●	Expression with data elements
●	Indicator type
●	Numerator and denominator

• Program Indicators

	●	Expression and Filter
	●	Aggregation types
	●	Functions
	●	Variables

• Aggregation Operators

• Aggregation Levels and Measure Criteria

	●	Apply filters to data in the response Operators: EQ, GT, GE, LT, LE
	●	Format: measureCriteria=criteria:value;criteria:value
	●	Example: api/analytics?measureCriteria=GE:6500;LT:33000

• Table Layout

• Options

• Response Formats

• Date Value set Format

• Integration with DVS format

• Raw Data Format

• Aggregate analytics API

• Event analytics API (aggregate/event query)

• Unified Analytics Across Data Models