1. Data and Interoperability:
Health Informatics in Low- and Middle-Income Countries
Short Course for Health Information System Professionals
Data and Interoperability:
Data Warehousing

2. Data Warehousing Learning Objective and Topics Covered Objective
Explain the basic definitions and concepts of data repositories and data warehousing architectures
Topics covered
Patient-centered information systems:
Electronic medical records (EMRs) and aggregate information systems
Readiness for patient-centered information technology solutions
Development of patients’ unique identifiers
Data repositories and data warehouses

3. Data Repository/Data Warehouse
Central place where an aggregation of data is kept and maintained in an organized way
May consist of several databases linked to one another by a common search engine
Can support data that are:
Open access only
Mediated access only
Closed/private only

4. Data Repository/Data Warehouse
Defined as a place that holds data, makes data available to use, and organizes data in a logical manner
Enables deposit, preservation, and access to digital content
Real-time databases that consolidate data from a variety of sources to present a unified single view

5. Repository Examples Research data repositories
Clinical data repositories
Public health center or district data repositories

6. Data Warehouse Concepts
Distinction between data and information
Data are observable and recordable facts that are often found in operational or transactional systems.
Data only have value to end users when they are organized and presented as information.
Information is an integrated collection of facts and is used as the basis for decision making.
Systems include the facility registry, human resource, data on financial aid, and so forth.

7. Data Warehouse Concepts
A data warehouse is designed for query and analysis rather than for transaction processing.
A data warehouse separates analysis workload from transaction workload. This helps:
Maintain historical records
Analyze data to better understand the business
Improve the business

8. Data Warehouse Definition A Practitioner’s Viewpoint
“A data warehouse is simply a single, complete, and consistent store of data obtained from a variety of sources and made available to end users in a way they can understand and use it in a business context.”
– Barry Devlin, IBM consultant

9. Data Warehouse Definition An Alternative Viewpoint
“A data warehouse is a subject-oriented, integrated, time-variant, and nonvolatile collection of data in support of management's decision-making process.”
– W. H. Inmon, computer scientist

10. Data Warehouse Definition

11. Subject-Oriented Stored Data
Target specific subjects; data warehouse can be used to analyze a particular subject area: for example, high drop- off rates between the first and fourth antenatal care visit in a particular region
Provide a simple and concise view around particular subject issues by excluding data that are not useful in the decision support process

12. Integrated
Data may be distributed across heterogeneous sources that have to be integrated.
A data warehouse must put data from disparate sources into consistent format.
Data cleaning and data integration techniques are applied.
Standardization is emphasized at this point.
Naming conventions
Coding structures
Data attributes
Example: HR data could be stored in one database system while data related to facilities are stored in flat files.

13. Time Variant A data warehouse focuses on change over time.
Data are stored as a series of snapshots, each representing a period in time.
The data stored may not be current but vary with time, and data have an element of time: for example, antenatal care first visits in the past five years.
Analysts need large amounts of data to discover trends in data. 

14. Nonvolatile
Once entered in the data warehouse, data should not change and should not be subjected to frequent modification.
Stored data generally are subject to only two operations:
Loading of data
Access to data
This is logical, because the purpose of a data warehouse is to enable you to analyze what has occurred.

15. Data Warehouse Architectures
Data warehouses and their architectures vary, depending on the specifics of an organization's situation. Three common architectures are:
Data warehouse architecture (basic)
Data warehouse architecture (with staging area)
Data warehouse architecture (with a staging area and data marts)

16. Data Warehouse Architecture: Basic
This figure shows a simple architecture for a data warehouse. End users directly access data derived from several source systems through the data warehouse.

17. Data Warehouse Architecture With Staging Area
Cleaning and processing operational data before putting them into the warehouse can be done through a staging area. This could also be achieved programmatically, although most data warehouses use a staging area instead. A staging area simplifies building summaries and managing the general warehouse.

18. Swaziland’s Health Information System Architecture
Swaziland’s HIS architecture 18

19. Data Staging Area Definition
Any data store that is designed primarily to receive data in a warehousing environment
Data staging involves ETL:
Extraction (E): Reading source data and copying data needed for the data warehouse into the staging area for further manipulation
Transformation (T): Converting the read data to a common data format; cleaning, auditing, and combining data from various sources
Load (L): Writing the data into the data warehouse

20. Data Warehouse Architecture With Staging Area and Data Marts
The need to customize the data warehouse architecture for different groups within your organization can be achieved by adding data marts, which are systems designed for a particular line of business. An example is where purchasing, patient medical records, and logistics are separated. A data analyst might want to analyze historical data for logistics and patient medical records.

21. Data Mart
Repository of data designed to serve a particular community of knowledge workers to meet the demands of specific groups of users in the organization, such as human resource management
A data mart represents data from a single “business process,” such as:
Antenatal care first visits
Completed reports and requisitions
Store inventory

22. Data Warehouse and Operational Data Comparison
Data warehouse data
Application-oriented
Subject-oriented
Detailed
Summarized, otherwise refined
Accurate, as of the moment of access
Represents values over time: snapshots
Serves the clerical community
Serves the managerial community
Can be updated
Are not updated
Run repetitively and nonreflectively
Are run heuristically
Performance sensitive (immediate response required when entering a transaction)
Performance relaxed (immediacy not required)
Transaction driven
Analysis driven
High availability
Relaxed availability

23. Data Warehousing Process Iterative Development Process
Start with one subject area (or subset or superset) and one target user group.
Continue to add subject areas, user groups, and informational capabilities to the architecture.
The process is based on the organization’s requirements for information, not technology.
Improvements are made from what was learned from previous increments.
Improvements are made from what was learned about warehouse operation and support.
The technical environment may have changed.
Results are seen very quickly after each iteration.
The end-user requirements are refined after each iteration.

24. This presentation was produced with the support of the United States Agency for International Development (USAID) under the terms of MEASURE Evaluation cooperative agreement AID-OAA-L MEASURE Evaluation is implemented by the Carolina Population Center, University of North Carolina at Chapel Hill in partnership with ICF International; John Snow, Inc.; Management Sciences for Health; Palladium; and Tulane University. Views expressed are not necessarily those of USAID or the United States government.
This slide deck is adapted from MEASURE Evaluation’s Routine Health Information Systems: A Curriculum on Basic Concepts and Practice. The complete RHIS curriculum is available here: