1. Introduction to Health Care Data Analytics
Module 4: Data Analysis Tools
and Techniques
Welcome to Module 4, Data Analysis Tools and Techniques, lecture c, Databases, Part II.
Lecture c, Databases Part II
This material was developed through a collaboration between Bellevue College and the Veterans Health Administration, U.S. Department of Veterans Affairs, funded in part by the Department of Health and Human Services, Office of the National Coordinator for Health Information Technology award number 90WT0002.
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2. Learning Objectives Define data analytics terms
Describe the process steps of data analytics and the tools used in each step
Describe the role of the data analyst
Identify tools and techniques used to analyze and interpret health care data effectively
Describe key database concepts.
Describe the various types of databases and how they are structured
Describe key data warehouse concepts
Describe enterprise data architecture as seen in health care organizations
The learning objectives include
Define data analytics terms
Describe the process steps of data analytics and the tools used in each step
Describe the role of the data analyst
Identify tools and techniques used to analyze and interpret health care data effectively
Describe key database concepts
Describe the various types of databases and how they are structured
Describe key data warehouse concepts
Describe enterprise data architecture as seen in health care organizations
This lecture will focus on objective numbers five and six.

3. Overview
This lecture further explores the various conceptual models of database designs and types of queries
This lecture explores databases in more detail, focusing on the various types of conceptual models for databases and the use of queries.
Image by Stuart Miles, 2014

4. Types of Databases
Databases and database management systems (DBMS) are categorized by structure (how the data is related or organized)
Example database models:
Flat file
Hierarchical
Network
Relational
Object oriented
Databases and database management systems have evolved in line with the increase in the types of data requiring analysis as well as the increased need for interfaces that are user friendly and able to support ad hoc queries created by end users. As database management systems have matured, they have improved data security, data integrity, and user interfaces, reducing the need for complex programming to design databases and create queries.
Database systems can be categorized by their structure or data model, which indicates how the data is related or organized. Database models include, among others, flat file, hierarchical, network, relational, and object oriented.

5. Flat File Database
Contains one table without any structured relationship between the records
Advantages: Simple, all records stored in one place, easy to search and filter
Disadvantages: Cannot handle large volumes of data, data redundancy, low data security, multiple versions
Example: Microsoft Excel spreadsheet
A flat file database system is a database composed of a single table that contains records without any structured relationship between the records. A flat file contains multiple instances of data redundancy. For instance, notice that several patients’ names are repeated in the flat file example below. There are other instances of data redundancy in the chart. Can you find them?
An example of a simple flat file is a Microsoft Excel spreadsheet. Spreadsheets are useful for a single user tracking information for his or her own personal use or for pulling data from other sources to create simple reports. They’re easy to set up and easy to understand. Because all of the records are stored in one table, they can be sorted, searched, and filtered. However, these types of databases cannot handle a large volume of data or multiple users. The larger the data set in a flat file, the more difficult it is to maintain the integrity of the data. Data integrity also may be compromised if a variety of versions of the same table are used by various people.

6. Hierarchical Database
Widely used on mainframe computers in the 1960s; found today on older systems
Data is organized in a tree-like structure
Each child record has one and only one parent (1:1)
Each parent record can have one or more child records (1:M)
Relationships are organized using address pointers linking records
Start at the root to retrieve data
VA (VISTA) is a hierarchical database
In a hierarchical model, data is organized in a tree-like structure, implying a single parent for each record. Hierarchical databases were widely used on mainframe computers in the 1960s and are found today on older systems.
The hierarchical database model mandates that each child record has only one parent (one-to-one relationship), whereas each parent record can have one or more child records (one-to-one or one-to-many relationship).
The relationship of parent to child is organized using address pointers, which link each parent record with each child record. To retrieve data from a hierarchical database, the whole tree needs to be traversed starting from the root. The root is the first or top level of the hierarchy, depicted as the top box or parent in a hierarchical diagram.
Shelly, Cashman & Rosenblatt, 2003
Image by Brandt, K., 2016

7. Hierarchical Database: Parent-to-Child Relationships
In this diagram, each box represents an entity. Similar to a tree diagram depicting a family tree, each box can be either a parent or a child. The very top box is called the root. This tree shows the parent-to-child relationship.
Image by Brandt, K., 2016

8. Hierarchical Database Example
Here’s a simplified example of a hierarchical database. To find information concerning medications, you must start with the root, which in this example is “Patients.” You then follow the path based on the hierarchal model to find the files pointing to medications.
Image by Brandt, K., 2016

9. Hierarchical Database: Advantages & Disadvantages
Able to handle large volumes of data
Able to map simple business processes (one to many)
Improved data integrity, data security, data sharing, and access speed
Disadvantages
Not user friendly
Data structural dependencies
Cannot model all types of relationships
Reduced flexibility
Lack of standards
The advantages of hierarchical databases include
The ability to handle large volumes of data
The ability to map business processes that depict simple relationships (one to many)
Improved data integrity and data security
Improved data sharing (one version used by all), and
Improved access speed due to predefined data paths
There are also some disadvantages. One disadvantage is that they are not user friendly. To access data, users need complex programming knowledge and must know where the data is distributed physically. Management difficulties arise because of structural dependencies whereby any changes in the structure of the database require changes in all application and programs that access the database. Hierarchical databases cannot model all types of data relationships, such as many-to-many relationships. Only expert users can perform ad hoc queries in a hierarchical database, which makes it less flexible. Additionally, a lack of standards for database concepts, components, or language used to manipulate the database contents limits the ability to import or export data from one hierarchical database to another.

10. Network Database
Similar to the hierarchical database in structure except that each child entity can have more than one parent
Each relationship called a set
Each set contains a parent record (owner) and child (member)
Not widely used today but may exist in legacy systems
Advantages: Map complex relationships, improved structural dependencies
Disadvantages: Still not user friendly
A network database is similar to a hierarchical database except that each child entity can have more than one parent. Each relationship is called a set, and each set contains a parent record or owner and a child or member.
Network databases are not widely used today but may still exist in older legacy systems. Note that “network database” refers strictly to the structure of the data and is not the same as a database residing on a network.
Network databases are useful for modeling complex relationships in the real world (such as many-to-many relationships). They offer an improvement to the data structural dependencies in that any changes in the data structure do not require changes in the programs and applications that access the database, and they do impose a database standard. However, the disadvantage is that the network database model is more complex than other models, and users still must learn the physical representation of the database, so these systems are not user friendly.
Image by Brandt, K., 2016

11. Relational Database Most common type of database
Tables are connected via primary and foreign keys
Primary key (PK): Unique identifier for each distinct row within a table
Foreign key (FK): An identifier that is a primary key in a different table
Relationship between PK and FK are displayed using an entity relationship diagram or E-R diagram
Examples: Microsoft Access, SQL Server, MySQL, IBM DB2, Oracle Database
A relational database is the most common type of database. In a relational database, tables are connected via primary and foreign keys. A primary key is a unique identifier for each distinct row within a table. A foreign key is an identifier that is a primary key in a different table.
The relationship between the primary keys and foreign keys of a database are displayed using an entity relationship diagram, or E-R diagram.
Examples of relational database management systems include Microsoft Access, Microsoft SQL [sequel] Server, MySQL (Oracle), IBM DB2, and Oracle Database.

12. Entity Relationship Diagram (E-R Diagram)
There are many different tools that can be used to create E-R diagrams. This entity relationship example was created using Microsoft Access.
Image by Brandt, K., 2016, using Microsoft Access Northwind sample database

13. ER-Diagram Example One patient has one or more appointments
One or more appointments are scheduled for one patient
Let’s consider another example. Remember the business rule that one patient can make or have many appointments? This is what the E-R diagram would look like. The primary key, or unique identifier, in the Patients table is the Patient ID, which is linked to the Appointments table through the Patient ID or the foreign key in a one-to-many relationship.
Image by Brandt, K., 2016

14. Relational Database: Advantages & Disadvantages
User friendly
Complete data structure independence
Improved security with privilege access control
Reduced data redundancies
Perform ad hoc queries with SQL
Disadvantages
Costly to set up and maintain
Changes between the relationship between tables may affect other relationships within the database
Multiple versions
A relational database has several advantages. It’s user friendly. Users don’t need to know the physical representation of the database to access the data, and the design is simplified with tabular views. In addition, there’s complete data structure independence, improved security with privilege access control (that is, restricted access to data based on the user’s role), and reduced data redundancies (because data is stored only once). Relational databases allow users to perform ad hoc queries or complex queries using a simple query language (SQL).
However, relational databases can be costly to set up and maintain. Due to the relational nature of the tables, changing one table relationship may affect other tables within the database. In addition, since relational databases with their relational database management systems are easy to create and use, there’s an increased chance of having more than one version (similar to the flat file databases) because many users may have their own version of the same database.

15. Object-Oriented Database
Developed for more complex data types (images, audio, and video)
Represent real-world objects
Data and their relationships are in a single structure
Advantages:
Can store more complex types of data
Disadvantages:
Not user friendly
Lack of marketing interest
Lack of standards
Decreased flexibility
The final type of database is the object-oriented database. Hierarchical, network, and relational databases were developed to store text and numeric data and were not designed to store more complex types of data such as x-ray images, ultrasound images, MRI scans, and electrocardiograms. The object-oriented database was developed to handle these more complex data types.
The object-oriented database models both the data and their relationships in a single structure known as an object.
An object represents a real-world entity, such as clinic appointments, and includes data about that entity and operations that work with that data (for example, patients or location of the clinic). Although object-oriented databases can store more complex types of data, they’re not widely marketed for various reasons, including a steep learning curve to implement and use, lack of major vendor marketing interest, lack of standards, and decreased flexibility in that users are unable to perform ad hoc queries. Relational databases still remain the most popular databases in use today.

16. Object-Oriented Database Example
In an object-oriented database, an E-R diagram of patients, appointments, and locations would be converted to a single object—appointments—with a relationship to patients and locations as one-to-many.
Image by Brandt, K., 2016

17. Flat & Hierarchical Databases: Advantages & Disadvantages
Database Structure
Advantages
Disadvantages
Flat
Simple to set up
Records stored in one place
Easy to understand
Records are in one table, making it easy to search and filter
Difficult to manage large volumes of data
Data redundancy
Low security
Multiple versions possible
Hierarchical
Manages large volumes of data
Able to model business processes and data as simple relationships
Increased data security and data integrity due to DBMS
Improved data sharing (one version used by all)
Speed of access increased due to predefined data paths
Not user friendly
Difficult to manage due to data structural dependencies
Unable to model all types of real-world data relationships
Reduced flexibility
Lack of standards
Scan the table that spans the next three slides to review a summary of the advantages and disadvantages of the various types of database conceptual models. This slide highlights the advantages and disadvantages of the flat and hierarchical database models.

18. Network & Relational Databases: Advantages & Disadvantages
Database Structure
Advantages
Disadvantages
Network
Deals with large amounts of data (more than hierarchical)
Able to map more complex relationship types
Improved data structural independence
High-speed data retrieval
Database standards
Promotes data integrity
Still not user friendly
System complexity—more than hierarchical
Relational
Supports large volumes of data
User friendly
Structural independence
Better security with privilege access control
Reduced data redundancy—data is stored once
Query language to create complex queries (SQL)
Expensive to set up and maintain
Data complexity—lots of records can be affected through a change in the relationship structure
Multiple versions possible
This slide highlights the advantages and disadvantages of the network and relational database models.

19. Object Oriented Database: Advantages & Disadvantages
Database Structure
Advantages
Disadvantages
Object Oriented
Able to store complex data types (graphics, video and audio)
Not user friendly
Not widely accepted by major vendors
Lack of standards
Reduced flexibility (lacks ad hoc query capability)
This slide highlights the advantages and disadvantages of the object-oriented database model.

20. Query A question answered by the database
May use various methods, such as Structured Query Language (SQL) and Query-by-Example (QBE)
Results presented on screen to be saved or printed
A query is a question that’s answered by the database. In a query, certain criteria are specified to pull the desired results. For example, you might ask for all of the patients who had appointments for the diabetes clinic in the month of October The criteria selected would include patients’ names, patients’ clinic appointments that equal diabetes clinic, and all dates that equal October The query results will be presented on the screen, which can then be printed or stored in a file.
A query language uses English-like statements to assist in preparing a query. Most relational databases support the Structured Query Language (SQL). Another method for developing queries is the Query-by-Example (QBE) method, which uses a graphical interface to enable the user to specify the criteria for selecting records.

21. Query-by-Example (QBE)
Query Example
SQL Statement
Suppose we want to know all of the customers who placed orders to be shipped to New York. We select first name, last name, and ship state with the specified criteria NY. On this slide, you see what this query would look like using the Query by Example and the SQL statement methods, and the query results are shown at the bottom right.
Query-by-Example (QBE)
Query Results
Images by Brandt, K., 2016

22. Summary Conceptual database model:
A database structure using entities, attributes and instances
Depicts relationships between entities
Follows business rules
Types: Flat, hierarchical, network, relational and object oriented
Database queries can be performed using SQL and QBE methods
In this presentation, we reviewed five major types of database models—flat, hierarchical, network, relational, and object oriented. The advantages and disadvantages of each database type were discussed. Finally, queries, which are questions to be answered by the database, were presented with two different methods of creating queries: Structured Query Language (SQL) and Query-by-Example (QBE). In the next lecture, we’ll review a unique type of database, the data warehouse.

23. Data Analytics Tools and Techniques References – Lecture c
Capron, H. L., & Johnson, J. A. (2004). Computers: Tools for an information age (8th ed.). Upper Saddle River, NJ: Prentice Hall.
Rob, P., & Coronel, P. (2004). Database systems: Design, implementation & management (6th ed.). Boston: Course Technology.
Shelly, G. B., Cashman, T. J., & Rosenblatt, H. J. (2003). Systems analysis and design (5th ed.). Boston: Course Technology.
Images
Slide 3: Miles, Stuart (2014). Database magnifier shows bytes magnification and computing stock photo. Retrieved from
Slides 5–8, 10, 12–13, 16: Brandt, K. (2016). Graphics
No audio.
Health IT Workforce Curriculum Version 4.0

24. Introduction to Health Care Data Analytics: Data Analytics Tools and Techniques Lecture c
This material was developed through a collaboration between Bellevue College and the Veterans Health Administration, U.S. Department of Veterans Affairs, funded in part by the Department of Health and Human Services, Office of the National Coordinator for Health Information Technology award number 90WT0002.
No audio.
Version 1.0/Fall 2016