DATA PROCESSING

DATA/ INFORMATION:

- are raw uninterrupted     fact that are without meaning.

-When data are interpreted, information is produced. While data are meaningless, information by definition is meaningful. For data to be interpreted and information produced, the data must be processed.

Some common approaches in organizing data:

Ø   Sorting

Ø   Classifying

Ø   Summarizing

Ø  Calculating

DATABASE

-is an organized collection of related data.

-A common paper example is PHONEBOOK; A much more complex example can be a PATIENT’S MEDICAL RECORD

Factors of finding information in databases:

v  How the data are named (indexed) and organized.

v  The size and complexity of the database.

v  The type of the data within the database.

v  The methodology or tools used to search the database

Information system

-are used to process data and produce information.

-it is often used to refer to computer systems, but this is only one type of information system. There are manual information systems as well as human information system.

Human Brain

-is the most effective and complex information system.

Types of data

1.       Computer-based data types

- this classification is used to build the physical database within the computer system. It identifies the number of spaces needed to capture each data element and specific function that can perform on these data.

Alphanumeric data – include letters and numbers in any combination.

Social security number – is an example of alphanumeric data made up of numbers.

Memo  - is a specific type of alphanumeric data with increased spaces and decreased indexing option.

Numeric data – are used to perform numeric functions including adding, subtracting, multiplying and dividing. It can be long integer, currency or scientific.

Date and time

-are special types of numeric data with which certain numeric functions are appropriate.

Logic Data

-          Are data limited to two options.

-          Ex: yes or no; true or false

2. Conceptual data types

-reflect how users view the data, these can be based on the source of the data

Example: the lab produces lab data, and the x-ray department produces image data.

-          It can also be based on the event that the data are attempting to capture.

-          Examples of data  that reflect event capturing:

q  Assessment data

q  Intervention and outcomes data

One of the major advantages if an information system is that each of these data elements can be captured once and used many times by different purposes, This is referred to as “ DATA COLLECTED ONCE, USED MANY TIMES.”

DATABASE MANAGEMENT SYSTEMS (DBMSs)

-are computer programs used to input, store, modify, process and access data in a database. Before the DBMS can be used, the DBM software must first be configured to manage the data specific to the project. This process of configuring the database software is called DATABASE SYSTEM DESIGN.

A functioning DBMS consists of three (3) interacting parts:

1.       The data

2.       The DBMS configured software program

3.       The query language used to access the data.

SOME EXAMPLES OF DBMS:

Ø  Computerized library systems

Ø  Automated teller machines

Ø  Flight reservation systems

ADVANTAGES OPFG AUTOMATED DATABASE MANAGEMENT SYSTEM:

ü  Decrease data redundancy

ü  Increase data consistency

ü  Improve access to all data

Types of files

1.PROCESSING FILES

Executable files consist of a computer program or set of instructions that, when executed causes the computer to open or start a specific computer program or function.

-are the files that tell a computer what actions the computer should perform when running a program.

Command files- are a set of instructions that perform a set of functions as opposed to running a whole program.

BATCH FILE- contains a set of operating system commands.

2. DATA FILES

-contain data that have been captured and stored on a computer using a software program. Many times the extension for the file identifies he software program used to create the file.

The master index file- contains the unique identifier and related indexes for all entities in the database.

Conceptual model

-Includes a diagram and narrative description of the data elements, their attribute, and the relationship between the data. It defines the structure of the whole database in terms of the attributes of entities (data elements) relationships, constrain and operation

Structural or physical data records

-includes each of the data elements and the relationship between the data elements, as they will be physically stored on the computer.

FOUR (4) PRIMARY APPROACHES TO THE DEVELOPMENTR OF A PHYSICAL DATA MODEL:

1. HIERARCHICAL

-all access data starts at the top of the hierarchy or at the root. In a parent node may have several children nodes, but each child node can only have one parent node.

- Are very effective at representing one-to-many relationships; however they have some disadvantages. Many data relationships do not fit to one-to-many- model

2. NETWORK MODEL

-developed from hierarchical model. In a network model, the child node is not limi8ted to one parent.

3. RELATIONAL DATABASE MODELS

-consists of a series of files set up as tables, each column represents an attribute, and each row is a record. Another name for a row is “tuple”.

-joins any two or more files that generates a new file from the records that meet the matching search criteria.

4. Object-Oriented Model

-this model is developed because the relational model has a limited ability to deal with binary large objects or BLOBs.

BLOBs-are complex data types such as images, sounds, spreadsheets, or text messages. They are large monatomic data with parts and subparts that are not easily represented in a rational database.

DATABASE LIFE CYCLE

-The development and use of DBMS follow a systematic process called THE LIFE CYCLE OF A DATABASE SYSTEM.

FIVE(5) STEPS IN LIFE CYCLE PROCESS:

1. INITIATION

-occurs when a need or problem is identified and the development of a DBMS is seen as potential solution.

2. PLANNING AND ANALYSIS

3.DETAILED SYSTEM DESIGN

4.IMPLEMENTATION

5.EVALUATION AND MAINTENANCE

COMMON DATABASE OPERATIONS

3 BASIC TYPES OF DATA PROCESSING OPERATIONS:

1. Data Input Operations

-are used to enter new data, update data in the system or change data in the DBMS.

2. Data Processing Processes

-are DBMS- directed actions that the computer performs on the data once entered into the system.

3. Data Output Operations

-includes online and written reports.

DATA WAREHOUSE a large collection of data imported from several different systems within one data base. The source of the data includes not only internal data from the institution but can also include data from external sources.

Functions of a data warehouse

v  The data warehouse must be able to extract data from the various computer systems and import that data into the data warehouse.

v  The data warehouse must function as a database able to store and process all of the data in the database.

v  The data warehouse must be able to deliver the data in the warehouse back to the users in the form of information

KNOWLEDGE DISCOVERY SYSTEM OR DATA TO KNOWLEDGE APPLICATION

-Process of extracting information and knowledge from a large scale databases.

-uses powerful automated approaches for the extraction of hidden predictive information from large databases

 3 types of data mining processes:

1. PREDICTING-discovering variables that predict or classify a future event.

Ex: decision tree, neural networks

2. DISCOVERY-discoverring patterns, associations, or clusters within a large dataset.

Ex: apriori; fractionalization

3. DEVIATIONS-DISCOVER THE NORM VIA PATTERN RE3COGNITION AND THEN DISCOVER DEVIATIONS FROM THIS NORM.

Ex: scatter plots, parallel coordinates

CRISP-DM MODEL

-is an international cross industry model it is now being applied to data mining within healthcare.

6 PHASES OF DATA MINING PROCESSES DESCRIBED BY CRISP-DM MODEL:

1.Understanding the business

2.Understanding the data

3.Data preparation

4.Modeling

5.Evaluation

6.deployment