Managing data resources in a traditional file
environment
• An effective information system provides users with accurate, timely, and
relevant information.
• Accurate information is free of errors.
• Information is timely when it is available to decision makers when it is
needed.
• Information is relevant when it is useful and appropriate for the types of
work and decisions that require it.
Database Approach to Data Management
What is database?
A database is a collection of related files containing records on
people, places, or things. One of the most successful databases in
modern history is the telephone book.
For example: The telephone book is a collection of records on
people and businesses who use telephones. The telephone book
lists four pieces of information for each phone user: last name, first
name, address, and phone number.
Database Approach to Data Management
Database Approach to Data
Management
• Organizing data in a relational database
• A database organizes the data much the same
way, grouping related pieces of data together.
• The relational database is the most common type
of database today. Relational databases organize
data into two-dimensional table (called: relations)
with columns and rows. Each table contains data
on an entity and its attributes. For the most part,
there is one table for each business entity.
File Organization Terms and Concepts
• File organization concepts
• Computer system uses hierarchies
• Field: Group of characters
• Record: Group of related fields
• File: Group of records of same type
• Database: Group of related files
• Record: Describes an entity
• Entity: Person, place, thing on which we store
information
• Attribute: Each characteristic, or quality, describing
entity
• E.g., Attributes Date or Grade belong to entity
COURSE
File Organization Terms and Concepts
• A computer system organizes data in a
hierarchy that starts with the bit, which
represents either 0 or 1. Bits can be
grouped to form a byte to represent one
character, number, or symbol. Bytes can
be grouped to form a field, and related
fields can be grouped to form a record.
Related records can be collected to form
a file, and related files can be organized
into a database.
Database Management Systems
▪ A database management system (DBMS) is software that permits an organization to
centralize data, manage them efficiently, and provide access to the stored data by
application programs.
▪ The DBMS is a specific type of software for creating, storing, organizing, and accessing data
from a database.
▪ The DBMS acts as an interface between application programs and the physical data files.
When the application program calls for a data item, such as gross pay, the DBMS finds this
item in the database and presents it to the application program.
Database Management Systems
The DBMS relieves the programmer or end
user from the task of understanding where
and how the data are actually stored by
separating the logical and physical views of
the data.
The logical view: it presents data as they would be
perceived by end users or business specialists,
whereas,
The physical view: it shows how data are actually
organized and structured on physical storage media.
The database management software
makes the physical database available for
different logical views required by users.
Database Management Systems
Microsoft Access is a DBMS
for desktop systems.
MySQL is a popular open-source DBMS,
and Oracle Database is a DBMS for small
handheld computing devices.
Database Management Systems
Structured Query Language (SQL)
Interactive Activity 1
True/False statements:
1. ( ) the DBMS enables the organization to centrally manage data,
their use, and security.
2. ( ) Microsoft Access does not support creating a database.
3. (
) database management systems enables generating reports
and permitting a query.
Problems with the Traditional File Environment
▪ In most organizations, systems tended to grow independently without a
companywide
plan.
Accounting,
finance,
manufacturing,
human
resources, and sales and marketing all developed their own systems and
data files.
▪ The traditional approach to information processing illustrates that each
application, of course, required its own files and its own computer
program to operate.
For example: the human resources functional area might have a personnel
master file, a payroll file, a medical insurance file, a pension file, a mailing
list file, and so forth, until tens, perhaps hundreds, of files and programs
existed.
Problems with the Traditional File Environment
From the Figure:
What could illustrate??
Problems with the Traditional File Environment
Five main problems with the traditional file environment are as:
Data Redundancy and Inconsistency
Data Dependence
Lack of Flexibility
Poor Security
Lack of Data Sharing and Availability
Problems with the Traditional File Environment
Five main problems with the traditional file environment are as
1 - Data Redundancy and Inconsistency:
Data redundancy is the presence of duplicate data in multiple data files so that
the same data are stored in more than one place or location. Data redundancy
occurs when different groups in an organization independently collect the same
piece of data and store it independently of each other. Data redundancy wastes
storage resources and also leads to data inconsistency.
Data inconsistency is a situation where the same attribute may have different
value.
Problems with the Traditional File Environment
Five main problems with the traditional file environment are as
2- Data Dependence:
Data dependence refers to the coupling of data stored in files and the specific
programs required to update and maintain those files such that changes in programs
require changes to the data. In other shorten phrase, if changes in program requires
changes to data accessed by program.
3- Lack of Flexibility:
Lack of Flexibility where a traditional file system can deliver routine scheduled reports
after extensive programming efforts, but it cannot deliver ad hoc reports or respond to
unanticipated information requirements in a timely fashion.
Problems with the Traditional File Environment
Five main problems with the traditional file environment are as
4- Poor Security:
It refers to that there is little control or management of data, access to and
dissemination of information may be out of control. Management may have no way
of knowing who is accessing or even making changes to the organization’s data.
5- Lack of Data Sharing and Availability:
Because pieces of information in different files and different parts of the
organization cannot be related to one another, it is virtually impossible for
information to be shared or accessed in a timely manner.
Capabilities of DBMS
Relational vs Non-Relational Database
Relational database
It represents data as two-dimensional tables (called relations).
For instance, a table with columns and rows, and even cells.
Non-Relational databases
It uses a more flexible data model and are designed for
managing large data sets across many distributed machines and
for easily scaling up or down. They are useful for accelerating
simple queries against large volumes of structured and
unstructured data (e.g., Web, Social media, graphics).
Data Warehouse
What is it and what does it do?
A data warehouse is defined as “a database that stores current and historical data
of potential interest to decision makers throughout the company where the data
originate in many core operational transaction systems, such as systems for sales,
customer accounts, and manufacturing, and may include data from Web site
transactions”.
– The data warehouse consolidates and standardizes information from different
operational databases so that the information can be used across the enterprise for
management analysis and decision making.
How data warehouse works?
The data warehouse extracts
current and historical data from
multiple operational systems
inside the organization. These
data are combined with data from
external sources and reorganized
into a central database designed
for management reporting and
analysis.
The
information
directory provides users with
information about the data
available in the warehouse.
Data warehouse outcomes
❖ The data warehouse makes the data available for anyone to access as needed, but it
cannot be altered.
❖ A data warehouse system also provides a range of ad hoc and standardized query tools,
analytical tools, and graphical reporting facilities
Important Note: Many firms use intranet portals to make the data warehouse information widely
available throughout the firm.
Components of a data warehouse
Peer Activity to answer the following question…
Q: From the figure, name components of data warehouse.
Data mining
Definition
The MIS literature is superabundant with "data mining" definitions. Three
sufficient definitions are as follows:
Data mining is an iterative process within which progress is defined
by discovery, through either automatic or manual methods.
It is a process of finding hidden patterns, relationship in datasets.
It is the process and analysis of (often large) observational data sets
to find unsuspected relationships and to summarize the data in novel
ways that are both understandable and useful to the data owner.
Data mining
Examples
customer
buying patterns
Infers rules to
predict future
behavior
Data mining
What is it and its types?
Clustering
Associations
Sequences
Forecasting
Classification
Data mining
What is it and its types?
Clustering
It works in a manner similar to classification when no
groups have yet been defined.
In sequences , events are linked over time.
Sequences
Forecasting
It uses predictions in a different way. It uses a
series of existing values to forecast what other
values will be.
Data mining
What is it and its types?
Associations are occurrences linked to a single event.
Associations
Classification
It recognizes patterns that describe the group to which an
item belongs by examining existing items that have been
classified and by inferring a set of rules.
What is SQL?
SQL (Structured Query Language) is the standard
universal language used to communicate with
Relational Database Management Systems (RDBMS).
It is the primary tool for data analysts and backend
developers to interact with enterprise systems
directly at the source.
Used to create and manage robust data
architectures.
Retrieves precise data points from millions of
records in milliseconds.
Updates and maintains data securely and efficiently,
ensuring organizational data integrity.
Why Use SQL in Business?
Decision
Support
Handling Big
Data
Automated
Reporting
System
Integration
Providing accurate,
Capability to process
Creating fixed
Seamlessly
real-time data to
millions of records
queries to generate
connecting
management,
much faster and
daily, weekly, or
operational
eliminating
more reliably than
monthly reports
databases to
guesswork from
traditional
automatically, saving
visualization tools
strategic planning.
spreadsheets.
hundreds of hours.
like Power BI or
Tableau.
The Foundation: Tables and Relations
At the core of any Relational Database are Tables. Data
is not stored in a chaotic pile, but in highly organized,
spreadsheet-like structures.
Table: The basic container for data. Example: A
"Customers" table or a "Sales" table.
Rows (Records): Horizontal entries representing
individual instances.
Columns (Fields): Vertical entries representing
attributes.
Relational Database
A system that organizes data into multiple, separate
tables to minimize redundancy, linked together
through logical relationships.
Data Integrity: Primary & Foreign Keys
Keys are the invisible threads that hold a relational database together, ensuring data is
accurate, accessible, and not duplicated.
Primary Key (PK)
Foreign Key (FK)
A unique field that definitively identifies each
A field in one table that refers to the Primary
record in a single table.
Key in another table, creating a structural
Rule 1: It must be absolutely unique.
Rule 2: It cannot be null (empty).
Examples: , .
relationship between the two.
Purpose: Enforces referential integrity.
Example: A
the "Sales" table.
field living inside
Types of SQL Commands
SQL is a broad language categorized by the specific actions the commands perform on the database.
DQL
DML
DDL
Data Query Language
Data Manipulation Language
Data Definition Language
Used purely for fetching and
Used for modifying the
Used for defining and
extracting data from the
actual data living inside the
modifying the structural
database.
tables.
architecture.
SELECT
INSERT,
CREATE,
UPDATE
ALTER
Extracting Data: The SELECT Statement
The SELECT statement is the most frequently used
command in SQL. It reads and retrieves specific
query.sql
data from one or more tables without altering the
underlying data.
-- Retrieving specific columns SELECT
column1, column2 FROM table_name; --
Business Example
The Marketing team needs to launch an SMS
campaign. They need a list of names and phone
numbers extracted from the massive
"Customers" database table.
Business Use Case Execution SELECT
FirstName, LastName, Phone FROM
Customers;
Precise Targeting: The WHERE Clause
Retrieving all records from a table is rarely useful in
business. The WHERE clause acts as a filter,
extracting only the rows that fulfill a specific
filter_query.sql
condition.
-- Using asterisk (*) selects ALL
Business Example
columns SELECT * FROM CommercialUnits
A real estate investor is looking for premium
WHERE SquareFootage > 5000 AND Status
properties. The sales team uses SQL to list all
= 'Available';
available commercial units where the square
footage exceeds a certain threshold.
Data Summarization & Statistics
SQL is not just for extracting raw lists; it contains
built-in Aggregate Functions to perform
aggregate_query.sql
mathematical operations on data sets.
SUM(): Calculates total values.
-- Example: Total sales revenue per
branch SELECT BranchLocation,
COUNT(): Counts the frequency of records.
SUM(SalesAmount) AS TotalRev FROM
AVG(): Calculates averages.
SalesData GROUP BY BranchLocation
ORDER BY TotalRev DESC;
The GROUP BY clause groups rows that have the
same values into summary rows (like a PivotTable).
The Full Picture: Joining Tables
Because relational databases split data into multiple
tables to reduce redundancy, analysts must use JOIN
commands to combine them back together for
reporting.
Function: Combines rows from two or more tables
based on a related column between them
(Primary/Foreign Keys).
INNER JOIN: Returns records that have matching
values in both tables.
LEFT JOIN: Returns all records from the left table,
and the matched records from the right table.
Business Case: High-Value Customer Campaign
Let's apply these SQL commands to solve a real-world business problem.
1. Scenario
2. Problem
3. Goal
The Marketing Department
They need a consolidated list of
Extract a clean report containing
wants to launch an exclusive
customers whose total combined
Customer Name, Phone
promotion specifically targeting
investments exceed $100,000.
Number, and Total Spent using
"High-Value Investors".
SQL.
Step 1: Analyzing the Schema
Before writing code, we must understand the
database structure (the schema). We identify
that the data we need lives in two separate
tables linked by a relationship.
Table 1: Customers
Columns: [CustomerID], [Name], [Phone]
Table 2: Transactions
Columns: [TransID], [CustomerID], [Amount]
Step 2: Linking Data (INNER JOIN)
We combine the customer identity (Name, Phone)
with their financial transactions (Amount) using an
INNER JOIN.
We tell the database exactly how these tables relate
by matching the Primary Key to the Foreign Key.
SELECT Customers.Name, Transactions.Amount
FROM Customers INNER JOIN Transactions ON
Customers.ID = Transactions.CustID;
Step 3: Aggregating and Filtering
Finally, we group by the customer, sum their
transactions,
and
use
HAVING
to
filter
aggregated totals > $100,000.
SELECT Customers.Name, Customers.Phone,
SUM(Trans.Amount) AS TotalSpent FROM Customers
INNER JOIN Trans ON Customers.ID = Trans.CustID
GROUP BY Customers.Name, Customers.Phone HAVING
SUM(Trans.Amount) > 100000 ORDER BY TotalSpent
DESC;