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data Resources: an introduction for understanding
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- 2. Database and DataOrganization What is Data? Data refers to raw facts or figures that by themselves may not have meaning. Example: Numbers, letters, symbols (A–Z, 0–9, %, $, etc.). When data is processed and organized, it becomes information.
- 3. Logical Organization ofData Data in a database is organized in a hierarchical structure: 1. Character o The smallest logical data element. o A single letter, digit, or symbol. o Example: A, 5, @. 2. Field o A group of related characters. o Example: "Name", "Age". 3.Record A collection of related fields. Example: A student’s row in a table (Name, Age, Roll No.). 4.Table (File) A collection of related records. Example: Student Table containing all students’ records. 5 Database A collection of related tables. It stores data so it can be accessed, managed, and updated by many users for different purposes.
- 4. Record in aDatabase A record is a single row in a database table. Each record is divided into fields (columns). Roll no Name Age course 101 Arjun 20 BBA 102 meera 21 MBA Row = records eg. Arjun detail Column = field name and age
- 5. Database • A databaseis a collection of related information stored in such a way that it can be: a. Retrieved b. Analyzed c. Updated d. Used by multiple applications and users Database is where data resides.
- 6. Traditional File ProcessingSystem • Before databases, data was stored in paper files or electronic files. • Problems with traditional file systems: 1. Data Redundancy (same data stored in many files). Customer details stored separately in sales, accounts, and dispatch files. 2. Lack of Data Integrity (changes in one file not reflected in others). 3. Difficulty in Access (hard to retrieve specific data). 4. Poor Security (files easily duplicated or lost).
- 7. The disadvantages ofthe traditional file system led to the development of the database approach, which is more flexible, secure, and independent. In this approach, data that was earlier stored in separate files is consolidated into a common pool of data elements. This shared data can then be used by many applications and users across an organization. Approach to Database Management
- 8. In a traditionalfile system, each department (sales, shipping, accounts, customer care) would maintain its own separate files for the same customer. This would lead to duplication, inconsistency, and difficulty in sharing data. With the Database Management Approach: • All data is stored in a central database. • Different departments access the same shared data according to their needs. How it works: Customer places an order → Information stored in the central database. Inventory Department → Checks stock availability from the same database. Accounts Department → Retrieves payment status from the database. Shipping Department → Uses the same database to update delivery details. Customer Care → Can access order history and status instantly. Example
- 9. Another Indian example IRCTCRailway Reservation System – All train ticket bookings, passenger details, and seat availability are stored in a central database, so whether you book online, at a counter, or via an app, the same updated data is visible everywhere.
- 10. In a universitysystem, student information (name, roll number, course, fees, grades) is stored in a single database. ➢ The accounts department uses it for fee details. ➢ The examination department uses it for grades. ➢ The library uses it for book issuance. This avoids duplication of student records in separate files and ensures all departments see consistent data. Example
- 11. Database Management System(DBMS) A DBMS is the main software tool in the database approach. It controls the creation, maintenance, storage, and use of data within an organization. Both administrators and end users depend on it for managing and accessing data. the Census Commission of India (specifically, the Registrar General and Census Commissioner of India) launched the CensusInfo India software in 2012 to help manage and disseminate its population and housing census data. Developed in partnership with the United Nations, this flexible database technology was designed to provide access to census data and enable users to create their own tables, maps, and charts from the information at various geographical levels.
- 12. Examples of DBMSSoftware • FoxPro • Ingres • Sybase • SQL / Firebird • Lotus Approach • Corel Paradox
- 13. Functions of aDBMS 1. Creation of Databases & Applications – Allows new databases and related applications to be designed. 2. Maintenance of Data Quality – Ensures accuracy, consistency, and security of stored data. 3. Data Usage for Decision Making – Provides required information to end users quickly and efficiently.
- 14. Components of DBMS 1.Tables – Store data in rows and columns. 2. Forms – Easy user interface for data entry. 3. Queries – Used to search and extract specific data. 4. Reports – Structured presentation of information for analysis and decision- making.
- 15. Relational Database ManagementSystem (RDBMS) 1. The Relational Model is the most widely used DBMS model. 2. In an RDBMS, data is stored in tables (relations) consisting of rows (records/tuples) and columns (fields/attributes). 3. A table is called a relation. 4. The key feature: one table can have a relationship with another table through a common data element (key).
- 16. Roll no NameAge Course ID 101 Arjun 20 C1 102 meera 21 C2 103 Rahul 22 C1 Course ID Course name Duration C1 BBA 3 yr C2 MBA 2 yr Relationship • Arjun (StudentID 101) → CourseID C1 → BBA • Meera (StudentID 102) → CourseID C2 → MBA • Rahul (StudentID 103) → CourseID C1 → BBA Course ID : primary key in this table The same course ID appears in the student table to show which student has enrolled in which course. Course table Student table
- 17. • Row =Record • Column = Field • Table = Relation • Common Field = Relationship between tables
- 18. RDBMS Advantages • StructuralIndependence – Changes in database structure (like adding a new column) don’t affect how users interact. • Simplicity of Design and Use – Data is stored in tables (rows & columns), which is easy to understand. • Advanced Query Capabilities – SQL queries allow quick retrieval, filtering, and updating of data.
- 19. Object-Oriented Database ManagementSystem (OODBMS) • Stores data in the form of objects, similar to object-oriented programming. • Useful when data is complex (images, videos, multimedia). Eg… In a hospital system, a Patient Object may include details, medical history, test reports, and X-rays stored together.
- 20. Multidimensional Database ManagementSystem (MDDBMS) • Stores data in a cube form (dimensions) instead of simple tables. • Best for analysis, reporting, and business intelligence. Eg… A sales database can be viewed by Product, Region, and Time (3D cube).
- 21. 1.Database Designing The processof structuring a database for efficiency and accuracy. • Data Planning – Identifying what data is required. • Relational Identity – Defining relationships among data tables. • Normalization – Removing redundancy and ensuring consistency. • Entity-Relationship Diagram (ERD) – Visual model of entities (tables) and their relationships. • Physical Model – Actual implementation on hardware and software. Eg. A university database with entities like Students, Courses, and Professors, linked via ERD.
- 22. Client-Server and DistributedDatabase • Client-Server Database – Data is stored on a server; clients (users) access it via a network. Ex-- Bank databases accessed by different branches. • Distributed Database – Data is stored across multiple locations, but appears as a single database to users. Ex-- Google stores your Gmail data in multiple data centers across the world.
- 23. Managing Database • InformationPolicies – Rules on who can access what data. • Database & Data Governance – Ensures accuracy, security, and compliance of data usage. • Database Tuning – Optimizing performance (faster queries, reduced delays).
- 24. Latest Trends inDatabase Management • Data Warehousing – Central repository that stores huge amounts of data from multiple sources for reporting. • Data Mining – Process of discovering patterns, trends, and hidden information from large datasets. • Web Mining – Data mining applied to the web (user behavior, website clicks, online shopping patterns). Amazon uses data mining to recommend products based on past purchases.
- 25. Online Analytical Processing(OLAP) • A tool for multidimensional analysis of data. • Allows users to “slice and dice” data in different ways (e.g., by product, time, or region). • Generates complex reports from large enterprise databases. Eg… A company can analyze sales: • By Year → Region → Product • Or by Product → Month → Salesperson Relation: • OLAP works on Multidimensional Databases. • Data Warehouses provide the source for OLAP analysis.