Introduction to Databases PDF

INTRODUCTION TO DATABASES Understanding about Databases is essential since they are under every aspect of today´s digital world facilitating efficient data management across the different industries: - E-commerce Platforms - Social Media Networks - Banking and Financial Services -...

INTRODUCTION TO DATABASES Understanding about Databases is essential since they are under every aspect of today´s digital world facilitating efficient data management across the different industries: - E-commerce Platforms - Social Media Networks - Banking and Financial Services - Healthcare Systems - Educational Institutions - Logistics and Supply Chain Management - Customer Relationship Management (CRM) - Government Services Different ways to store and manage information Paper Magnetic Tapes Books and Accounting Records Electronic Files and Directories These methods had limitations: ➔ Difficulty in searching and retrieving ➔ Lack of integrity and security ➔ Inability to handle large volumes of data 1970s: ER Model - Introduction of the Entity-Relationship model as a standard tool for database design - Oracle introduces the first RDBMS 1980s: DBMS / SQL - IBM creates SQL and it becomes the standard language - More companies creating RDBMS like Sybase introducing the early Microsoft SQL Server. 1990s: NoSQL / Data mining  - NoSQL Databases starting to manage not structured data (images, text, audios – other type of information) - Data Warehousing (DataLake: place where there are many databases to analyze data from different databases) and Data mining (data analytics – analysis of data) appear. 2000s: Big Data / Cloud - Open source databases (free version – MySQL, Postgree, Neo4j) - Database products for large volumes - DataLake concepts - Databases in the cloud and serverless solutions Database: collection of interrelated data that is organized and stored in such a way that it can be easily accessed, managed and updated. It consists of tables, each containing rows and columns where data is stored and related to other tables through relationships. Databases can store information about people, products, orders or other things. Many databases start as a list in a spreadsheet or word processing program. As the list grows, data redundancies and inconsistencies start to appear. It becomes increasingly difficult to understand data in list form, and methods for searching or extracting subsets of data for review are limited. Once these problems start to appear, it´s a good idea to transfer the data to a database created with a database management system (DBMS) Database Management System (DBMS): software designed to manage databases, providing functionalities to define, create, query (search & select), update and administer databases. It acts as an interface between users and the database, ensuring efficient storage, retrieval and manipulation of data while maintaining data integrity and security. Oracle Database, Microsoft SQL Server, MySQL. *It helps you organize the different tables included in the database. DBM Tools and Software: applications that help users create, manage and manipulate databases. They provide an interface to interact with the data and perform various operations like querying, updating and reporting. - Storage: large volumes in structured format - Retrieval: querying capabilities using languages like SQL - Manipulation: insert, update and delete - Integrity: accuracy and consistency through constraints, validation rules and transactions - Security: protecting data with user authentication - Back up and recovery: offering tools for data backup and recovery  - Performance optimization: including features like indexing (creating a number for a field that is a text), caching (already stored in the devide), query optimization for better performance (doing it quicker) One of the main purposes of DBMS is to provide users with a simplified view of the data, hiding the complexities of how the data is stored and managed. 1. CONCEPTUAL DESIGN: defining the main entities and relationships in a way that is technology-agnostic. Highest level of abstraction. 2. LOGICAL LEVEL: detailed but still abstract, specifying tables, columns and relationships, ready to be mapped to a specific DBMS. 3. PHYSICAL LEVEL: describes how data is really stored. Is the lower level. o NN: not null – ese campo no puede estar vacío o PK: primary key – único, que no se puede repetir o FK: foreign key – conectar dos tablas (poner solamente el PK de una tabla en la que está el resto de la información para no repetirla entera) Provide a structured way to store data related to markets, transactions, financial records Organizing the data into easily accessible formats for data analysis, reporting, prediction Facilitating informed decision making, identifying trends and performing accurate forecasting Maintaining accuracy and confidentiality of sensitive financial information