Business Intelligence Databases & Information Management PDF

Chapter 6: Foundation Of Business Intelligence Databases & INFORMATION MANAGEMENT Presented By: Yousif Abdelghany  Topic Outlines 1- What is a database, and how does a relational database organize data ? 2- What are the principles of a DBMS ?...

Chapter 6: Foundation Of Business Intelligence Databases & INFORMATION MANAGEMENT Presented By: Yousif Abdelghany  Topic Outlines 1- What is a database, and how does a relational database organize data ? 2- What are the principles of a DBMS ? 3- What are the principal tools and technologies for accessing information from databases to improve business performance and decision making ? 4- Why are data governance and data quality assurance essential for managing the firm’s data resources ? What is a database, and how does a relational database organize data? Database is a structured collection of data organized in a specific way to facilitate easy storage, retrieval, and management of information. Think of it as an electronic filing cabinet, where you can store documents and access them easily. A relational database is a specific type of database that organizes data into tables, rows, and columns. This structure is particularly useful for representing data that has relationships between different entities. What is a database, and how does a relational database organize data? How Relational Databases Organize Data: 1- Tables: Data is stored in tables, where each table represents a specific entity (e.g., customers, products, orders). 2- Rows: Each row in a table represents a record or an instance of that entity (e.g., a specific customer, a particular product). 3- Columns: Each column represents an attribute or property of the entity (e.g., customer name, product price, order date). What are the principles of a Database Management System? ”DBMS” There are 6 main principles of DBMS: 1-Database Modeling: Creates a visual representation of data structures, relationships, and constraints. 2-Database Design: Translates data models into physical database structures, considering performance, scalability, and security. 3-Database Systems: Software systems that manage and store data, providing tools for data definition, manipulation, and querying. What are the principles of a Database Management System? ”DBMS” There are 6 main principles of DBMS: 4-Data Modeling: The process of creating a data model, which is a blueprint for a database 5-Data Management: The practice of organizing, storing, and retrieving data to meet an organization's information needs. 6-Data Science: The field of extracting knowledge and insights from large datasets using statistical and computational techniques. What are the principal tools and technologies for accessing information from databases to improve business performance and decision making? 1-Business Intelligence (BI) Tools: These tools provide a user-friendly interface to analyze and visualize data from databases. Example: Microsoft Power BI: A versatile BI tool for creating interactive reports and dashboards. 2-Data Warehouses and Data Marts: These centralized repositories store and integrate data from various sources, making it accessible for analysis. 3-Data Mining Tools: These tools uncover hidden patterns and trends within large datasets. Example: RapidMiner: A comprehensive data mining platform. 4-SQL (Structured Query Language): A standard language for interacting with databases, allowing users to retrieve, manipulate, and update data. What are the principal tools and technologies for accessing information from databases to improve business performance and decision making? ETL Tools: These tools are used to extract data from various sources, transform it into a suitable format, and load it into a data warehouse or data 1 mart. Data Integration Tools: These tools combine data from multiple sources into a unified view. Cloud-Based BI Platforms: These platforms offer scalable and cost- effective BI solutions, Example: Google Cloud Platform (GCP) Data Analytics: Provides tools for data warehousing, data engineering, and machine learning. By leveraging these tools and technologies, organizations can gain valuable insights from their data, make informed decisions, and improve overall business performance. Why are data governance and data quality assurance essential for managing the firm’s data resources? Ensure data accuracy and consistency: This prevents errors, inconsistencies, and misleading insights. Enhance decision-making: Reliable and accurate data leads to better-informed decisions.. Improve operational efficiency: Well-managed data can streamline processes and reduce costs. Mitigate risks: Data governance and quality assurance help identify and address potential risks, such as data breaches and regulatory non-compliance. Why are data governance and data quality assurance essential for managing the firm’s data resources? Boost customer satisfaction: High-quality data enables personalized experiences and better customer service. Support innovation: Clean and accessible data fuels innovation and new product development. Enhance regulatory compliance: Proper data management helps organizations adhere to data privacy and security regulations. Build trust: Reliable data builds trust among stakeholders, including customers, employees, and investors.  Q&A SESSION