Data and Knowledge Management
Defining Big Data
Big Data Generally Consist of: – Traditional enterprise data –Machine-generated/sensor data – Social Data – Images captured by billions of devices
located around the world
Characteristics of Big Data
The Database Approach
Database management system (DBMS) minimize the following problems:
Data Hierarchy Bit
File (or table)
Designing the Database
• Database designers plan the database design in a process called entity- relationship (ER) modeling.
• ER diagrams consists of entities, attributes and relationships. – Entity classes – Instance – Identifiers
Database Management Systems
Database management system (DBMS)
Relational database model
Structured Query Language (SQL)
Query by Example (QBE)
Normalization • Normalization is a method for analyzing
and reducing a relational database to its most streamlined form for: –Minimum redundancy –Maximum data integrity – Best processing performance
• Normalized data is when attributes in the table depend only on the primary key.
Data warehouses and Data Marts Organized by business dimension or
subject. Multidimensional. Historical. Use online analytical processing.
Benefits of Data Warehousing
•End users can access data quickly and easily via Web browsers because they are located in one place. •End users can conduct extensive analysis with data in ways that may not have been possible before. •End users have a consolidated view of organizational data.
• A data mart is a small data warehouse, designed for the end-user needs in a strategic business unit (SBU) or a department.
• Knowledge management (KM)
• Intellectual capital (or intellectual assets)
Knowledge Management System Cycle
•Create knowledge •Capture knowledge •Refine knowledge •Store knowledge •Manage knowledge •Disseminate knowledge